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 language | English |
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Title of host publication | 2024 17th International Conference on Development in eSystem Engineering (DeSE) |
Publisher | IEEE |
Pages | 84-88 |
Number of pages | 5 |
ISBN (Print) | 9798350368697 |
DOIs | |
Publication status | Published - 11 Mar 2025 |
Event | 17th International Conference on Development in eSystem Engineering (DeSE) - University of Sharjah, Dubai, United Arab Emirates Duration: 6 Nov 2024 → 8 Nov 2024 https://dese.ai/dese-2024/ |
Conference
Conference | 17th International Conference on Development in eSystem Engineering (DeSE) |
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Country/Territory | United Arab Emirates |
City | Dubai |
Period | 6/11/24 → 8/11/24 |
Internet address |
Bibliographical note
Publisher Copyright:© 2024 IEEE.