An AI-Enabled Wearable System for Tactical Sign Language Recognition and Secure Data Transmission

An AI-Enabled Wearable System for Tactical Sign Language Recognition and Secure Data Transmission | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 18 December 2025 V1 Latest version Share on An AI-Enabled Wearable System for Tactical Sign Language Recognition and Secure Data Transmission Authors : Priyanshi Soni 0009-0006-7610-8933 [email protected] , Shaligram Prajapat , and Aditya R Chandre Authors Info & Affiliations https://doi.org/10.22541/au.176607235.52173437/v1 152 views 75 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract In high-stakes critical combat environments, soldiers have to operate in complete pin-drop silence. They have to exchange vital information discreetly without making sound/noise while making sure that their positions are still hidden! Traditional means like radio or any general spoken commands can expose positions or prove a bit ineffective and risky amid battlefield noise and electronic interference. Therefore, in such critical situations, soldiers rely on visual signaling systems, standard hand gestures, and body language. It is a better replacement for conventional means, which can be a bit impractical and dangerous. But then this is also constrained by the environment, including poor visibility, physical obstacles in the terrain, and the inherent risk of misinterpretation. Such conditions can cause communication breakdown. To overcome these challenges, this paper presents the prototype for an AI-powered platform, "Tactical Sign Language Communication System" (TSLCS). It represents a military communication system for secure, unambiguous and tamper-free communication while avoiding unauthorised access and any scope of misinterpretation. It recognizes gestures (using deep learning and RNN), secure encryption protocols, and transmission technologies to provide reliable communication among military personnel. It's a next-generation prototype system created to give soldiers better ways to communicate and work amid the crushing conditions of a hostile battlefield. Its highly developed computer vision and AI technology interprets hand signals, facial expressions and body language. It can function in a variety of lighting and sound conditions, including the dark or places that are too noisy. The system also ensures the security of its data using strong encryption so that no one can hack it. It sends important information like GPS location and updates about team members' status. Overall, this technology is trying to make teamwork, safety and decision-making better during a mission. Supplementary Material File (thec3ai-29.pdf) Download 1.51 MB Information & Authors Information Version history V1 Version 1 18 December 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords ai-powered systems computer vision encryption gesture recognition gps integration mesh network military communication real-time communication secure communication networks sign language (sl) tactical communication wearable devices Authors Affiliations Priyanshi Soni 0009-0006-7610-8933 [email protected] View all articles by this author Shaligram Prajapat International Institute of Professional Studies View all articles by this author Aditya R Chandre PCRO Labs Foundation View all articles by this author Metrics & Citations Metrics Article Usage 152 views 75 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Priyanshi Soni, Shaligram Prajapat, Aditya R Chandre. An AI-Enabled Wearable System for Tactical Sign Language Recognition and Secure Data Transmission. Authorea . 18 December 2025. DOI: https://doi.org/10.22541/au.176607235.52173437/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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