Agri Sage: A Mobile Application for Agricultural Disease Detection, E-Commerce, and Real-Time Information Systems

Talha Aslam, Shatha Ghareeb, Jamila Mustafina

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper introduces Agri Sage, a mobile application aimed at addressing critical challenges in modern agriculture. Agri Sage integrates real-time plant disease detection using machine learning, an e-commerce platform for agricultural products, and weather updates alongside government pricing and subsidy information. Leveraging TensorFlow Lite for image analysis, the app diagnoses plant diseases even under suboptimal image conditions. The e-commerce platform allows farmers to connect with buyers and manage bulk transactions, while real-time weather and government data help farmers make informed decisions. This holistic approach enhances farm management, boosts productivity, and makes technology accessible to farmers in diverse environments. Extensive testing of Agri Sage demonstrated its efficacy in real-world applications, particularly in improving crop health and market access.
Original languageEnglish
Title of host publication2024 17th International Conference on Development in eSystem Engineering (DeSE)
PublisherIEEE
Pages84-88
Number of pages5
ISBN (Print)9798350368697
DOIs
Publication statusPublished - 11 Mar 2025
Event17th International Conference on Development in eSystem Engineering (DeSE) - University of Sharjah, Dubai, United Arab Emirates
Duration: 6 Nov 20248 Nov 2024
https://dese.ai/dese-2024/

Conference

Conference17th International Conference on Development in eSystem Engineering (DeSE)
Country/TerritoryUnited Arab Emirates
CityDubai
Period6/11/248/11/24
Internet address

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

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