Ai & Ml-based Pet Feeding System

Ai & Ml-based Pet Feeding System | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (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;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Ai & Ml-based Pet Feeding System B.amulya, Chinna Royyala Arun Kumar, Anupoju Akhil, Cheemala Sai Kumar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6665411/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The AI and ML-Based Pet Feeding System is a software-driven solution designed to automate and optimize pet feeding recommendations based on pet species classification using digital image processing. The system utilizes a convolutional neural network (CNN) to classify different pet species from images captured by the user. Following classification, the system provides personalized feeding suggestions tailored to the specific needs of the pet, based on established feeding guidelines for various species. The project leverages Python and TensorFlow for deep learning, OpenCV for image processing, and Tkinter for a user-friendly graphical interface. The system aims to simplify pet care by offering a quick and accurate method for determining appropriate feeding practices, reducing the dependency on generic advice and enhancing the well-being of pets through informed, species-specific recommendations. Machine Learning Pet Species Classification Image Processing Convolutional Neural Network TensorFlow Digital Image Processing (DIP) Pet Recognition Image Classification Deep Learning AI-Based Pet Feeding Automated Feeding Recommendation Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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