Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process

Proposed Solar-Powered Motion Sensor for Farm... | F1000Research "use strict";function _typeof(t){return(_typeof="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t})(t)}!function(){var t=function(){var t,e,o=[],n=window,r=n;for(;r;){try{if(r.frames.__tcfapiLocator){t=r;break}}catch(t){}if(r===n.top)break;r=r.parent}t||(!function t(){var e=n.document,o=!!n.frames.__tcfapiLocator;if(!o)if(e.body){var r=e.createElement("iframe");r.style.cssText="display:none",r.name="__tcfapiLocator",e.body.appendChild(r)}else setTimeout(t,5);return!o}(),n.__tcfapi=function(){for(var t=arguments.length,n=new Array(t),r=0;r 3&&2===parseInt(n[1],10)&&"boolean"==typeof n[3]&&(e=n[3],"function"==typeof n[2]&&n[2]("set",!0)):"ping"===n[0]?"function"==typeof n[2]&&n[2]({gdprApplies:e,cmpLoaded:!1,cmpStatus:"stub"}):o.push(n)},n.addEventListener("message",(function(t){var e="string"==typeof t.data,o={};if(e)try{o=JSON.parse(t.data)}catch(t){}else o=t.data;var n="object"===_typeof(o)&&null!==o?o.__tcfapiCall:null;n&&window.__tcfapi(n.command,n.version,(function(o,r){var a={__tcfapiReturn:{returnValue:o,success:r,callId:n.callId}};t&&t.source&&t.source.postMessage&&t.source.postMessage(e?JSON.stringify(a):a,"*")}),n.parameter)}),!1))};"undefined"!=typeof module?module.exports=t:t()}(); dataLayer = dataLayer || []; // Standard GTM initialization - Google Consent Mode handles consent automatically (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start': new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0], j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src= 'https://www.googletagmanager.com/gtm.js?id='+i+dl+ '>m_auth=hzk0Vc3qFsQYhCrIoHz68A>m_preview=env-1>m_cookies_win=x';f.parentNode.insertBefore(j,f); })(window,document,'script','dataLayer','GTM-MWFK8L5J'); ;window.NREUM||(NREUM={});NREUM.init={distributed_tracing:{enabled:true},privacy:{cookies_enabled:true},ajax:{deny_list:["bam.nr-data.net"]}}; ;NREUM.loader_config={accountID:"438030",trustKey:"438030",agentID:"772317073",licenseKey:"97f8f67f26",applicationID:"772317073"} ;NREUM.info={beacon:"bam.nr-data.net",errorBeacon:"bam.nr-data.net",licenseKey:"97f8f67f26",applicationID:"772317073",sa:1} ;/*! For license information please see nr-loader-spa-1.236.0.min.js.LICENSE.txt */ (()=>{"use strict";var e,t,r={5763:(e,t,r)=>{r.d(t,{P_:()=>l,Mt:()=>g,C5:()=>s,DL:()=>v,OP:()=>T,lF:()=>D,Yu:()=>y,Dg:()=>h,CX:()=>c,GE:()=>b,sU:()=>_});var n=r(8632),i=r(9567);const o={beacon:n.ce.beacon,errorBeacon:n.ce.errorBeacon,licenseKey:void 0,applicationID:void 0,sa:void 0,queueTime:void 0,applicationTime:void 0,ttGuid:void 0,user:void 0,account:void 0,product:void 0,extra:void 0,jsAttributes:{},userAttributes:void 0,atts:void 0,transactionName:void 0,tNamePlain:void 0},a={};function s(e){if(!e)throw new Error("All info objects require an agent identifier!");if(!a[e])throw new Error("Info for ".concat(e," was never set"));return a[e]}function c(e,t){if(!e)throw new Error("All info objects require an agent identifier!");a[e]=(0,i.D)(t,o),(0,n.Qy)(e,a[e],"info")}var u=r(7056);const d=()=>{const e={blockSelector:"[data-nr-block]",maskInputOptions:{password:!0}};return{allow_bfcache:!0,privacy:{cookies_enabled:!0},ajax:{deny_list:void 0,enabled:!0,harvestTimeSeconds:10},distributed_tracing:{enabled:void 0,exclude_newrelic_header:void 0,cors_use_newrelic_header:void 0,cors_use_tracecontext_headers:void 0,allowed_origins:void 0},session:{domain:void 0,expiresMs:u.oD,inactiveMs:u.Hb},ssl:void 0,obfuscate:void 0,jserrors:{enabled:!0,harvestTimeSeconds:10},metrics:{enabled:!0},page_action:{enabled:!0,harvestTimeSeconds:30},page_view_event:{enabled:!0},page_view_timing:{enabled:!0,harvestTimeSeconds:30,long_task:!1},session_trace:{enabled:!0,harvestTimeSeconds:10},harvest:{tooManyRequestsDelay:60},session_replay:{enabled:!1,harvestTimeSeconds:60,sampleRate:.1,errorSampleRate:.1,maskTextSelector:"*",maskAllInputs:!0,get blockClass(){return"nr-block"},get ignoreClass(){return"nr-ignore"},get maskTextClass(){return"nr-mask"},get blockSelector(){return e.blockSelector},set blockSelector(t){e.blockSelector+=",".concat(t)},get maskInputOptions(){return e.maskInputOptions},set maskInputOptions(t){e.maskInputOptions={...t,password:!0}}},spa:{enabled:!0,harvestTimeSeconds:10}}},f={};function l(e){if(!e)throw new Error("All configuration objects require an agent identifier!");if(!f[e])throw new Error("Configuration for ".concat(e," was never set"));return f[e]}function h(e,t){if(!e)throw new Error("All configuration objects require an agent identifier!");f[e]=(0,i.D)(t,d()),(0,n.Qy)(e,f[e],"config")}function g(e,t){if(!e)throw new Error("All configuration objects require an agent identifier!");var r=l(e);if(r){for(var n=t.split("."),i=0;i {r.d(t,{D:()=>i});var n=r(50);function i(e,t){try{if(!e||"object"!=typeof e)return(0,n.Z)("Setting a Configurable requires an object as input");if(!t||"object"!=typeof t)return(0,n.Z)("Setting a Configurable requires a model to set its initial properties");const r=Object.create(Object.getPrototypeOf(t),Object.getOwnPropertyDescriptors(t)),o=0===Object.keys(r).length?e:r;for(let a in o)if(void 0!==e[a])try{"object"==typeof e[a]&&"object"==typeof t[a]?r[a]=i(e[a],t[a]):r[a]=e[a]}catch(e){(0,n.Z)("An error occurred while setting a property of a Configurable",e)}return r}catch(e){(0,n.Z)("An error occured while setting a Configurable",e)}}},6818:(e,t,r)=>{r.d(t,{Re:()=>i,gF:()=>o,q4:()=>n});const n="1.236.0",i="PROD",o="CDN"},385:(e,t,r)=>{r.d(t,{FN:()=>a,IF:()=>u,Nk:()=>f,Tt:()=>s,_A:()=>o,il:()=>n,pL:()=>c,v6:()=>i,w1:()=>d});const n="undefined"!=typeof window&&!!window.document,i="undefined"!=typeof WorkerGlobalScope&&("undefined"!=typeof self&&self instanceof WorkerGlobalScope&&self.navigator instanceof WorkerNavigator||"undefined"!=typeof globalThis&&globalThis instanceof WorkerGlobalScope&&globalThis.navigator instanceof WorkerNavigator),o=n?window:"undefined"!=typeof WorkerGlobalScope&&("undefined"!=typeof self&&self instanceof WorkerGlobalScope&&self||"undefined"!=typeof globalThis&&globalThis instanceof WorkerGlobalScope&&globalThis),a=""+o?.location,s=/iPad|iPhone|iPod/.test(navigator.userAgent),c=s&&"undefined"==typeof SharedWorker,u=(()=>{const e=navigator.userAgent.match(/Firefox[/\s](\d+\.\d+)/);return Array.isArray(e)&&e.length>=2?+e[1]:0})(),d=Boolean(n&&window.document.documentMode),f=!!navigator.sendBeacon},1117:(e,t,r)=>{r.d(t,{w:()=>o});var n=r(50);const i={agentIdentifier:"",ee:void 0};class o{constructor(e){try{if("object"!=typeof e)return(0,n.Z)("shared context requires an object as input");this.sharedContext={},Object.assign(this.sharedContext,i),Object.entries(e).forEach((e=>{let[t,r]=e;Object.keys(i).includes(t)&&(this.sharedContext[t]=r)}))}catch(e){(0,n.Z)("An error occured while setting SharedContext",e)}}}},8e3:(e,t,r)=>{r.d(t,{L:()=>d,R:()=>c});var n=r(2177),i=r(1284),o=r(4322),a=r(3325);const s={};function c(e,t){const r={staged:!1,priority:a.p[t]||0};u(e),s[e].get(t)||s[e].set(t,r)}function u(e){e&&(s[e]||(s[e]=new Map))}function d(){let e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"feature";if(u(e),!e||!s[e].get(t))return a(t);s[e].get(t).staged=!0;const r=[...s[e]];function a(t){const r=e?n.ee.get(e):n.ee,a=o.X.handlers;if(r.backlog&&a){var s=r.backlog[t],c=a[t];if(c){for(var u=0;s&&u {let[t,r]=e;return r.staged}))&&(r.sort(((e,t)=>e[1].priority-t[1].priority)),r.forEach((e=>{let[t]=e;a(t)})))}function f(e,t){var r=e[1];(0,i.D)(t[r],(function(t,r){var n=e[0];if(r[0]===n){var i=r[1],o=e[3],a=e[2];i.apply(o,a)}}))}},2177:(e,t,r)=>{r.d(t,{c:()=>f,ee:()=>u});var n=r(8632),i=r(2210),o=r(1284),a=r(5763),s="nr@context";let c=(0,n.fP)();var u;function d(){}function f(e){return(0,i.X)(e,s,l)}function l(){return new d}function h(){u.aborted=!0,u.backlog={}}c.ee?u=c.ee:(u=function e(t,r){var n={},c={},f={},g=!1;try{g=16===r.length&&(0,a.OP)(r).isolatedBacklog}catch(e){}var p={on:b,addEventListener:b,removeEventListener:y,emit:v,get:x,listeners:w,context:m,buffer:A,abort:h,aborted:!1,isBuffering:E,debugId:r,backlog:g?{}:t&&"object"==typeof t.backlog?t.backlog:{}};return p;function m(e){return e&&e instanceof d?e:e?(0,i.X)(e,s,l):l()}function v(e,r,n,i,o){if(!1!==o&&(o=!0),!u.aborted||i){t&&o&&t.emit(e,r,n);for(var a=m(n),s=w(e),d=s.length,f=0;fn,p:()=>i});var n=r(2177).ee.get("handle");function i(e,t,r,i,o){o?(o.buffer([e],i),o.emit(e,t,r)):(n.buffer([e],i),n.emit(e,t,r))}},4322:(e,t,r)=>{r.d(t,{X:()=>o});var n=r(5546);o.on=a;var i=o.handlers={};function o(e,t,r,o){a(o||n.E,i,e,t,r)}function a(e,t,r,i,o){o||(o="feature"),e||(e=n.E);var a=t[o]=t[o]||{};(a[r]=a[r]||[]).push([e,i])}},3239:(e,t,r)=>{r.d(t,{bP:()=>s,iz:()=>c,m$:()=>a});var n=r(385);let i=!1,o=!1;try{const e={get passive(){return i=!0,!1},get signal(){return o=!0,!1}};n._A.addEventListener("test",null,e),n._A.removeEventListener("test",null,e)}catch(e){}function a(e,t){return i||o?{capture:!!e,passive:i,signal:t}:!!e}function s(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2],n=arguments.length>3?arguments[3]:void 0;window.addEventListener(e,t,a(r,n))}function c(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2],n=arguments.length>3?arguments[3]:void 0;document.addEventListener(e,t,a(r,n))}},4402:(e,t,r)=>{r.d(t,{Ht:()=>u,M:()=>c,Rl:()=>a,ky:()=>s});var n=r(385);const i="xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx";function o(e,t){return e?15&e[t]:16*Math.random()|0}function a(){const e=n._A?.crypto||n._A?.msCrypto;let t,r=0;return e&&e.getRandomValues&&(t=e.getRandomValues(new Uint8Array(31))),i.split("").map((e=>"x"===e?o(t,++r).toString(16):"y"===e?(3&o()|8).toString(16):e)).join("")}function s(e){const t=n._A?.crypto||n._A?.msCrypto;let r,i=0;t&&t.getRandomValues&&(r=t.getRandomValues(new Uint8Array(31)));const a=[];for(var s=0;s {r.d(t,{Bq:()=>n,Hb:()=>o,oD:()=>i});const n="NRBA",i=144e5,o=18e5},7894:(e,t,r)=>{function n(){return Math.round(performance.now())}r.d(t,{z:()=>n})},7243:(e,t,r)=>{r.d(t,{e:()=>o});var n=r(385),i={};function o(e){if(e in i)return i[e];if(0===(e||"").indexOf("data:"))return{protocol:"data"};let t;var r=n._A?.location,o={};if(n.il)t=document.createElement("a"),t.href=e;else try{t=new URL(e,r.href)}catch(e){return o}o.port=t.port;var a=t.href.split("://");!o.port&&a[1]&&(o.port=a[1].split("/")[0].split("@").pop().split(":")[1]),o.port&&"0"!==o.port||(o.port="https"===a[0]?"443":"80"),o.hostname=t.hostname||r.hostname,o.pathname=t.pathname,o.protocol=a[0],"/"!==o.pathname.charAt(0)&&(o.pathname="/"+o.pathname);var s=!t.protocol||":"===t.protocol||t.protocol===r.protocol,c=t.hostname===r.hostname&&t.port===r.port;return o.sameOrigin=s&&(!t.hostname||c),"/"===o.pathname&&(i[e]=o),o}},50:(e,t,r)=>{function n(e,t){"function"==typeof console.warn&&(console.warn("New Relic: ".concat(e)),t&&console.warn(t))}r.d(t,{Z:()=>n})},2587:(e,t,r)=>{r.d(t,{N:()=>c,T:()=>u});var n=r(2177),i=r(5546),o=r(8e3),a=r(3325);const s={stn:[a.D.sessionTrace],err:[a.D.jserrors,a.D.metrics],ins:[a.D.pageAction],spa:[a.D.spa],sr:[a.D.sessionReplay,a.D.sessionTrace]};function c(e,t){const r=n.ee.get(t);e&&"object"==typeof e&&(Object.entries(e).forEach((e=>{let[t,n]=e;void 0===u[t]&&(s[t]?s[t].forEach((e=>{n?(0,i.p)("feat-"+t,[],void 0,e,r):(0,i.p)("block-"+t,[],void 0,e,r),(0,i.p)("rumresp-"+t,[Boolean(n)],void 0,e,r)})):n&&(0,i.p)("feat-"+t,[],void 0,void 0,r),u[t]=Boolean(n))})),Object.keys(s).forEach((e=>{void 0===u[e]&&(s[e]?.forEach((t=>(0,i.p)("rumresp-"+e,[!1],void 0,t,r))),u[e]=!1)})),(0,o.L)(t,a.D.pageViewEvent))}const u={}},2210:(e,t,r)=>{r.d(t,{X:()=>i});var n=Object.prototype.hasOwnProperty;function i(e,t,r){if(n.call(e,t))return e[t];var i=r();if(Object.defineProperty&&Object.keys)try{return Object.defineProperty(e,t,{value:i,writable:!0,enumerable:!1}),i}catch(e){}return e[t]=i,i}},1284:(e,t,r)=>{r.d(t,{D:()=>n});const n=(e,t)=>Object.entries(e||{}).map((e=>{let[r,n]=e;return t(r,n)}))},4351:(e,t,r)=>{r.d(t,{P:()=>o});var n=r(2177);const i=()=>{const e=new WeakSet;return(t,r)=>{if("object"==typeof r&&null!==r){if(e.has(r))return;e.add(r)}return r}};function o(e){try{return JSON.stringify(e,i())}catch(e){try{n.ee.emit("internal-error",[e])}catch(e){}}}},3960:(e,t,r)=>{r.d(t,{K:()=>a,b:()=>o});var n=r(3239);function i(){return"undefined"==typeof document||"complete"===document.readyState}function o(e,t){if(i())return e();(0,n.bP)("load",e,t)}function a(e){if(i())return e();(0,n.iz)("DOMContentLoaded",e)}},8632:(e,t,r)=>{r.d(t,{EZ:()=>u,Qy:()=>c,ce:()=>o,fP:()=>a,gG:()=>d,mF:()=>s});var n=r(7894),i=r(385);const o={beacon:"bam.nr-data.net",errorBeacon:"bam.nr-data.net"};function a(){return i._A.NREUM||(i._A.NREUM={}),void 0===i._A.newrelic&&(i._A.newrelic=i._A.NREUM),i._A.NREUM}function s(){let e=a();return e.o||(e.o={ST:i._A.setTimeout,SI:i._A.setImmediate,CT:i._A.clearTimeout,XHR:i._A.XMLHttpRequest,REQ:i._A.Request,EV:i._A.Event,PR:i._A.Promise,MO:i._A.MutationObserver,FETCH:i._A.fetch}),e}function c(e,t,r){let i=a();const o=i.initializedAgents||{},s=o[e]||{};return Object.keys(s).length||(s.initializedAt={ms:(0,n.z)(),date:new Date}),i.initializedAgents={...o,[e]:{...s,[r]:t}},i}function u(e,t){a()[e]=t}function d(){return function(){let e=a();const t=e.info||{};e.info={beacon:o.beacon,errorBeacon:o.errorBeacon,...t}}(),function(){let e=a();const t=e.init||{};e.init={...t}}(),s(),function(){let e=a();const t=e.loader_config||{};e.loader_config={...t}}(),a()}},7956:(e,t,r)=>{r.d(t,{N:()=>i});var n=r(3239);function i(e){let t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],r=arguments.length>2?arguments[2]:void 0,i=arguments.length>3?arguments[3]:void 0;return void(0,n.iz)("visibilitychange",(function(){if(t)return void("hidden"==document.visibilityState&&e());e(document.visibilityState)}),r,i)}},1214:(e,t,r)=>{r.d(t,{em:()=>v,u5:()=>N,QU:()=>S,_L:()=>I,Gm:()=>L,Lg:()=>M,gy:()=>U,BV:()=>Q,Kf:()=>ee});var n=r(2177);const i="nr@original";var o=Object.prototype.hasOwnProperty,a=!1;function s(e,t){return e||(e=n.ee),r.inPlace=function(e,t,n,i,o){n||(n="");var a,s,c,u="-"===n.charAt(0);for(c=0;c 2?n-2:0),o=2;o {r(A[T],e,w),r(E[T],e,w)})),r(l._A,"fetch",y),t.on(y+"end",(function(e,r){var n=this;if(r){var i=r.headers.get("content-length");null!==i&&(n.rxSize=i),t.emit(y+"done",[null,r],n)}else t.emit(y+"done",[e],n)})),t}const O={},j=["pushState","replaceState"];function S(e){const t=function(e){return(e||n.ee).get("history")}(e);return!l.il||O[t.debugId]++||(O[t.debugId]=1,s(t).inPlace(window.history,j,"-")),t}var P=r(3239);const C={},R=["appendChild","insertBefore","replaceChild"];function I(e){const t=function(e){return(e||n.ee).get("jsonp")}(e);if(!l.il||C[t.debugId])return t;C[t.debugId]=!0;var r=s(t),i=/[?&](?:callback|cb)=([^&#]+)/,o=/(.*)\.([^.]+)/,a=/^(\w+)(\.|$)(.*)$/;function c(e,t){var r=e.match(a),n=r[1],i=r[3];return i?c(i,t[n]):t[n]}return r.inPlace(Node.prototype,R,"dom-"),t.on("dom-start",(function(e){!function(e){if(!e||"string"!=typeof e.nodeName||"script"!==e.nodeName.toLowerCase())return;if("function"!=typeof e.addEventListener)return;var n=(a=e.src,s=a.match(i),s?s[1]:null);var a,s;if(!n)return;var u=function(e){var t=e.match(o);if(t&&t.length>=3)return{key:t[2],parent:c(t[1],window)};return{key:e,parent:window}}(n);if("function"!=typeof u.parent[u.key])return;var d={};function f(){t.emit("jsonp-end",[],d),e.removeEventListener("load",f,(0,P.m$)(!1)),e.removeEventListener("error",l,(0,P.m$)(!1))}function l(){t.emit("jsonp-error",[],d),t.emit("jsonp-end",[],d),e.removeEventListener("load",f,(0,P.m$)(!1)),e.removeEventListener("error",l,(0,P.m$)(!1))}r.inPlace(u.parent,[u.key],"cb-",d),e.addEventListener("load",f,(0,P.m$)(!1)),e.addEventListener("error",l,(0,P.m$)(!1)),t.emit("new-jsonp",[e.src],d)}(e[0])})),t}var k=r(5763);const H={};function L(e){const t=function(e){return(e||n.ee).get("mutation")}(e);if(!l.il||H[t.debugId])return t;H[t.debugId]=!0;var r=s(t),i=k.Yu.MO;return i&&(window.MutationObserver=function(e){return this instanceof i?new i(r(e,"fn-")):i.apply(this,arguments)},MutationObserver.prototype=i.prototype),t}const z={};function M(e){const t=function(e){return(e||n.ee).get("promise")}(e);if(z[t.debugId])return t;z[t.debugId]=!0;var r=n.c,o=s(t),a=k.Yu.PR;return a&&function(){function e(r){var n=t.context(),i=o(r,"executor-",n,null,!1);const s=Reflect.construct(a,[i],e);return t.context(s).getCtx=function(){return n},s}l._A.Promise=e,Object.defineProperty(e,"name",{value:"Promise"}),e.toString=function(){return a.toString()},Object.setPrototypeOf(e,a),["all","race"].forEach((function(r){const n=a[r];e[r]=function(e){let i=!1;[...e||[]].forEach((e=>{this.resolve(e).then(a("all"===r),a(!1))}));const o=n.apply(this,arguments);return o;function a(e){return function(){t.emit("propagate",[null,!i],o,!1,!1),i=i||!e}}}})),["resolve","reject"].forEach((function(r){const n=a[r];e[r]=function(e){const r=n.apply(this,arguments);return e!==r&&t.emit("propagate",[e,!0],r,!1,!1),r}})),e.prototype=a.prototype;const n=a.prototype.then;a.prototype.then=function(){var e=this,i=r(e);i.promise=e;for(var a=arguments.length,s=new Array(a),c=0;c e())),t};function m(e,t){i.inPlace(t,["onreadystatechange"],"fn-",E)}function b(){var e=this,t=r.context(e);e.readyState>3&&!t.resolved&&(t.resolved=!0,r.emit("xhr-resolved",[],e)),i.inPlace(e,f,"fn-",E)}if(function(e,t){for(var r in e)t[r]=e[r]}(o,p),p.prototype=o.prototype,i.inPlace(p.prototype,J,"-xhr-",E),r.on("send-xhr-start",(function(e,t){m(e,t),function(e){h.push(e),a&&(y?y.then(A):u?u(A):(w=-w,x.data=w))}(t)})),r.on("open-xhr-start",m),a){var y=c&&c.resolve();if(!u&&!c){var w=1,x=document.createTextNode(w);new a(A).observe(x,{characterData:!0})}}else t.on("fn-end",(function(e){e[0]&&e[0].type===d||A()}));function A(){for(var e=0;e {r.d(t,{t:()=>n});const n=r(3325).D.ajax},6660:(e,t,r)=>{r.d(t,{A:()=>i,t:()=>n});const n=r(3325).D.jserrors,i="nr@seenError"},3081:(e,t,r)=>{r.d(t,{gF:()=>o,mY:()=>i,t9:()=>n,vz:()=>s,xS:()=>a});const n=r(3325).D.metrics,i="sm",o="cm",a="storeSupportabilityMetrics",s="storeEventMetrics"},4649:(e,t,r)=>{r.d(t,{t:()=>n});const n=r(3325).D.pageAction},7633:(e,t,r)=>{r.d(t,{Dz:()=>i,OJ:()=>a,qw:()=>o,t9:()=>n});const n=r(3325).D.pageViewEvent,i="firstbyte",o="domcontent",a="windowload"},9251:(e,t,r)=>{r.d(t,{t:()=>n});const n=r(3325).D.pageViewTiming},3614:(e,t,r)=>{r.d(t,{BST_RESOURCE:()=>i,END:()=>s,FEATURE_NAME:()=>n,FN_END:()=>u,FN_START:()=>c,PUSH_STATE:()=>d,RESOURCE:()=>o,START:()=>a});const n=r(3325).D.sessionTrace,i="bstResource",o="resource",a="-start",s="-end",c="fn"+a,u="fn"+s,d="pushState"},7836:(e,t,r)=>{r.d(t,{BODY:()=>A,CB_END:()=>E,CB_START:()=>u,END:()=>x,FEATURE_NAME:()=>i,FETCH:()=>_,FETCH_BODY:()=>v,FETCH_DONE:()=>m,FETCH_START:()=>p,FN_END:()=>c,FN_START:()=>s,INTERACTION:()=>l,INTERACTION_API:()=>d,INTERACTION_EVENTS:()=>o,JSONP_END:()=>b,JSONP_NODE:()=>g,JS_TIME:()=>T,MAX_TIMER_BUDGET:()=>a,REMAINING:()=>f,SPA_NODE:()=>h,START:()=>w,originalSetTimeout:()=>y});var n=r(5763);const i=r(3325).D.spa,o=["click","submit","keypress","keydown","keyup","change"],a=999,s="fn-start",c="fn-end",u="cb-start",d="api-ixn-",f="remaining",l="interaction",h="spaNode",g="jsonpNode",p="fetch-start",m="fetch-done",v="fetch-body-",b="jsonp-end",y=n.Yu.ST,w="-start",x="-end",A="-body",E="cb"+x,T="jsTime",_="fetch"},5938:(e,t,r)=>{r.d(t,{W:()=>o});var n=r(5763),i=r(2177);class o{constructor(e,t,r){this.agentIdentifier=e,this.aggregator=t,this.ee=i.ee.get(e,(0,n.OP)(this.agentIdentifier).isolatedBacklog),this.featureName=r,this.blocked=!1}}},9144:(e,t,r)=>{r.d(t,{j:()=>m});var n=r(3325),i=r(5763),o=r(5546),a=r(2177),s=r(7894),c=r(8e3),u=r(3960),d=r(385),f=r(50),l=r(3081),h=r(8632);function g(){const e=(0,h.gG)();["setErrorHandler","finished","addToTrace","inlineHit","addRelease","addPageAction","setCurrentRouteName","setPageViewName","setCustomAttribute","interaction","noticeError","setUserId"].forEach((t=>{e[t]=function(){for(var r=arguments.length,n=new Array(r),i=0;i 1?r-1:0),i=1;i {e.exposed&&e.api[t]&&o.push(e.api[t](...n))})),o.length>1?o:o[0]}(t,...n)}}))}var p=r(2587);function m(e){let t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{},m=arguments.length>2?arguments[2]:void 0,v=arguments.length>3?arguments[3]:void 0,{init:b,info:y,loader_config:w,runtime:x={loaderType:m},exposed:A=!0}=t;const E=(0,h.gG)();y||(b=E.init,y=E.info,w=E.loader_config),(0,i.Dg)(e,b||{}),(0,i.GE)(e,w||{}),(0,i.sU)(e,x),y.jsAttributes??={},d.v6&&(y.jsAttributes.isWorker=!0),(0,i.CX)(e,y),g();const T=function(e,t){t||(0,c.R)(e,"api");const h={};var g=a.ee.get(e),p=g.get("tracer"),m="api-",v=m+"ixn-";function b(t,r,n,o){const a=(0,i.C5)(e);return null===r?delete a.jsAttributes[t]:(0,i.CX)(e,{...a,jsAttributes:{...a.jsAttributes,[t]:r}}),x(m,n,!0,o||null===r?"session":void 0)(t,r)}function y(){}["setErrorHandler","finished","addToTrace","inlineHit","addRelease"].forEach((e=>h[e]=x(m,e,!0,"api"))),h.addPageAction=x(m,"addPageAction",!0,n.D.pageAction),h.setCurrentRouteName=x(m,"routeName",!0,n.D.spa),h.setPageViewName=function(t,r){if("string"==typeof t)return"/"!==t.charAt(0)&&(t="/"+t),(0,i.OP)(e).customTransaction=(r||"http://custom.transaction")+t,x(m,"setPageViewName",!0)()},h.setCustomAttribute=function(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2];if("string"==typeof e){if(["string","number"].includes(typeof t)||null===t)return b(e,t,"setCustomAttribute",r);(0,f.Z)("Failed to execute setCustomAttribute.\nNon-null value must be a string or number type, but a type of was provided."))}else(0,f.Z)("Failed to execute setCustomAttribute.\nName must be a string type, but a type of was provided."))},h.setUserId=function(e){if("string"==typeof e||null===e)return b("enduser.id",e,"setUserId",!0);(0,f.Z)("Failed to execute setUserId.\nNon-null value must be a string type, but a type of was provided."))},h.interaction=function(){return(new y).get()};var w=y.prototype={createTracer:function(e,t){var r={},i=this,a="function"==typeof t;return(0,o.p)(v+"tracer",[(0,s.z)(),e,r],i,n.D.spa,g),function(){if(p.emit((a?"":"no-")+"fn-start",[(0,s.z)(),i,a],r),a)try{return t.apply(this,arguments)}catch(e){throw p.emit("fn-err",[arguments,this,"string"==typeof e?new Error(e):e],r),e}finally{p.emit("fn-end",[(0,s.z)()],r)}}}};function x(e,t,r,i){return function(){return(0,o.p)(l.xS,["API/"+t+"/called"],void 0,n.D.metrics,g),i&&(0,o.p)(e+t,[(0,s.z)(),...arguments],r?null:this,i,g),r?void 0:this}}function A(){r.e(439).then(r.bind(r,7438)).then((t=>{let{setAPI:r}=t;r(e),(0,c.L)(e,"api")})).catch((()=>(0,f.Z)("Downloading runtime APIs failed...")))}return["actionText","setName","setAttribute","save","ignore","onEnd","getContext","end","get"].forEach((e=>{w[e]=x(v,e,void 0,n.D.spa)})),h.noticeError=function(e,t){"string"==typeof e&&(e=new Error(e)),(0,o.p)(l.xS,["API/noticeError/called"],void 0,n.D.metrics,g),(0,o.p)("err",[e,(0,s.z)(),!1,t],void 0,n.D.jserrors,g)},d.il?(0,u.b)((()=>A()),!0):A(),h}(e,v);return(0,h.Qy)(e,T,"api"),(0,h.Qy)(e,A,"exposed"),(0,h.EZ)("activatedFeatures",p.T),T}},3325:(e,t,r)=>{r.d(t,{D:()=>n,p:()=>i});const n={ajax:"ajax",jserrors:"jserrors",metrics:"metrics",pageAction:"page_action",pageViewEvent:"page_view_event",pageViewTiming:"page_view_timing",sessionReplay:"session_replay",sessionTrace:"session_trace",spa:"spa"},i={[n.pageViewEvent]:1,[n.pageViewTiming]:2,[n.metrics]:3,[n.jserrors]:4,[n.ajax]:5,[n.sessionTrace]:6,[n.pageAction]:7,[n.spa]:8,[n.sessionReplay]:9}}},n={};function i(e){var t=n[e];if(void 0!==t)return t.exports;var o=n[e]={exports:{}};return r[e](o,o.exports,i),o.exports}i.m=r,i.d=(e,t)=>{for(var r in t)i.o(t,r)&&!i.o(e,r)&&Object.defineProperty(e,r,{enumerable:!0,get:t[r]})},i.f={},i.e=e=>Promise.all(Object.keys(i.f).reduce(((t,r)=>(i.f[r](e,t),t)),[])),i.u=e=>(({78:"page_action-aggregate",147:"metrics-aggregate",242:"session-manager",317:"jserrors-aggregate",348:"page_view_timing-aggregate",412:"lazy-feature-loader",439:"async-api",538:"recorder",590:"session_replay-aggregate",675:"compressor",733:"session_trace-aggregate",786:"page_view_event-aggregate",873:"spa-aggregate",898:"ajax-aggregate"}[e]||e)+"."+{78:"ac76d497",147:"3dc53903",148:"1a20d5fe",242:"2a64278a",317:"49e41428",348:"bd6de33a",412:"2f55ce66",439:"30bd804e",538:"1b18459f",590:"cf0efb30",675:"ae9f91a8",733:"83105561",786:"06482edd",860:"03a8b7a5",873:"e6b09d52",898:"998ef92b"}[e]+"-1.236.0.min.js"),i.o=(e,t)=>Object.prototype.hasOwnProperty.call(e,t),e={},t="NRBA:",i.l=(r,n,o,a)=>{if(e[r])e[r].push(n);else{var s,c;if(void 0!==o)for(var u=document.getElementsByTagName("script"),d=0;d {s.onerror=s.onload=null,clearTimeout(h);var i=e[r];if(delete e[r],s.parentNode&&s.parentNode.removeChild(s),i&&i.forEach((e=>e(n))),t)return t(n)},h=setTimeout(l.bind(null,void 0,{type:"timeout",target:s}),12e4);s.onerror=l.bind(null,s.onerror),s.onload=l.bind(null,s.onload),c&&document.head.appendChild(s)}},i.r=e=>{"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(e,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(e,"__esModule",{value:!0})},i.j=364,i.p="https://js-agent.newrelic.com/",(()=>{var e={364:0,953:0};i.f.j=(t,r)=>{var n=i.o(e,t)?e[t]:void 0;if(0!==n)if(n)r.push(n[2]);else{var o=new Promise(((r,i)=>n=e[t]=[r,i]));r.push(n[2]=o);var a=i.p+i.u(t),s=new Error;i.l(a,(r=>{if(i.o(e,t)&&(0!==(n=e[t])&&(e[t]=void 0),n)){var o=r&&("load"===r.type?"missing":r.type),a=r&&r.target&&r.target.src;s.message="Loading chunk "+t+" failed.\n("+o+": "+a+")",s.name="ChunkLoadError",s.type=o,s.request=a,n[1](s)}}),"chunk-"+t,t)}};var t=(t,r)=>{var n,o,[a,s,c]=r,u=0;if(a.some((t=>0!==e[t]))){for(n in s)i.o(s,n)&&(i.m[n]=s[n]);if(c)c(i)}for(t&&t(r);u {i.r(o);var e=i(3325),t=i(5763);const r=Object.values(e.D);function n(e){const n={};return r.forEach((r=>{n[r]=function(e,r){return!1!==(0,t.Mt)(r,"".concat(e,".enabled"))}(r,e)})),n}var a=i(9144);var s=i(5546),c=i(385),u=i(8e3),d=i(5938),f=i(3960),l=i(50);class h extends d.W{constructor(e,t,r){let n=!(arguments.length>3&&void 0!==arguments[3])||arguments[3];super(e,t,r),this.auto=n,this.abortHandler,this.featAggregate,this.onAggregateImported,n&&(0,u.R)(e,r)}importAggregator(){let e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{};if(this.featAggregate||!this.auto)return;const r=c.il&&!0===(0,t.Mt)(this.agentIdentifier,"privacy.cookies_enabled");let n;this.onAggregateImported=new Promise((e=>{n=e}));const o=async()=>{let t;try{if(r){const{setupAgentSession:e}=await Promise.all([i.e(860),i.e(242)]).then(i.bind(i,3228));t=e(this.agentIdentifier)}}catch(e){(0,l.Z)("A problem occurred when starting up session manager. This page will not start or extend any session.",e)}try{if(!this.shouldImportAgg(this.featureName,t))return void(0,u.L)(this.agentIdentifier,this.featureName);const{lazyFeatureLoader:r}=await i.e(412).then(i.bind(i,8582)),{Aggregate:o}=await r(this.featureName,"aggregate");this.featAggregate=new o(this.agentIdentifier,this.aggregator,e),n(!0)}catch(e){(0,l.Z)("Downloading and initializing ".concat(this.featureName," failed..."),e),this.abortHandler?.(),n(!1)}};c.il?(0,f.b)((()=>o()),!0):o()}shouldImportAgg(r,n){return r!==e.D.sessionReplay||!1!==(0,t.Mt)(this.agentIdentifier,"session_trace.enabled")&&(!!n?.isNew||!!n?.state.sessionReplay)}}var g=i(7633),p=i(7894);class m extends h{static featureName=g.t9;constructor(r,n){let i=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];if(super(r,n,g.t9,i),("undefined"==typeof PerformanceNavigationTiming||c.Tt)&&"undefined"!=typeof PerformanceTiming){const n=(0,t.OP)(r);n[g.Dz]=Math.max(Date.now()-n.offset,0),(0,f.K)((()=>n[g.qw]=Math.max((0,p.z)()-n[g.Dz],0))),(0,f.b)((()=>{const t=(0,p.z)();n[g.OJ]=Math.max(t-n[g.Dz],0),(0,s.p)("timing",["load",t],void 0,e.D.pageViewTiming,this.ee)}))}this.importAggregator()}}var v=i(1117),b=i(1284);class y extends v.w{constructor(e){super(e),this.aggregatedData={}}store(e,t,r,n,i){var o=this.getBucket(e,t,r,i);return o.metrics=function(e,t){t||(t={count:0});return t.count+=1,(0,b.D)(e,(function(e,r){t[e]=w(r,t[e])})),t}(n,o.metrics),o}merge(e,t,r,n,i){var o=this.getBucket(e,t,n,i);if(o.metrics){var a=o.metrics;a.count+=r.count,(0,b.D)(r,(function(e,t){if("count"!==e){var n=a[e],i=r[e];i&&!i.c?a[e]=w(i.t,n):a[e]=function(e,t){if(!t)return e;t.c||(t=x(t.t));return t.min=Math.min(e.min,t.min),t.max=Math.max(e.max,t.max),t.t+=e.t,t.sos+=e.sos,t.c+=e.c,t}(i,a[e])}}))}else o.metrics=r}storeMetric(e,t,r,n){var i=this.getBucket(e,t,r);return i.stats=w(n,i.stats),i}getBucket(e,t,r,n){this.aggregatedData[e]||(this.aggregatedData[e]={});var i=this.aggregatedData[e][t];return i||(i=this.aggregatedData[e][t]={params:r||{}},n&&(i.custom=n)),i}get(e,t){return t?this.aggregatedData[e]&&this.aggregatedData[e][t]:this.aggregatedData[e]}take(e){for(var t={},r="",n=!1,i=0;i t.max&&(t.max=e),e 2&&void 0!==arguments[2])||arguments[2];super(e,r,j.t,n),c.il&&((0,t.OP)(e).initHidden=Boolean("hidden"===document.visibilityState),(0,N.N)((()=>(0,s.p)("docHidden",[(0,p.z)()],void 0,j.t,this.ee)),!0),(0,O.bP)("pagehide",(()=>(0,s.p)("winPagehide",[(0,p.z)()],void 0,j.t,this.ee))),this.importAggregator())}}var P=i(3081);class C extends h{static featureName=P.t9;constructor(e,t){let r=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];super(e,t,P.t9,r),this.importAggregator()}}var R,I=i(2210),k=i(1214),H=i(2177),L={};try{R=localStorage.getItem("__nr_flags").split(","),console&&"function"==typeof console.log&&(L.console=!0,-1!==R.indexOf("dev")&&(L.dev=!0),-1!==R.indexOf("nr_dev")&&(L.nrDev=!0))}catch(e){}function z(e){try{L.console&&z(e)}catch(e){}}L.nrDev&&H.ee.on("internal-error",(function(e){z(e.stack)})),L.dev&&H.ee.on("fn-err",(function(e,t,r){z(r.stack)})),L.dev&&(z("NR AGENT IN DEVELOPMENT MODE"),z("flags: "+(0,b.D)(L,(function(e,t){return e})).join(", ")));var M=i(6660);class B extends h{static featureName=M.t;constructor(r,n){let i=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];super(r,n,M.t,i),this.skipNext=0;try{this.removeOnAbort=new AbortController}catch(e){}const o=this;o.ee.on("fn-start",(function(e,t,r){o.abortHandler&&(o.skipNext+=1)})),o.ee.on("fn-err",(function(t,r,n){o.abortHandler&&!n[M.A]&&((0,I.X)(n,M.A,(function(){return!0})),this.thrown=!0,(0,s.p)("err",[n,(0,p.z)()],void 0,e.D.jserrors,o.ee))})),o.ee.on("fn-end",(function(){o.abortHandler&&!this.thrown&&o.skipNext>0&&(o.skipNext-=1)})),o.ee.on("internal-error",(function(t){(0,s.p)("ierr",[t,(0,p.z)(),!0],void 0,e.D.jserrors,o.ee)})),this.origOnerror=c._A.onerror,c._A.onerror=this.onerrorHandler.bind(this),c._A.addEventListener("unhandledrejection",(t=>{const r=function(e){let t="Unhandled Promise Rejection: ";if(e instanceof Error)try{return e.message=t+e.message,e}catch(t){return e}if(void 0===e)return new Error(t);try{return new Error(t+(0,D.P)(e))}catch(e){return new Error(t)}}(t.reason);(0,s.p)("err",[r,(0,p.z)(),!1,{unhandledPromiseRejection:1}],void 0,e.D.jserrors,this.ee)}),(0,O.m$)(!1,this.removeOnAbort?.signal)),(0,k.gy)(this.ee),(0,k.BV)(this.ee),(0,k.em)(this.ee),(0,t.OP)(r).xhrWrappable&&(0,k.Kf)(this.ee),this.abortHandler=this.#e,this.importAggregator()}#e(){this.removeOnAbort?.abort(),this.abortHandler=void 0}onerrorHandler(t,r,n,i,o){"function"==typeof this.origOnerror&&this.origOnerror(...arguments);try{this.skipNext?this.skipNext-=1:(0,s.p)("err",[o||new F(t,r,n),(0,p.z)()],void 0,e.D.jserrors,this.ee)}catch(t){try{(0,s.p)("ierr",[t,(0,p.z)(),!0],void 0,e.D.jserrors,this.ee)}catch(e){}}return!1}}function F(e,t,r){this.message=e||"Uncaught error with no additional information",this.sourceURL=t,this.line=r}let U=1;const q="nr@id";function G(e){const t=typeof e;return!e||"object"!==t&&"function"!==t?-1:e===c._A?0:(0,I.X)(e,q,(function(){return U++}))}function V(e){if("string"==typeof e&&e.length)return e.length;if("object"==typeof e){if("undefined"!=typeof ArrayBuffer&&e instanceof ArrayBuffer&&e.byteLength)return e.byteLength;if("undefined"!=typeof Blob&&e instanceof Blob&&e.size)return e.size;if(!("undefined"!=typeof FormData&&e instanceof FormData))try{return(0,D.P)(e).length}catch(e){return}}}var X=i(7243);class W{constructor(e){this.agentIdentifier=e,this.generateTracePayload=this.generateTracePayload.bind(this),this.shouldGenerateTrace=this.shouldGenerateTrace.bind(this)}generateTracePayload(e){if(!this.shouldGenerateTrace(e))return null;var r=(0,t.DL)(this.agentIdentifier);if(!r)return null;var n=(r.accountID||"").toString()||null,i=(r.agentID||"").toString()||null,o=(r.trustKey||"").toString()||null;if(!n||!i)return null;var a=(0,_.M)(),s=(0,_.Ht)(),c=Date.now(),u={spanId:a,traceId:s,timestamp:c};return(e.sameOrigin||this.isAllowedOrigin(e)&&this.useTraceContextHeadersForCors())&&(u.traceContextParentHeader=this.generateTraceContextParentHeader(a,s),u.traceContextStateHeader=this.generateTraceContextStateHeader(a,c,n,i,o)),(e.sameOrigin&&!this.excludeNewrelicHeader()||!e.sameOrigin&&this.isAllowedOrigin(e)&&this.useNewrelicHeaderForCors())&&(u.newrelicHeader=this.generateTraceHeader(a,s,c,n,i,o)),u}generateTraceContextParentHeader(e,t){return"00-"+t+"-"+e+"-01"}generateTraceContextStateHeader(e,t,r,n,i){return i+"@nr=0-1-"+r+"-"+n+"-"+e+"----"+t}generateTraceHeader(e,t,r,n,i,o){if(!("function"==typeof c._A?.btoa))return null;var a={v:[0,1],d:{ty:"Browser",ac:n,ap:i,id:e,tr:t,ti:r}};return o&&n!==o&&(a.d.tk=o),btoa((0,D.P)(a))}shouldGenerateTrace(e){return this.isDtEnabled()&&this.isAllowedOrigin(e)}isAllowedOrigin(e){var r=!1,n={};if((0,t.Mt)(this.agentIdentifier,"distributed_tracing")&&(n=(0,t.P_)(this.agentIdentifier).distributed_tracing),e.sameOrigin)r=!0;else if(n.allowed_origins instanceof Array)for(var i=0;i 2&&void 0!==arguments[2])||arguments[2];super(r,n,Z.t,i),(0,t.OP)(r).xhrWrappable&&(this.dt=new W(r),this.handler=(e,t,r,n)=>(0,s.p)(e,t,r,n,this.ee),(0,k.u5)(this.ee),(0,k.Kf)(this.ee),function(r,n,i,o){function a(e){var t=this;t.totalCbs=0,t.called=0,t.cbTime=0,t.end=E,t.ended=!1,t.xhrGuids={},t.lastSize=null,t.loadCaptureCalled=!1,t.params=this.params||{},t.metrics=this.metrics||{},e.addEventListener("load",(function(r){_(t,e)}),(0,O.m$)(!1)),c.IF||e.addEventListener("progress",(function(e){t.lastSize=e.loaded}),(0,O.m$)(!1))}function s(e){this.params={method:e[0]},T(this,e[1]),this.metrics={}}function u(e,n){var i=(0,t.DL)(r);i.xpid&&this.sameOrigin&&n.setRequestHeader("X-NewRelic-ID",i.xpid);var a=o.generateTracePayload(this.parsedOrigin);if(a){var s=!1;a.newrelicHeader&&(n.setRequestHeader("newrelic",a.newrelicHeader),s=!0),a.traceContextParentHeader&&(n.setRequestHeader("traceparent",a.traceContextParentHeader),a.traceContextStateHeader&&n.setRequestHeader("tracestate",a.traceContextStateHeader),s=!0),s&&(this.dt=a)}}function d(e,t){var r=this.metrics,i=e[0],o=this;if(r&&i){var a=V(i);a&&(r.txSize=a)}this.startTime=(0,p.z)(),this.listener=function(e){try{"abort"!==e.type||o.loadCaptureCalled||(o.params.aborted=!0),("load"!==e.type||o.called===o.totalCbs&&(o.onloadCalled||"function"!=typeof t.onload)&&"function"==typeof o.end)&&o.end(t)}catch(e){try{n.emit("internal-error",[e])}catch(e){}}};for(var s=0;s 1?e[1]=i:e.push(i)}else e[0]&&e[0].headers&&s(e[0].headers,n)&&(this.dt=n);function s(e,t){var r=!1;return t.newrelicHeader&&(e.set("newrelic",t.newrelicHeader),r=!0),t.traceContextParentHeader&&(e.set("traceparent",t.traceContextParentHeader),t.traceContextStateHeader&&e.set("tracestate",t.traceContextStateHeader),r=!0),r}}function x(e,t){this.params={},this.metrics={},this.startTime=(0,p.z)(),this.dt=t,e.length>=1&&(this.target=e[0]),e.length>=2&&(this.opts=e[1]);var r,n=this.opts||{},i=this.target;"string"==typeof i?r=i:"object"==typeof i&&i instanceof Y?r=i.url:c._A?.URL&&"object"==typeof i&&i instanceof URL&&(r=i.href),T(this,r);var o=(""+(i&&i instanceof Y&&i.method||n.method||"GET")).toUpperCase();this.params.method=o,this.txSize=V(n.body)||0}function A(t,r){var n;this.endTime=(0,p.z)(),this.params||(this.params={}),this.params.status=r?r.status:0,"string"==typeof this.rxSize&&this.rxSize.length>0&&(n=+this.rxSize);var o={txSize:this.txSize,rxSize:n,duration:(0,p.z)()-this.startTime};i("xhr",[this.params,o,this.startTime,this.endTime,"fetch"],this,e.D.ajax)}function E(t){var r=this.params,n=this.metrics;if(!this.ended){this.ended=!0;for(var o=0;o 2&&void 0!==arguments[2])||arguments[2];super(e,t,we.t,r),this.importAggregator()}}new class{constructor(e){let t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:(0,_.ky)(16);c._A?(this.agentIdentifier=t,this.sharedAggregator=new y({agentIdentifier:this.agentIdentifier}),this.features={},this.desiredFeatures=new Set(e.features||[]),this.desiredFeatures.add(m),Object.assign(this,(0,a.j)(this.agentIdentifier,e,e.loaderType||"agent")),this.start()):(0,l.Z)("Failed to initial the agent. Could not determine the runtime environment.")}get config(){return{info:(0,t.C5)(this.agentIdentifier),init:(0,t.P_)(this.agentIdentifier),loader_config:(0,t.DL)(this.agentIdentifier),runtime:(0,t.OP)(this.agentIdentifier)}}start(){const t="features";try{const r=n(this.agentIdentifier),i=[...this.desiredFeatures];i.sort(((t,r)=>e.p[t.featureName]-e.p[r.featureName])),i.forEach((t=>{if(r[t.featureName]||t.featureName===e.D.pageViewEvent){const n=function(t){switch(t){case e.D.ajax:return[e.D.jserrors];case e.D.sessionTrace:return[e.D.ajax,e.D.pageViewEvent];case e.D.sessionReplay:return[e.D.sessionTrace];case e.D.pageViewTiming:return[e.D.pageViewEvent];default:return[]}}(t.featureName);n.every((e=>r[e]))||(0,l.Z)("".concat(t.featureName," is enabled but one or more dependent features has been disabled (").concat((0,D.P)(n),"). This may cause unintended consequences or missing data...")),this.features[t.featureName]=new t(this.agentIdentifier,this.sharedAggregator)}})),(0,T.Qy)(this.agentIdentifier,this.features,t)}catch(e){(0,l.Z)("Failed to initialize all enabled instrument classes (agent aborted) -",e);for(const e in this.features)this.features[e].abortHandler?.();const r=(0,T.fP)();return delete r.initializedAgents[this.agentIdentifier]?.api,delete r.initializedAgents[this.agentIdentifier]?.[t],delete this.sharedAggregator,r.ee?.abort(),delete r.ee?.get(this.agentIdentifier),!1}}}({features:[J,m,S,class extends h{static featureName=oe;constructor(t,r){if(super(t,r,oe,!(arguments.length>2&&void 0!==arguments[2])||arguments[2]),!c.il)return;const n=this.ee;let i;(0,k.QU)(n),this.eventsEE=(0,k.em)(n),this.eventsEE.on(se,(function(e,t){this.bstStart=(0,p.z)()})),this.eventsEE.on(ae,(function(t,r){(0,s.p)("bst",[t[0],r,this.bstStart,(0,p.z)()],void 0,e.D.sessionTrace,n)})),n.on(ce+ne,(function(e){this.time=(0,p.z)(),this.startPath=location.pathname+location.hash})),n.on(ce+ie,(function(t){(0,s.p)("bstHist",[location.pathname+location.hash,this.startPath,this.time],void 0,e.D.sessionTrace,n)}));try{i=new PerformanceObserver((t=>{const r=t.getEntries();(0,s.p)(te,[r],void 0,e.D.sessionTrace,n)})),i.observe({type:re,buffered:!0})}catch(e){}this.importAggregator({resourceObserver:i})}},C,xe,B,class extends h{static featureName=de;constructor(e,r){if(super(e,r,de,!(arguments.length>2&&void 0!==arguments[2])||arguments[2]),!c.il)return;if(!(0,t.OP)(e).xhrWrappable)return;try{this.removeOnAbort=new AbortController}catch(e){}let n,i=0;const o=this.ee.get("tracer"),a=(0,k._L)(this.ee),s=(0,k.Lg)(this.ee),u=(0,k.BV)(this.ee),d=(0,k.Kf)(this.ee),f=this.ee.get("events"),l=(0,k.u5)(this.ee),h=(0,k.QU)(this.ee),g=(0,k.Gm)(this.ee);function m(e,t){h.emit("newURL",[""+window.location,t])}function v(){i++,n=window.location.hash,this[ve]=(0,p.z)()}function b(){i--,window.location.hash!==n&&m(0,!0);var e=(0,p.z)();this[pe]=~~this[pe]+e-this[ve],this[ye]=e}function y(e,t){e.on(t,(function(){this[t]=(0,p.z)()}))}this.ee.on(ve,v),s.on(be,v),a.on(be,v),this.ee.on(ye,b),s.on(ge,b),a.on(ge,b),this.ee.buffer([ve,ye,"xhr-resolved"],this.featureName),f.buffer([ve],this.featureName),u.buffer(["setTimeout"+le,"clearTimeout"+fe,ve],this.featureName),d.buffer([ve,"new-xhr","send-xhr"+fe],this.featureName),l.buffer([me+fe,me+"-done",me+he+fe,me+he+le],this.featureName),h.buffer(["newURL"],this.featureName),g.buffer([ve],this.featureName),s.buffer(["propagate",be,ge,"executor-err","resolve"+fe],this.featureName),o.buffer([ve,"no-"+ve],this.featureName),a.buffer(["new-jsonp","cb-start","jsonp-error","jsonp-end"],this.featureName),y(l,me+fe),y(l,me+"-done"),y(a,"new-jsonp"),y(a,"jsonp-end"),y(a,"cb-start"),h.on("pushState-end",m),h.on("replaceState-end",m),window.addEventListener("hashchange",m,(0,O.m$)(!0,this.removeOnAbort?.signal)),window.addEventListener("load",m,(0,O.m$)(!0,this.removeOnAbort?.signal)),window.addEventListener("popstate",(function(){m(0,i>1)}),(0,O.m$)(!0,this.removeOnAbort?.signal)),this.abortHandler=this.#e,this.importAggregator()}#e(){this.removeOnAbort?.abort(),this.abortHandler=void 0}}],loaderType:"spa"})})(),window.NRBA=o})(); window.jQuery || document.write(' ') CKEDITOR_BASEPATH='https://f1000research.com/js/vendor/ckeditor/' window.reactTheme = 'research'; window.MathJax = { CommonHTML: { linebreaks: { automatic: true } }, 'HTML-CSS': { linebreaks: { automatic: true } }, SVG: { linebreaks: { automatic: true } }, AuthorInit: function() { MathJax.Hub.Register.MessageHook('End Process', function () { let timeout = false; // holder for timeout id const delay = 250; // delay after event is "complete" to run callback const reflowMath = function() { const dispFormulas = document.querySelectorAll('.disp-formula.panel'); if (!dispFormulas) { return; } for (const dispFormula of dispFormulas) { const child = dispFormula.querySelector('.MathJax_Preview').nextSibling.firstChild; const isMultiline = MathJax.Hub.getAllJax(dispFormula)[0].root.isMultiline; if (dispFormula.offsetWidth < child.offsetWidth || isMultiline) { MathJax.Hub.Queue(['Rerender', MathJax.Hub, dispFormula]); } } }; window.addEventListener('resize', function() { clearTimeout(timeout); // clear the timeout timeout = setTimeout(reflowMath, delay); // start timing for event "completion" }); }); }, }; if (window.location.hash == '#_=_'){ window.location = window.location.href.split('#')[0] } !function(f,b,e,v,n,t,s){if(f.fbq)return;n=f.fbq=function() {n.callMethod? n.callMethod.apply(n,arguments):n.queue.push(arguments)} ;if(!f._fbq)f._fbq=n; n.push=n;n.loaded=!0;n.version='2.0';n.queue=[];t=b.createElement(e);t.async=!0; t.src=v;s=b.getElementsByTagName(e)[0];s.parentNode.insertBefore(t,s)}(window, document,'script','https://connect.facebook.net/en_US/fbevents.js'); fbq('init', '1641728616063202'); fbq('track', "PixelInitialized", {}); (function(h,o,t,j,a,r){ h.hj=h.hj||function(){(h.hj.q=h.hj.q||[]).push(arguments)}; h._hjSettings={hjid:2318163,hjsv:6}; a=o.getElementsByTagName('head')[0]; r=o.createElement('script');r.async=1; r.src=t+h._hjSettings.hjid+j+h._hjSettings.hjsv; a.appendChild(r); })(window,document,'https://static.hotjar.com/c/hotjar-','.js?sv='); search file_upload Submit your research search menu close search Browse Gateways & Collections How to Publish Submit your Research My Submissions Article Guidelines Article Guidelines (New Versions) Open Data, Software and Code Guidelines Open Data and Accessible Source Materials Guidelines (HSS) Open Data, Software and Code Guidelines (PSE) Prepublication Checks Production Process Posters and Slides Guidelines Document Guidelines Article Processing Charges Peer Review Finding Article Reviewers About How it Works For Reviewers Our Advisors Policies Glossary FAQs For Developers Newsroom Contact My Research Submissions Content and Tracking Alerts My Details Sign In file_upload Submit your research { "@context": "https://schema.org", "@type": "ScholarlyArticle", "mainEntityOfPage": { "@type": "WebPage", "@id": "https://f1000research.com/articles/14-624" }, "headline": "Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process", "datePublished": "2025-06-25T15:31:49", "dateModified": "2025-11-04T17:01:19", "author": [ { "@type": "Person", "name": "Foziah Gazzawe" }, { "@type": "Person", "name": "Marwan Albahar" } ], "publisher": { "@type": "Organization", "name": "F1000Research", "logo": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 480, "width": 60 } }, "image": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 1200, "width": 150 }, "description": " Background The farming industry faces continuous threats from pest control and farm security issues because rodents cause significant damage to crops and disrupt farm operations. Traditional pest control methods require continuous human interaction which proves both resource-intensive and inefficient. Modern agricultural practices benefit from sustainable solutions through the combination of renewable energy with smart technologies. Method The research presents an innovative solar-powered motion-sensor system that utilizes OpenCV-based image analysis to detect and classify rodent intruders on farmland autonomously. The system depends on solar panels for energy autonomy while employing computer vision to monitor threats in real time and classify them. Results The system demonstrates its ability to detect and prevent rodent intruders according to initial testing results. The OpenCV system uses motion sensor signals to analyze movement patterns before distinguishing rodents from other detected objects. The solar-powered system operates continuously which decreases human intervention needs and enhances farm surveillance capabilities. The model demonstrates its capability to defend crops from rodent damage and enhance farm resistance against land degradation threats. Conclusion The proposed system demonstrates progress in uniting renewable energy systems with smart surveillance technologies to mitigate agricultural risks. The current system encounters problems with detecting wild animals beyond rodents as well as tracking rodent activity beneath ground level. Future developments could include improved pest capture systems alongside enhanced surveillance features for detecting both unauthorized human intruders and large animals. The research shows that solar power systems need to be connected with automated monitoring technology to create sustainable agricultural operations that are efficient and resilient. " } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/14-624/v1", "name": "Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance:..." } } ] } Home Browse Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance:... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Gazzawe F and Albahar M. Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process [version 1; peer review: 1 approved with reservations] . F1000Research 2025, 14 :624 ( https://doi.org/10.12688/f1000research.164633.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process [version 1; peer review: 1 approved with reservations] Foziah Gazzawe https://orcid.org/0000-0003-1200-9849 1 , Marwan Albahar 2 Foziah Gazzawe https://orcid.org/0000-0003-1200-9849 1 , Marwan Albahar 2 PUBLISHED 25 Jun 2025 Author details Author details 1 computer science, Umm Al-Qura University, Mecca, Makkah Province, Saudi Arabia 2 Department of Computing, College of Engineering and Computing in Al-Lith, Umm Al-Qura University, Mecca, Makkah Province, Saudi Arabia Foziah Gazzawe Roles: Conceptualization, Formal Analysis, Methodology, Project Administration, Resources, Visualization, Writing – Review & Editing Marwan Albahar Roles: Conceptualization, Funding Acquisition, Project Administration, Resources, Supervision, Writing – Review & Editing OPEN PEER REVIEW DETAILS REVIEWER STATUS This article is included in the Agriculture, Food and Nutrition gateway. Abstract Background The farming industry faces continuous threats from pest control and farm security issues because rodents cause significant damage to crops and disrupt farm operations. Traditional pest control methods require continuous human interaction which proves both resource-intensive and inefficient. Modern agricultural practices benefit from sustainable solutions through the combination of renewable energy with smart technologies. Method The research presents an innovative solar-powered motion-sensor system that utilizes OpenCV-based image analysis to detect and classify rodent intruders on farmland autonomously. The system depends on solar panels for energy autonomy while employing computer vision to monitor threats in real time and classify them. Results The system demonstrates its ability to detect and prevent rodent intruders according to initial testing results. The OpenCV system uses motion sensor signals to analyze movement patterns before distinguishing rodents from other detected objects. The solar-powered system operates continuously which decreases human intervention needs and enhances farm surveillance capabilities. The model demonstrates its capability to defend crops from rodent damage and enhance farm resistance against land degradation threats. Conclusion The proposed system demonstrates progress in uniting renewable energy systems with smart surveillance technologies to mitigate agricultural risks. The current system encounters problems with detecting wild animals beyond rodents as well as tracking rodent activity beneath ground level. Future developments could include improved pest capture systems alongside enhanced surveillance features for detecting both unauthorized human intruders and large animals. The research shows that solar power systems need to be connected with automated monitoring technology to create sustainable agricultural operations that are efficient and resilient. READ ALL READ LESS Keywords Solar-powered farm monitoring, rodent detection, automated surveillance, image recognition, sustainable agriculture Corresponding Author(s) Foziah Gazzawe ( [email protected] ) Close Corresponding author: Foziah Gazzawe Competing interests: No competing interests were disclosed. Grant information: This research work was funded by Umm Al-Qura University, Saudi Arabia, under grant number: 25UQU4400257GSSR05. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2025 Gazzawe F and Albahar M. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Gazzawe F and Albahar M. Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process [version 1; peer review: 1 approved with reservations] . F1000Research 2025, 14 :624 ( https://doi.org/10.12688/f1000research.164633.1 ) First published: 25 Jun 2025, 14 :624 ( https://doi.org/10.12688/f1000research.164633.1 ) Latest published: 04 Nov 2025, 14 :624 ( https://doi.org/10.12688/f1000research.164633.3 )  There is a newer version of this article available. Suppress this message for one day. 1. Introduction Motion sensors are devices used to detect objects that have moved within a given area. These sensors act as though they are self-activated, giving an alarm or engaging in their pre-programmed activity upon the detection of motion. In the agricultural domain, planning the process of motion monitoring constitutes one of the most important steps toward protecting the farming business as well as increasing its efficiency. Today, farm monitoring and surveillance still involve manual driving around the farm or the installation of security cameras at vantage points within the farm. However, these systems come with pitfalls, such as the inability to generate comprehensive lists, having low rates of penetration, and requiring frequent manual monitoring. Also, they effectively depend on conventional energy sources, which can be expensive and practically destructive to the natural environment. Emmanuel et al. (2018) established that by using a wireless sensor network differently from the usual method of erecting fences with sticks and ropes, farms could be monitored and controlled more effectively and sustainably. In addition to triggering the lighting, a wireless sensor network can also activate an alarm and send an SMS or an app notification to the farmer to take necessary action. Sensors also send an SMS or an app notification to the farmer to take necessary action ( Emmanuel et al., 2018 ). 1.1 Research gap The current solution for using motion sensor technologies and implementing them in farm monitoring systems is also not without several drawbacks that hamper their efficacy, especially for the large-scale and remote environments of the farming sector. Almost all the conventional motion sensors and CCTV cameras are specially designed to detect human movement or larger animal intrusions but are not efficient at detecting smaller vertebrate pests like rodents that are well known to cause massive losses through crop and stored produce raiding. This consequently results in huge losses since rodent infestations are normally undetected until extensive damage has been done. Moreover, the current surveillance systems require a constant supply of electrical power, which is not available in most of the rural and developed central region areas. Another problem in current motion sensor systems is that they are not real-time responsive, or at least not fully automated. Most typical systems employ the human operator to watch monitors for the footage or to respond to alerts, which raises a great deal of labor costs and hampers the efficiency of farm surveillance. All these systems are post-incident systems, which implies that these systems work following an incident, not to prevent it. Also, the utilization of these energy resources is costly and raises the environmental costs of operation, thereby making these systems unsustainable in their current utilization. Hence, the research question lies in finding a solution that would not only enhance the detection accuracy of relatively small targets like rodents but also employ sustainable forms of power in the process. The resulting gaps can be filled by the proposed solar-powered motion sensor system, which is capable of using renewable energy, up-to-date sensors, automation, and systems to monitor both large and small intrusions more effectively in terms of energy consumption. 1.2 Research aim and objectives The primary objective of this proposed study is to develop a solar-powered motion sensor system capable of recognizing rodent invasion on farms within the monitored area, thereby enhancing efficient monitoring and surveillance efforts while consuming energy efficiently. 1.3 Research question The proposed study is guided by the following research question: How can a solar-powered motion sensor system utilizing computer vision and deep learning techniques be developed and implemented to accurately detect and recognize animals on farms to enhance efficient farm monitoring and surveillance? 1.4 Research novelty This study proposes a new concept of farm monitoring and surveillance through the use of solar-powered motion sensors coupled with computer vision and deep learning algorithms for rodent invasion detection. Compared to conventional farm surveillance systems, which are primarily meant to monitor human interference or large animal movement and require continuous electrical power, this proposed system is intended to be energy-autonomous and is to be powered through solar energy. This not only provides for the need to power such devices in areas where there is no physical access to an energy grid but also provides a positive impact on worldwide sustainability as the need for fossil fuels lessens. Furthermore, through the integrated feature of computer vision technology, it also has the possibility to differentiate between varying cycles of motion, for instance, to differentiate the wind-blown leaves with rodent movements. The use of deep learning in the algorithms helps the system to update the information that is collected, enhancing detection results in the future. This adaptive capability greatly improves the chances of the system to detect the smaller pests that are ignored in most traditional systems. Further, notification through a mobile application that reflects the actual situation in the field enables farmers to act instantly and avoid further harm that may require manual intervention. This study’s uniqueness is found in the integration of renewable energy sources, advanced detection systems, and automation in the monitoring of farms. This approach has the possibility of radically changing the practice of monitoring farms, providing one distinctive tool for the farmers, especially those who are located in areas where they have no access to the normal electrical power source. 2. Literature review 2.1 Monitoring systems for farms utilizing sensors The use of sensors has been vastly studied for the protection of agricultural farms and for detecting possible intruders as soon as possible. Mrunal Khedkar (2021) proposed a system that employs wireless sensor nodes in conjunction with passive infrared (PIR) sensors and low-power digital cameras that can detect motion and take pictures of intruders. The PIR sensors, universal in motion detection, are sensitive to variations in infrared emissions that warm objects produce. On detection, a low-power camera, including the OpenMV Cam, is actuated to take pictures or record the video. These visual data are transmitted wirelessly through protocols that include ZigBee or Bluetooth, whereby long-range protocols, such as the ZigBee, are appropriate for large areas of the farm, and short-range protocols, such as the Bluetooth. The base station collects the images and analyses them to capture the intruder; the quality of images is measured using peak signal-to-noise ratio (PSNR) and mean squared error (MSE). Nevertheless, this system is a good example of PIR sensors and low-power cameras used in farm monitoring, though the whole system remains dependent on external power supplies. Its use is slightly effective in remote farm areas where power availability might be quite a challenge. Furthermore, using conventional battery-based devices for the wireless sensor nodes may not extend for long hours of performance without requiring frequent charging or replacement of batteries with fresh ones. Sowmika, Rohith Paul, and Malathi (2020) described an Internet of Things (IoT)-based rodent detection system using a PIR sensor for detecting the rodent. This system is triggered by sensing infrared radiation emitted from the body of the rats and sends an alert to a cloud-based platform. The PIR sensor for the rodent location works up to a 10-meter range, and the mode of operation can be live with instant alerts to the farmer via mobile applications. This system gives real-time detection and notification through wireless means, but it has a limited range and, more critically, it derives its power from conventional sources, thus a constraint in rural farming environments not connected to the grid. 2.2 The application of vision-based farm surveillance system Vision-based systems are now considered an essential part of today’s farm monitoring and surveillance because of their capacity to obtain and interpret visual information. A low-power bait station monitoring system for rodent detection has been designed by Ross et al. (2020) , and it is known as RatSpy. RatSpy employs a combination of sensors and cameras to detect rats’ movement and the uptake of baits without the need for inspection. The results are sent wirelessly to pest control operators, enabling those operators to monitor the status without physically checking it. Owing to technology, the labor expenses associated with monitoring the bait stations’ condition and the general rodent population have greatly decreased, and the best feature of this solution is that it always actively scans for rodents. Nevertheless, the system has consistently lower power consumption to accomplish its task, which realistically necessitates battery change, making it impractical for large-scale farming or areas where a simple battery replacement is not easily accessible. Lai et al. (2023) offered an ingenious approach using IoT nodes with Long Range (LoRa) modules to look after the farm. These nodes are fitted with PIR sensors and an ESP32 camera for picture capture in real time. The system provided with a terminal transmits the data on the rodent activity wirelessly and stores it at a cloud server to process and analyze. The flexibility offered by LoRa technology of transmitting information from one IoT node to another and to the cloud server is well applicable to large farms. However, there is the same problem known for other vision-based systems: energy consumption is high due to the continuous work of cameras and sensors that need a stable power supply. Implementation of the deep learning algorithms in these systems was likely to provide more precise detection of the mice, for instance, as an individual threat within the building. Nevertheless, the utilization of deep learning models entails higher computational requirements that may further exponentially drain the energy supply, requiring a more efficient power source. 2.3 Wireless sensor networks and low-power solutions Wireless sensor networks (WSNs) capable of operating at low power have been researched with the view to extending the battery lifetime of the farm monitoring systems and, as a result, minimizing the need for frequent battery replacement. In that recent work, Cambra et al. (2017) proposed another low-power WSN system that employs a multi-hop wireless mesh network design for detecting rodent pests in agricultural fields. The system comprises the network coordinator, parent nodes – routers, and child nodes – sensor nodes. The PIR motion sensors placed on the hardware of the sensor nodes detect the motion and relay the information received through the mesh network to the network coordinator. The data transmission is made utilizing nRF24L01+ 2.4 GHz RF Transceivers, which consume negligible power. Besides, the system utilizes a number of power management features, including power down, interrupt, and sleep, which all help to further prolong battery lifespan. Though this system provides up to 90% saving of energy use, it comes from the conventional battery power that needs to be recharged. However, the sensitivity level of PIR sensors is not very high; we need to go for the fine level of detecting small creatures like rats, etc. 2.4 Solar-powered monitoring systems Solar power has gained traction as an alternative energy source for farm surveillance systems, particularly in remote areas where access to the electrical grid is limited. Patel et al. (2021) explored a solar-powered IoT-based agricultural monitoring system that integrates solar panels to power wireless sensor networks and GSM communication devices. This approach significantly reduces reliance on conventional power sources and enhances the system’s feasibility in off-grid locations. The system monitors crop health, soil moisture, and environmental conditions using IoT sensors and transmits data wirelessly to the farmer’s mobile device. However, while this system addresses power-related challenges, it is not optimized for rodent detection or other farm surveillance needs, as its primary focus is on crop monitoring. Adirala et al. (2025) devised an IoT-based detection system using PIR motion sensors to detect intrusions from large animals, such as cattle. The system employs a two-level deterrent mechanism namely randomized carnivorous animal sounds and high-intensity focus lights, and wireless connectivity for remote monitoring. However, it is limited to detecting larger animals and is not sensitive enough for small pests like rodents. Thus, a more advanced detection mechanism is required to monitor a wider range of potential animal intruders. 3. Methods In order to understand the proposed architecture, a simulation of image recognition was carried out using the Google Teachable Machine platform to train and simulate the rodent recognition model. Data for training the model involved downloaded images of rodents. These images were grouped into five categories, namely: rat, mouse, squirrel, chipmunk and mole. The five categories formed the classes of the rodent recognition model. After feeding in the training samples, the model was trained using 15 samples per class. The model was trained using sample images of rodents belonging to the 5 classes, which were accordingly recognized and classified. 3.1 System infrastructure Figures 1 and 2 comprise the system infrastructure based on a motion sensor, flood light, motor, battery, speaker, rotating knob, a smart camera, and a solar panel. Figure 1. Front view of the system. Figure 2. Top (left) and back (right) view of the system. 3.2 System components 3.2.1 Motion sensor Image-based motion sensors analyze changes in the captured video to visually identify movement using cameras and computer vision algorithms ( Futagami et al., 2020 ). They are extremely accurate for this system because they use sophisticated algorithms for motion pattern detection and object tracking. 3.2.2 Data transmission protocol WI-FI data transmission protocols will enable data transfer between the system and the mobile application. WI-FI allows the transfer of data over a wide range ( Pahlavan and Krishnamurthy, 2020 ), hence the most convenient for this type of technology. When the system detects motion and the camera takes a video, and processes it, it will use WI-FI to notify the farmer of the intrusion. 3.2.3 Rotating knob The rotating knob serves as a mechanism to physically rotate the entire surveillance equipment, allowing the smart camera to capture images from all angles within the monitored area. It is connected to a motorized rotational mechanism, which rotates the entire surveillance equipment horizontally. Users can rotate the knob manually to adjust the viewing angle of the surveillance equipment. It is integrated with the battery to give power to the motorized rotational mechanism and motion detection sensors to enable it to pause temporarily when motion is detected, ensuring that the camera focuses on the detected movement to capture images or video footage. 3.2.4 Smart camera According to Kurniawan and Sofiarani (2020) , a smart camera combines complex image sensors and processors with the capability to process images on its own without assistance from humans. It records high-quality video footage of the areas under observation only once the motion is detected, enabling remote surveillance, evidence collection, and in-depth analysis of any activity that is detected. Smart cameras are equipped with high-resolution imaging sensors that enable them to record clear and detailed video footage. These sensors might use technologies like charge-coupled devices (CCD) or complementary metal-oxide semiconductors (CMOS), which provide better image quality even in low light. 3.2.5 Flood light Floodlight is the essential element that produces light illumination in low-light or nighttime conditions. It typically uses energy-efficient LED (Light-Emitting Diode) technology. LEDs deliver a high light output while using very little power energy, making them ideal for solar-powered systems where energy conservation is essential ( Pulli et al., 2015 ). The floodlight is connected to the solar-charged battery, enabling it to draw power from it and operate effectively at night. This component is particularly useful for farm surveillance, as it can deter potential intruders and help the smart camera identify any activity occurring after dark. 3.2.6 Battery The battery serves as the energy storage component in the system, ensuring a reliable and continuous power supply for the motion sensor, floodlight, and any other associated components. The preferred battery type for this system is lithium-ion batteries because they can be frequently charged and discharged without experiencing significant degradation and can be used for extended periods of time in solar-powered applications ( Manthiram, 2017 ). All linked components receive a smooth power supply from the battery as it is integrated into the overall system architecture. 3.2.7 Speaker The speaker serves as an audio output device within the surveillance system. Its main purpose is to mimic sound, which allows for alarming and alerting. According to Bernardini, Bianchi and Sarti (2023) , speakers utilize transducer technology to change electrical signals into sound waves, which are then released by speakers. When these transducers receive electrical signals, they vibrate, which causes sound waves to travel through the atmosphere. The motion sensor and speaker are combined so that when motion is detected, the motion sensor sends a signal to close the circuit linking the speakers. This causes the speakers to activate and emit sound alarms to frighten away any intruders, which includes either livestock or rodents. 4. Results & Discussion To solve the problem of animal recognition and categorization, we utilized OpenCV’s deep learning module (DNN). The process involves several key steps. 4.1 Image recognition process in OpenCV Preprocessing techniques are first used to simplify and lower noise in the image, as shown in Figure 3 . These techniques include first grayscale conversion and then Gaussian blurring. After that, thresholding is done to create a binary image that highlights the important objects. This binary image has contours that show the edges of distinct objects. Each contour’s area is computed, and contours having areas outside of a predetermined range are removed. For each remaining contour, bounding rectangles are generated in order to identify and pinpoint each particular object in the image ( Duwal and Tamang, 2024 ). Figure 3. Flowchart showing image processing steps. The following analytical results were obtained from the training and testing of the model. 4.2 Accuracy per class of rodents The accuracy per class of rodents is calculated (see Figure 4 ) using the test samples. The test samples include 15% of the samples that are not used in model training. Therefore, after the model has been trained, the model uses these samples to test performance on new data. Figure 4. Accuracy per class of rodents. 4.3 Confusion matrix Figure 5 shows the confusion matrix between classes of the model. This summarizes the accuracy of the model in determining confusion between samples in a class and that of another class. The class of the samples is shown on the y-axis, whereas the x-axis (prediction) shows the class to which the model classifies the samples to belong after learning. For instance, from the above results, it can be shown that after learning from the data, the model misclassified one instance of the rat class as a mouse. This means that the two classes share characteristics, and that particular rat sample was more similar to that of the mouse. Figure 5. Confusion matrix. 4.4 Accuracy per Epoch Figure 6 shows the accuracy calculated per epoch. Accuracy refers to the percentage of classifications accurately spotted by the model during training. Figure 6. Accuracy per Epoch. 4.5 Loss per Epoch Based on the samples for the training model, the evaluation of how well a model has learned to predict correct classifications using these samples can be measured using Loss. The higher the confidence value for the accurate classification of the sample, the lower the loss value depicted in Figure 7 . Figure 7. Loss per Epoch. 4.6 Sample image recognition & categorization of the rodents The sample image recognition and categorization of the rodents was done, and the data was collected in the form depicted in Figure 8 . Figure 8. Image recognition and categorization. 4.7 The Photovoltaic (PV) model The proposed solar-powered motion sensor system ( Figure 9 ) operates autonomously by harnessing clean, renewable energy from the sun. The photovoltaic (PV) module is the cornerstone of this system, converting sunlight directly into electrical energy through the photovoltaic effect. A photovoltaic system is an array of PV modules that comprise a number of solar cells that generate electrical power. Figure 9. Photovoltaic System. 4.8 Photon absorption When sunlight, basically composed of photons, strikes the solar cells, the photons transfer their energy to electrons within the semiconductor material, hence exciting them ( Vinod, Kumar, and Singh, 2018 ). This energy transfer is the initial step in converting solar energy into electrical energy. The photon absorption circuit is shown in Figure 10 . Figure 10. Photon absorption circuit. 4.9 Formation of electric potential in p-n junctions Each solar cell contains a junction between two types of semiconductor materials: n-type and p-type. The junction between the n-type and p-type materials forms an electric field, causing the excited electrons to migrate to the p-type layer and leaving behind a static positive charge. Simultaneously, the holes wander across the junction, leaving behind a static negative charge. Eventually, a depletion zone forms at the junction, preventing further movement of charge carriers ( Kirchartz and Rau, 2018 ). The separated static positive and negative charges establish an electric field across the depletion zone. This field generates the voltage necessary to drive current through an external circuit. As the semiconductor continuously absorbs sunlight, the energy excites more electrons, causing them to jump to the conduction band and leave behind holes in the valence band ( Chaudhery Mustansar Hussain, 2018 ). These freed electrons contribute to the electric current, moving toward the negative end, while holes move toward the positive end. According to Chaudhery Mustansar Hussain (2018) , when the absorbed photon energy exceeds the PV cell material’s bandgap energy, the atoms in the semiconductor collide, freeing more electrons and generating an electric current. This process ( Figure 11 ) effectively converts sunlight into electrical energy, harnessing solar power for practical use. Figure 11. Formation of electric potential in p-n junctions. 4.10 Series and parallel connections Individual solar cells generate a relatively small voltage, typically around 0.5 to 0.7 volts. To increase the voltage output, cells are wired in series within a module. Parallel connections of cell strings are used to achieve higher currents. This configuration allows a typical 60-cell PV module to produce approximately 30 volts DC at its maximum power point. ( Malinowski, León and Haitham Abu-Rub, 2019 ). 4.11 Solar charge controller A Solar Charge Controller performs several vital functions to optimize performance and safeguard equipment. Yassine and Anderson (2020) state that it prevents overcharging by regulating the voltage and current supplied to the batteries during sunlight hours, preserving battery life and preventing damage. Additionally, it blocks reverse current flow from batteries to panels, ensuring energy generated by the panels doesn’t drain back into the battery during low-light or nighttime conditions. 5. Conclusion By integrating OpenCV-based image recognition and classification, the proposed system provides automated monitoring and surveillance on farms by providing a method to detect and classify rodents without manual intervention. This uses exclusively solar energy, lowers labor expenses, and improves farm management efficiency. This technology also improves security and productivity by precisely identifying and chasing away the animals. This allows for prompt responses to possible threats or emergencies, such as land degradation and rodent intrusion in farms. The PV model describes how solar energy is converted to electrical energy, which powers the system. Although the development and possibilities of the proposed solar motion sensor system for monitoring and surveillance in farms are encouraging, it is necessary to consider some constrictions. First, even though the system of identification and classification of rodents uses OpenCV, the operation of the system can be influenced by external conditions that include illumination, weather changes, and other problems that may hinder the view of the camera. However, the system’s current capability is limited to detecting only small rodents and is not comprehensive enough for most forms of agriculture threats, such as large wild animals and human interlopers. Besides, a major incentive for the use of solar energy is that it is comparatively cheaper in terms of operation and may present reliability problems during cloudy days or for a long time in the day with minimal sunlight. Finally, there are no proposed systems for capturing pests or detecting invasions underground, which are critical issues in farm management to this day. This raises the following suggestions for future work: These limitations should be overcome to improve the setup in general and broaden its utility in various forms of agriculture. Future studies should be explored to have the system capture pests and deep scanning in the ground. This is because some rodents invade the farm through underground channels, which could be a challenge for the camera to capture. Additionally, the system could be enhanced to capture and detect wild animals and thieves that could be a threat to livestock farming. Ethics approval Not applicable. Availability of data and materials The underlying dataset for this study has been deposited in the public GitHub repository- https://github.com/fhg25/solar-power . fhg25 and Memoalbahar (2025) The repository contains all source data files, including automated detection system in agriculture, associated metadata, as well as processing scripts and documentation. This dataset is released under the Creative Commons Public Domain Dedication (CC0 1.0) to maximize reuse and interoperability by the research community. Acknowledgment The authors extend their appreciation to Umm Al-Qura University, Saudi Arabia for funding this research work through grant number: 25UQU4400257GSSR05. References Adirala Hema A, Naga Kesava KP, Dhana Meghana C: Animal Detection in Farms using PIR Motion Sensors and Alert System using IoT. Int. J. Innov. Res. Technol. 2025; 11 (10): 4586–4593. Bernardini A, Bianchi L, Sarti A: Loudspeaker virtualization–Part II: The inverse transducer model and the Direct-Inverse-Direct Chain. Signal Process. 2023; 202 : 108713. Publisher Full Text Reference Source Cambra C, Sendra S, García L, et al. : Low cost wireless sensor network for rodents detection. Proceedings of the 10th IFIP Wireless and Mobile Networking Conference (WMNC). IEEE; 2017; pp. 1–7. Publisher Full Text Reference Source Chaudhery M: Handbook of nanomaterials for industrial applications. Elsevier; 2018. Duwal R, Tamang CL: Image Processing Using OpenCV.2024. Publisher Full Text Emmanuel IO, Afolabi MO, Olalekan IA: Design and implementation of farm monitoring and security system. Int. J. Comput. Appl. 2018; 181 (9): 10–15. Publisher Full Text Futagami T, Yano T, Huang C, et al. : Experimental evaluation for daylight-linked gradation lighting control using image-based motion sensors. IEEJ Trans. Electr. Electron. Eng. 2020; 15 (5): 723–732. Publisher Full Text Kirchartz T, Rau U: What makes a good solar cell? Adv. Energy Mater. 2018; 8 (28): 1703385. Publisher Full Text Kurniawan F, Sofiarani A: Smart camera traffic for congestion using fuzzy methods based on serious game. Sains, Aplikasi, Komputasi dan Teknologi Informasi. 2020; 2 (2): 64. Publisher Full Text Lai S-C, Wang S-T, Liu K-L, et al. : A remote monitoring system for rodent infestation based on LoRaWAN. Sensors. 2023; 23 (9): 4185. PubMed Abstract | Publisher Full Text | Free Full Text Malinowski M, León JI, Abu-Rub H: Photovoltaic energy systems. Abu-Rub H, editor. Photovoltaic Energy Systems. John Wiley & Sons; 2019; pp. 347–389. Publisher Full Text Manthiram A: An outlook on lithium ion battery technology. ACS Central Science. 2017; 3 (10): 1063–1069. PubMed Abstract | Publisher Full Text | Free Full Text Khedkar M: Wireless intruder detection system for remote locations. Turk. J. Comput. Math. Educ. 2021; 12 (12): 1390–1401. Pahlavan K, Krishnamurthy P: Evolution and impact of Wi-Fi technology and applications: A historical perspective. Int. J. Wireless Inf. Networks. 2020; 28 : 3–19. Publisher Full Text Patel P, Kishor A, Mehta G: Smart solar-powered smart agricultural monitoring system using Internet of Things devices. Shaw RN, editor. AI and IoT in Renewable Energy (Studies in Infrastructure and Control). Springer Nature Singapore Pte Ltd.2021; pp. 101–109. Publisher Full Text Pulli T, Dönsberg T, Poikonen T, et al. : Advantages of white LED lamps and new detector technology in photometry. Light: Sci. Appl. 2015; 4 (9): e332. Publisher Full Text Ross R, Parsons L, Thai BS, et al. : An IoT smart rodent bait station system utilizing computer vision. Sensors. 2020; 20 (17): 4670. PubMed Abstract | Publisher Full Text | Free Full Text Sowmika T, Paul LR, Malathi G: IoT based smart rodent detection and fire alert system in farmland. Int. Res. J. Multidiscip. Technovation. 2020; 1–6. Publisher Full Text Vinod Kumar R, Singh SK: Solar photovoltaic modeling and simulation: As a renewable energy solution. Energy Rep. 2018; 4 : 701–712. Publisher Full Text Yassine W, Anderson KR: Testing and simulation of a solar PV/battery storage system with and without PWM charge control. Int. J. Renew. Energy Technol. 2020; 11 (1): 86. Publisher Full Text fhg25, Memoalbahar: Underlying data for Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process.2025. Reference Source Reference Source Comments on this article Comments (2) Version 3 VERSION 3 PUBLISHED 04 Nov 2025 Revised Comment ADD YOUR COMMENT Version 1 VERSION 1 PUBLISHED 25 Jun 2025 Discussion is closed on this version, please comment on the latest version above. Author Response 10 Sep 2025 Marwan Albahar , $usrAffiliation 10 Sep 2025 Author Response Reviewer comments Comment Answer 1 Replace simplified ML modeling with rigorous, transparent, and reproducible approaches Using GTM is just demonstration of the model since it is proposed. The focus ... Continue reading Reviewer comments Comment Answer 1 Replace simplified ML modeling with rigorous, transparent, and reproducible approaches Using GTM is just demonstration of the model since it is proposed. The focus is on the solar-system used to power other model components. However, more rigorous can be used for future research where there is practical implementation of the model hardware. 2 Improve experimental design and system evaluation with real-world benchmarks Real world phenomenon has been included. For instance, in the event of shadows, low light or darkness, falling of objects such leaves and twigs. The model could involve minimal monitoring from human personnel in minor cases, even though the system runs autonomously. Future research could leverage more robust real-time implementation using more sophisticated tools and algorithms to capture every aspect. 3 Broaden literature review with more recent and high-impact sources. The literature review has been reorganized concisely to highly related works. All the sources use are current, ie <5 years of publication. Previous research has been highlighted in summary and shortcomings established. Gaps are identified from the shortcomings hence justifying the proposed model. 4 Revise writing for conciseness and clarity in the methods and discussion sections The structure of the paper has been reorganized accordingly and the sections rectified. 5 Deepen theoretical or technical innovation beyond system integration Inclusion of theoretical perspective of the battery used. Reviewer comments Comment Answer 1 Replace simplified ML modeling with rigorous, transparent, and reproducible approaches Using GTM is just demonstration of the model since it is proposed. The focus is on the solar-system used to power other model components. However, more rigorous can be used for future research where there is practical implementation of the model hardware. 2 Improve experimental design and system evaluation with real-world benchmarks Real world phenomenon has been included. For instance, in the event of shadows, low light or darkness, falling of objects such leaves and twigs. The model could involve minimal monitoring from human personnel in minor cases, even though the system runs autonomously. Future research could leverage more robust real-time implementation using more sophisticated tools and algorithms to capture every aspect. 3 Broaden literature review with more recent and high-impact sources. The literature review has been reorganized concisely to highly related works. All the sources use are current, ie <5 years of publication. Previous research has been highlighted in summary and shortcomings established. Gaps are identified from the shortcomings hence justifying the proposed model. 4 Revise writing for conciseness and clarity in the methods and discussion sections The structure of the paper has been reorganized accordingly and the sections rectified. 5 Deepen theoretical or technical innovation beyond system integration Inclusion of theoretical perspective of the battery used. Competing Interests: No competing interests were disclosed. Close Report a concern Reader Comment 10 Sep 2025 Mohammad Alshehri , Taif University, Taif, Saudi Arabia 10 Sep 2025 Reader Comment The article presents a timely and innovative solution for farm surveillance by integrating solar power, motion sensing, and AI-based rodent detection. The combination of OpenCV with a solar-powered autonomous setup ... Continue reading The article presents a timely and innovative solution for farm surveillance by integrating solar power, motion sensing, and AI-based rodent detection. The combination of OpenCV with a solar-powered autonomous setup is practical, environmentally friendly, and highly relevant to sustainable agriculture. The authors’ commitment to open-source data and code is commendable, enabling reproducibility and future improvements. The concept is well-structured and offers a holistic design, including hardware (camera, solar panels, sensors) and software components. This interdisciplinary approach demonstrates strong potential for real-world applications, especially in rural or off-grid environments. The article presents a timely and innovative solution for farm surveillance by integrating solar power, motion sensing, and AI-based rodent detection. The combination of OpenCV with a solar-powered autonomous setup is practical, environmentally friendly, and highly relevant to sustainable agriculture. The authors’ commitment to open-source data and code is commendable, enabling reproducibility and future improvements. The concept is well-structured and offers a holistic design, including hardware (camera, solar panels, sensors) and software components. This interdisciplinary approach demonstrates strong potential for real-world applications, especially in rural or off-grid environments. Competing Interests: No competing interests were disclosed. Close Report a concern Discussion is closed on this version, please comment on the latest version above. Author details Author details 1 computer science, Umm Al-Qura University, Mecca, Makkah Province, Saudi Arabia 2 Department of Computing, College of Engineering and Computing in Al-Lith, Umm Al-Qura University, Mecca, Makkah Province, Saudi Arabia Foziah Gazzawe Roles: Conceptualization, Formal Analysis, Methodology, Project Administration, Resources, Visualization, Writing – Review & Editing Marwan Albahar Roles: Conceptualization, Funding Acquisition, Project Administration, Resources, Supervision, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information This research work was funded by Umm Al-Qura University, Saudi Arabia, under grant number: 25UQU4400257GSSR05. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Article Versions (3) version 3 Revised Published: 04 Nov 2025, 14:624 https://doi.org/10.12688/f1000research.164633.3 version 2 Revised Published: 16 Sep 2025, 14:624 https://doi.org/10.12688/f1000research.164633.2 version 1 Published: 25 Jun 2025, 14:624 https://doi.org/10.12688/f1000research.164633.1 Copyright © 2025 Gazzawe F and Albahar M. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Gazzawe F and Albahar M. Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process [version 1; peer review: 1 approved with reservations] . F1000Research 2025, 14 :624 ( https://doi.org/10.12688/f1000research.164633.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 1 VERSION 1 PUBLISHED 25 Jun 2025 Views 0 Cite How to cite this report: Ramli RM. Reviewer Report For: Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process [version 1; peer review: 1 approved with reservations] . F1000Research 2025, 14 :624 ( https://doi.org/10.5256/f1000research.181174.r394971 ) The direct URL for this report is: https://f1000research.com/articles/14-624/v1#referee-response-394971 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 18 Aug 2025 Roshahliza M. Ramli , University Malaysia Pahang Al-Sultan Abdullah, Pahang, Malaysia Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.181174.r394971 Suggestions to improving the paper: Replace simplified ML modeling with rigorous, transparent, and reproducible approaches. Improve experimental design and system evaluation with real-world benchmarks. Broaden literature review with more recent and high-impact ... Continue reading READ ALL Suggestions to improving the paper: Replace simplified ML modeling with rigorous, transparent, and reproducible approaches. Improve experimental design and system evaluation with real-world benchmarks. Broaden literature review with more recent and high-impact sources. Revise writing for conciseness and clarity in the methods and discussion sections. Deepen theoretical or technical innovation beyond system integration. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly Competing Interests: No competing interests were disclosed. Reviewer Expertise: smart systems, adaptive control systems, applied electronics, precision agriculture I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Ramli RM. Reviewer Report For: Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process [version 1; peer review: 1 approved with reservations] . F1000Research 2025, 14 :624 ( https://doi.org/10.5256/f1000research.181174.r394971 ) The direct URL for this report is: https://f1000research.com/articles/14-624/v1#referee-response-394971 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Comments on this article Comments (2) Version 3 VERSION 3 PUBLISHED 04 Nov 2025 Revised Comment ADD YOUR COMMENT Version 1 VERSION 1 PUBLISHED 25 Jun 2025 Discussion is closed on this version, please comment on the latest version above. Author Response 10 Sep 2025 Marwan Albahar , $usrAffiliation 10 Sep 2025 Author Response Reviewer comments Comment Answer 1 Replace simplified ML modeling with rigorous, transparent, and reproducible approaches Using GTM is just demonstration of the model since it is proposed. The focus ... Continue reading Reviewer comments Comment Answer 1 Replace simplified ML modeling with rigorous, transparent, and reproducible approaches Using GTM is just demonstration of the model since it is proposed. The focus is on the solar-system used to power other model components. However, more rigorous can be used for future research where there is practical implementation of the model hardware. 2 Improve experimental design and system evaluation with real-world benchmarks Real world phenomenon has been included. For instance, in the event of shadows, low light or darkness, falling of objects such leaves and twigs. The model could involve minimal monitoring from human personnel in minor cases, even though the system runs autonomously. Future research could leverage more robust real-time implementation using more sophisticated tools and algorithms to capture every aspect. 3 Broaden literature review with more recent and high-impact sources. The literature review has been reorganized concisely to highly related works. All the sources use are current, ie <5 years of publication. Previous research has been highlighted in summary and shortcomings established. Gaps are identified from the shortcomings hence justifying the proposed model. 4 Revise writing for conciseness and clarity in the methods and discussion sections The structure of the paper has been reorganized accordingly and the sections rectified. 5 Deepen theoretical or technical innovation beyond system integration Inclusion of theoretical perspective of the battery used. Reviewer comments Comment Answer 1 Replace simplified ML modeling with rigorous, transparent, and reproducible approaches Using GTM is just demonstration of the model since it is proposed. The focus is on the solar-system used to power other model components. However, more rigorous can be used for future research where there is practical implementation of the model hardware. 2 Improve experimental design and system evaluation with real-world benchmarks Real world phenomenon has been included. For instance, in the event of shadows, low light or darkness, falling of objects such leaves and twigs. The model could involve minimal monitoring from human personnel in minor cases, even though the system runs autonomously. Future research could leverage more robust real-time implementation using more sophisticated tools and algorithms to capture every aspect. 3 Broaden literature review with more recent and high-impact sources. The literature review has been reorganized concisely to highly related works. All the sources use are current, ie <5 years of publication. Previous research has been highlighted in summary and shortcomings established. Gaps are identified from the shortcomings hence justifying the proposed model. 4 Revise writing for conciseness and clarity in the methods and discussion sections The structure of the paper has been reorganized accordingly and the sections rectified. 5 Deepen theoretical or technical innovation beyond system integration Inclusion of theoretical perspective of the battery used. Competing Interests: No competing interests were disclosed. Close Report a concern Reader Comment 10 Sep 2025 Mohammad Alshehri , Taif University, Taif, Saudi Arabia 10 Sep 2025 Reader Comment The article presents a timely and innovative solution for farm surveillance by integrating solar power, motion sensing, and AI-based rodent detection. The combination of OpenCV with a solar-powered autonomous setup ... Continue reading The article presents a timely and innovative solution for farm surveillance by integrating solar power, motion sensing, and AI-based rodent detection. The combination of OpenCV with a solar-powered autonomous setup is practical, environmentally friendly, and highly relevant to sustainable agriculture. The authors’ commitment to open-source data and code is commendable, enabling reproducibility and future improvements. The concept is well-structured and offers a holistic design, including hardware (camera, solar panels, sensors) and software components. This interdisciplinary approach demonstrates strong potential for real-world applications, especially in rural or off-grid environments. The article presents a timely and innovative solution for farm surveillance by integrating solar power, motion sensing, and AI-based rodent detection. The combination of OpenCV with a solar-powered autonomous setup is practical, environmentally friendly, and highly relevant to sustainable agriculture. The authors’ commitment to open-source data and code is commendable, enabling reproducibility and future improvements. The concept is well-structured and offers a holistic design, including hardware (camera, solar panels, sensors) and software components. This interdisciplinary approach demonstrates strong potential for real-world applications, especially in rural or off-grid environments. Competing Interests: No competing interests were disclosed. Close Report a concern Discussion is closed on this version, please comment on the latest version above. keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 3 4 Version 3 (revision) 04 Nov 25 read read Version 2 (revision) 16 Sep 25 read Version 1 25 Jun 25 read Roshahliza M. Ramli , University Malaysia Pahang Al-Sultan Abdullah, Pahang, Malaysia G. Radhika Deshmukh , Shri Shivaji Scirnce College, Amravati, India Gangu Dharmaraju , Gandhi Institute of Engineering and Technology University, Gunupur, India; GMR Institute of Technology, Razam, India K Kamakshi Priya , Saveetha School of Engineering, SIMATS, Chennai, India Comments on this article All Comments (2) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Priya K. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions. 05 Feb 2026 | for Version 3 K Kamakshi Priya , Saveetha School of Engineering, SIMATS, Chennai, India 0 Views copyright © 2026 Priya K. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions. format_quote Cite this report speaker_notes Responses (0) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The manuscript demonstrates significant relevance to both the scientific and industrial communities and holds potential archival quality; however, minor revisions are recommended to improve its overall clarity and impact. The introduction effectively sets the stage but should be more focused on clearly articulating the research objectives and hypotheses. The literature review, while comprehensive, would benefit from the inclusion of more recent studies, particularly "Investigation of heat transport characteristics of titanium dioxide nanofluids with corrugated tube &. Thermal management using nano coated heat sink for electric vehicle battery cooling". The methodology is well-structured, but it lacks detailed descriptions of data collection and analysis procedures, which are essential for replicability. Additionally, the rationale for the chosen sample size is insufficiently justified; incorporating a statistical power analysis or referencing prior research would strengthen this aspect. The explanation of statistical methods also requires more clarity to be accessible to a broader readership. Furthermore, the results and discussion section needs to elaborate on key scientific issues more thoroughly and integrate recent literature to provide stronger contextual grounding. In particular, references such as “Improving the performance of heat sinks through the integration of fins and the utilization of graphene-mixed latent heat energy storage & An experimental investigation on winter heat storage in compact salinity gradient solar ponds with silicon dioxide particulates infused paraffin wax ” are recommended to enrich the discussion and align the study with current research trends. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Solar and Renewable Energy I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (0) Priya KK. Peer Review Report For: Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process [version 1; peer review: 1 approved with reservations] . F1000Research 2025, 14 :624 ( https://doi.org/10.5256/f1000research.189869.r449514) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-624/v3#referee-response-449514 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Dharmaraju G. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 02 Jan 2026 | for Version 3 Gangu Dharmaraju , Gandhi Institute of Engineering and Technology University, Gunupur, India; Computer Science and Engineering, GMR Institute of Technology, Razam, Andhra Pradesh, India 0 Views copyright © 2026 Dharmaraju G. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions 1. Clarity in Literature Survey: Yes, the cited papers for related work are clearly related to the proposed work. 2. Novelty: Yes, solar power and motion sensing are integrated with YOLOv8-based CV in the agriculture monitoring system, and it addresses a real agricultural gap. 3. Methodology: Partly, a very small dataset was used, which cannot support strong generalization. 4. Statistical Analysis: Partly, FPS, confidence distribution, and detections are helpful but not enough. Approved with reservations , since there is a scope to work with deeper ML validation Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Partly Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Deep Learning, Machine Learning I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (0) Dharmaraju G. Peer Review Report For: Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process [version 1; peer review: 1 approved with reservations] . F1000Research 2025, 14 :624 ( https://doi.org/10.5256/f1000research.189869.r437151) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-624/v3#referee-response-437151 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2025 Deshmukh G. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 09 Oct 2025 | for Version 2 G. Radhika Deshmukh , Shri Shivaji Scirnce College, Amravati, Maharashtra, India 0 Views copyright © 2025 Deshmukh G. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions A brief summary of the peer review assessment for the article: Clarity and Literature Citation : Yes The work is well-structured, clear in presenting aims and results, and cites recent, relevant literature. Study Design and Technical Soundness : Partly The concept and design are sound, but the implementation is mainly a demonstration using a small dataset and Google Teachable Machine. More powerful modeling and field validation are needed. Methods and Replication: Partly Methods are described in reasonable detail, but demonstration-level modeling and limited data restrict full experimental replication and robustness. Statistical Analysi s: Partly Standard metrics are provided, but small sample sizes limit the reliability and clarification of statistical results. Data Availability and Reproducibility : Yes Source data and code are publicly available under Creative Commons licensing, supporting reproducibility. Conclusions Support: Partly Conclusions are justified for the demonstration stage but remain preliminary pending full field validation and robust machine learning modeling. Strengths i nclude timeliness, relevance, novelty, interdisciplinarity, and open science practices. Weaknesses center on limited machine learning rigor, experimental design mostly at demonstration level, and a need for deeper literature framing and critical comparison. Recommendations suggest further ML experimentation, expanded field benchmarking, clearer writing, more technical innovation highlights, and additional theoretical contributions on energy management. Overall, the study has good potential and fills a practical research gap but requires addressing robustness and validation issues before full publication quality can be reached. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly Competing Interests No competing interests were disclosed. Reviewer Expertise Luminiscence,Renweable Energy, alternative theories of Gravitation and Cosmology,Educational Physics I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (0) Deshmukh GR. Peer Review Report For: Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process [version 1; peer review: 1 approved with reservations] . F1000Research 2025, 14 :624 ( https://doi.org/10.5256/f1000research.187475.r415205) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-624/v2#referee-response-415205 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2025 Ramli R. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 18 Aug 2025 | for Version 1 Roshahliza M. Ramli , University Malaysia Pahang Al-Sultan Abdullah, Pahang, Malaysia 0 Views copyright © 2025 Ramli R. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Suggestions to improving the paper: Replace simplified ML modeling with rigorous, transparent, and reproducible approaches. Improve experimental design and system evaluation with real-world benchmarks. Broaden literature review with more recent and high-impact sources. Revise writing for conciseness and clarity in the methods and discussion sections. Deepen theoretical or technical innovation beyond system integration. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly Competing Interests No competing interests were disclosed. Reviewer Expertise smart systems, adaptive control systems, applied electronics, precision agriculture I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (0) Ramli RM. Peer Review Report For: Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process [version 1; peer review: 1 approved with reservations] . F1000Research 2025, 14 :624 ( https://doi.org/10.5256/f1000research.181174.r394971) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-624/v1#referee-response-394971 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Adjust parameters to alter display View on desktop for interactive features Includes Interactive Elements View on desktop for interactive features Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). You work at the same institute as any of the authors. You hope/expect to benefit (e.g. favour or employment) as a result of your submission. You are an Editor for the journal in which the article is published. Examples of 'Financial Competing Interests' You expect to receive, or in the past 4 years have received, any of the following from any commercial organisation that may gain financially from your submission: a salary, fees, funding, reimbursements. You expect to receive, or in the past 4 years have received, shared grant support or other funding with any of the authors. You hold, or are currently applying for, any patents or significant stocks/shares relating to the subject matter of the paper you are commenting on. Stay Updated Sign up for content alerts and receive a weekly or monthly email with all newly published articles Register with F1000Research Already registered? Sign in Not now, thanks close PLEASE NOTE If you are an AUTHOR of this article, please check that you signed in with the account associated with this article otherwise we cannot automatically identify your role as an author and your comment will be labelled as a “User Comment”. If you are a REVIEWER of this article, please check that you have signed in with the account associated with this article and then go to your account to submit your report, please do not post your review here. If you do not have access to your original account, please contact us . All commenters must hold a formal affiliation as per our Policies . The information that you give us will be displayed next to your comment. User comments must be in English, comprehensible and relevant to the article under discussion. We reserve the right to remove any comments that we consider to be inappropriate, offensive or otherwise in breach of the User Comment Terms and Conditions . Commenters must not use a comment for personal attacks. When criticisms of the article are based on unpublished data, the data should be made available. I accept the User Comment Terms and Conditions Please confirm that you accept the User Comment Terms and Conditions. Affiliation ✕ refresh Please enter your institution. Note: To add your institution or organisation, start typing the name and then select the correct name from the list. Where applicable, the name will appear in both the original language and in English. Do not paste in the name. If the name does not appear in the drop-down list, we will display the information you have entered. ✕ refresh Country/Region * USA UK Canada China France Germany Afghanistan Aland Islands Albania Algeria American Samoa Andorra Angola Anguilla Antarctica Antigua and Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Bouvet Island Brazil British Indian Ocean Territory British Virgin Islands Brunei Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Christmas Island Cocos (Keeling) Islands Colombia Comoros Congo Cook Islands Costa Rica Cote d'Ivoire Croatia Cuba Cyprus Czech Republic Democratic Republic of the Congo Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Falkland Islands Faroe Islands Federated States of Micronesia Fiji Finland France French Guiana French Polynesia French Southern Territories Gabon Georgia Germany Ghana Gibraltar Greece Greenland Grenada Guadeloupe Guam Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Heard Island and Mcdonald Islands Holy See (Vatican City State) Honduras Hong Kong Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jersey Jordan Kazakhstan Kenya Kiribati Kosovo (Serbia and Montenegro) Kuwait Kyrgyzstan Lao People's Democratic Republic Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Macao Madagascar Malawi Malaysia Maldives Mali Malta Marshall Islands Martinique Mauritania Mauritius Mayotte Mexico Minor Outlying Islands of the United States Moldova Monaco Mongolia Montenegro Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands Antilles New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norfolk Island North Korea North Macedonia Northern Mariana Islands Norway Oman Pakistan Palau Palestinian Territory Panama Papua New Guinea Paraguay Peru Philippines Pitcairn Poland Portugal Puerto Rico Qatar Reunion Romania Russian Federation Rwanda Saint Helena Saint Kitts and Nevis Saint Lucia Saint Pierre and Miquelon Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa South Georgia and the South Sandwich Is South Korea South Sudan Spain Sri Lanka Sudan Suriname Svalbard and Jan Mayen Swaziland Sweden Switzerland Syria Taiwan Tajikistan Tanzania Thailand The Gambia The Netherlands Timor-Leste Togo Tokelau Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Turks and Caicos Islands Tuvalu UK USA Uganda Ukraine United Arab Emirates United States Virgin Islands Uruguay Uzbekistan Vanuatu Venezuela Vietnam Wallis and Futuna West Bank and Gaza Strip Western Sahara Yemen Zambia Zimbabwe Please select your country/region. You must enter a comment. Competing Interests Please disclose any competing interests that might be construed to influence your judgment of the article's or peer review report's validity or importance. Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). You work at the same institute as any of the authors. You hope/expect to benefit (e.g. favour or employment) as a result of your submission. You are an Editor for the journal in which the article is published. Examples of 'Financial Competing Interests' You expect to receive, or in the past 4 years have received, any of the following from any commercial organisation that may gain financially from your submission: a salary, fees, funding, reimbursements. You expect to receive, or in the past 4 years have received, shared grant support or other funding with any of the authors. You hold, or are currently applying for, any patents or significant stocks/shares relating to the subject matter of the paper you are commenting on. Please state your competing interests The comment has been saved. An error has occurred. Please try again. Cancel Post var lTitle = "Proposed Solar-Powered Motion Sensor for...".replace("'", ''); var linkedInUrl = "http://www.linkedin.com/shareArticle?url=https://f1000research.com/articles/14-624/v1" + "&title=" + encodeURIComponent(lTitle) + "&summary=" + encodeURIComponent('Read the article by '); var deliciousUrl = "https://del.icio.us/post?url=https://f1000research.com/articles/14-624/v1&title=" + encodeURIComponent(lTitle); var redditUrl = "http://reddit.com/submit?url=https://f1000research.com/articles/14-624/v1" + "&title=" + encodeURIComponent(lTitle); linkedInUrl += encodeURIComponent('Gazzawe F and Albahar M'); var offsetTop = /chrome/i.test( navigator.userAgent ) ? 4 : -10; var addthis_config = { ui_offset_top: offsetTop, services_compact : "facebook,twitter,www.linkedin.com,www.mendeley.com,reddit.com", services_expanded : "facebook,twitter,www.linkedin.com,www.mendeley.com,reddit.com", services_custom : [ { name: "LinkedIn", url: linkedInUrl, icon:"/img/icon/at_linkedin.svg" }, { name: "Mendeley", url: "http://www.mendeley.com/import/?url=https://f1000research.com/articles/14-624/v1/mendeley", icon:"/img/icon/at_mendeley.svg" }, { name: "Reddit", url: redditUrl, icon:"/img/icon/at_reddit.svg" }, ] }; var addthis_share = { url: "https://f1000research.com/articles/14-624", templates : { twitter : "Proposed Solar-Powered Motion Sensor for Farm Monitoring and.... Gazzawe F and Albahar M, published by " + "@F1000Research" + ", https://f1000research.com/articles/14-624/v1" } }; if (typeof(addthis) != "undefined"){ addthis.addEventListener('addthis.ready', checkCount); addthis.addEventListener('addthis.menu.share', checkCount); } $(".f1r-shares-twitter").attr("href", "https://twitter.com/intent/tweet?text=" + addthis_share.templates.twitter); $(".f1r-shares-facebook").attr("href", "https://www.facebook.com/sharer/sharer.php?u=" + addthis_share.url); $(".f1r-shares-linkedin").attr("href", addthis_config.services_custom[0].url); $(".f1r-shares-reddit").attr("href", addthis_config.services_custom[2].url); $(".f1r-shares-mendelay").attr("href", addthis_config.services_custom[1].url); function checkCount(){ setTimeout(function(){ $(".addthis_button_expanded").each(function(){ var count = $(this).text(); if (count !== "" && count != "0") $(this).removeClass("is-hidden"); else $(this).addClass("is-hidden"); }); }, 1000); } close How to cite this report {{reportCitation}} Cancel Copy Citation Details $(function(){R.ui.buttonDropdowns('.dropdown-for-downloads');}); $(function(){R.ui.toolbarDropdowns('.toolbar-dropdown-for-downloads');}); $.get("/articles/acj/164633/181174") new F1000.Clipboard(); new F1000.ThesaurusTermsDisplay("articles", "article", "181174"); $(document).ready(function() { $( "#frame1" ).on('load', function() { var mydiv = $(this).contents().find("div"); var h = mydiv.height(); console.log(h) }); var tooltipLivingFigure = jQuery(".interactive-living-figure-label .icon-more-info"), titleLivingFigure = tooltipLivingFigure.attr("title"); tooltipLivingFigure.simpletip({ fixed: true, position: ["-115", "30"], baseClass: 'small-tooltip', content:titleLivingFigure + " " }); tooltipLivingFigure.removeAttr("title"); $("body").on("click", ".cite-living-figure", function(e) { e.preventDefault(); var ref = $(this).attr("data-ref"); $(this).closest(".living-figure-list-container").find("#" + ref).fadeIn(200); }); $("body").on("click", ".close-cite-living-figure", function(e) { e.preventDefault(); $(this).closest(".popup-window-wrapper").fadeOut(200); }); $(document).on("mouseup", function(e) { var metricsContainer = $(".article-metrics-popover-wrapper"); if (!metricsContainer.is(e.target) && metricsContainer.has(e.target).length === 0) { $(".article-metrics-close-button").click(); } }); var articleId = $('#articleId').val(); if($("#main-article-count-box").attachArticleMetrics) { $("#main-article-count-box").attachArticleMetrics(articleId, { articleMetricsView: true }); } }); var figshareWidget = $(".new_figshare_widget"); if (figshareWidget.length > 0) { window.figshare.load("f1000", function(Widget) { // Select a tag/tags defined in your page. In this tag we will place the widget. _.map(figshareWidget, function(el){ var widget = new Widget({ articleId: $(el).attr("figshare_articleId") //height:300 // this is the height of the viewer part. [Default: 550] }); widget.initialize(); // initialize the widget widget.mount(el); // mount it in a tag that's on your page // this will save the widget on the global scope for later use from // your JS scripts. This line is optional. //window.widget = widget; }); }); } close Error Close Add Reset F1000.MICROSERVICES.AFFILIATION = ''; $(document).ready(function () { $('.js-affiliations-form').each((index, form) => { new AffiliationForm({ formId: form.id, institutionErrorSelector: '.comment-enter-institution', departmentErrorSelector: '.comment-enter-department', placeSelector: '.js-add-comment-place', stateSelector: '.js-add-comment-state', zipCodeSelector: '.js-add-comment-zipcode', countrySelector: '.js-add-comment-country', countryErrorSelector: '.comment-enter-country', }); }); }); $(document).ready(function () { var reportIds = { "432158": 0, "442910": 0, "432159": 0, "442911": 0, "432156": 0, "442908": 0, "432157": 0, "442909": 0, "432154": 0, "442906": 0, "429850": 0, "432155": 0, "442907": 0, "429851": 0, "432152": 0, "432153": 0, "442914": 0, "442915": 0, "432160": 0, "442912": 0, "432161": 0, "442913": 0, "414782": 0, "449430": 0, "437150": 0, "447902": 0, "447903": 0, "437151": 11, "437148": 0, "447900": 0, "437149": 0, "447901": 0, "437146": 0, "447898": 0, "437147": 0, "447899": 0, "447896": 0, "437145": 0, "447897": 0, "437154": 0, "437152": 0, "447904": 0, "437153": 0, "447905": 0, "445615": 0, "445622": 0, "445623": 0, "445620": 0, "445621": 0, "445618": 0, "445619": 0, "445616": 0, "445617": 0, "396478": 0, "396479": 0, "396476": 0, "396477": 0, "396475": 0, "445624": 0, "396484": 0, "396482": 0, "396483": 0, "396480": 0, "396481": 0, "430551": 0, "394974": 0, "430558": 0, "394975": 0, "430559": 0, "394972": 0, "430556": 0, "394973": 0, "430557": 0, "394970": 0, "430554": 0, "394971": 18, "430555": 0, "394968": 0, "430552": 0, "394969": 0, "430553": 0, "449510": 0, "415206": 0, "449511": 0, "415207": 0, "449508": 0, "415204": 0, "449509": 0, "415205": 20, "415202": 0, "449507": 0, "415203": 0, "394976": 0, "430560": 0, "394977": 0, "449514": 3, "415210": 0, "449515": 0, "415211": 0, "449512": 0, "415208": 0, "449513": 0, "415209": 0, }; $(".referee-response-container,.js-referee-report").each(function(index, el) { var reportId = $(el).attr("data-reportid"), reportCount = reportIds[reportId] || 0; $(el).find(".comments-count-container,.js-referee-report-views").html(reportCount); }); var uuidInput = $("#article_uuid"), oldUUId = uuidInput.val(), newUUId = "2209cb06-2fb3-47a0-8a0a-f385d34d79c2"; uuidInput.val(newUUId); $("a[href*='article_uuid=']").each(function(index, el) { var newHref = $(el).attr("href").replace(oldUUId, newUUId); $(el).attr("href", newHref); }); }); An innovative open access publishing platform offering rapid publication and open peer review, whilst supporting data deposition and sharing. Browse Gateways Collections How it Works Contact For Developers Cookie Notice Privacy Notice RSS Submit Your Research Follow us © 2012-2026 F1000 Research Ltd. ISSN 2046-1402 | Legal | Partner of Research4Life • CrossRef • ORCID • FAIRSharing R.templateTests.simpleTemplate = R.template(' $text $text $text $text $text '); R.templateTests.runTests(); var F1000platform = new F1000.Platform({ name: "f1000research", displayName: "F1000Research", hostName: "f1000research.com", id: "1", editorialEmail: "[email protected]", infoEmail: "[email protected]", usePmcStats: true }); $(function(){R.ui.dropdowns('.dropdown-for-authors, .dropdown-for-about, .dropdown-for-myresearch');}); // $(function(){R.ui.dropdowns('.dropdown-for-referees');}); $(document).ready(function () { if ($(".cookie-warning").is(":visible")) { $(".sticky").css("margin-bottom", "35px"); $(".devices").addClass("devices-and-cookie-warning"); } $(".cookie-warning .close-button").click(function (e) { $(".devices").removeClass("devices-and-cookie-warning"); $(".sticky").css("margin-bottom", "0"); }); $("#tweeter-feed .tweet-message").each(function (i, message) { var self = $(message); self.html(linkify(self.html())); }); $(".partner").on("mouseenter mouseleave", function() { $(this).find(".gray-scale, .colour").toggleClass("is-hidden"); }); }); Sign In Remember me Forgotten your password? Sign In Cancel Email or password not correct. Please try again Please wait... $(function(){ // Note: All the setup needs to run against a name attribute and *not* the id due the clonish // nature of facebox... $("a[id=googleSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("GOOGLE"); $("form[id=oAuthForm]").submit(); }); $("a[id=facebookSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("FACEBOOK"); $("form[id=oAuthForm]").submit(); }); $("a[id=orcidSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("ORCID"); $("form[id=oAuthForm]").submit(); }); }); If you've forgotten your password, please enter your email address below and we'll send you instructions on how to reset your password. The email address should be the one you originally registered with F1000. Email address not valid, please try again You registered with F1000 via Google, so we cannot reset your password. To sign in, please click here . If you still need help with your Google account password, please click here . You registered with F1000 via Facebook, so we cannot reset your password. To sign in, please click here . If you still need help with your Facebook account password, please click here . Code not correct, please try again Reset password Cancel Email us for further assistance. Server error, please try again. If your email address is registered with us, we will email you instructions to reset your password. If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance. Please wait... Register $(document).ready(function () { signIn.createSignInAsRow($("#sign-in-form-gfb-popup")); $(".target-field").each(function () { var uris = $(this).val().split("/"); if (uris.pop() === "login") { $(this).val(uris.toString().replace(",","/")); } }); });