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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM47657
Volume:
9 |
5 |
May 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Even though agriculture is a pillar of many economies, farmers nevertheless confront difficulties because of crop diseases, erratic weather patterns, a lack of reliable information, and poor government-to-government communication. We have created a comprehensive mobile application called AgriNama to help farmers with technology-driven solutions in order to address these problems. Multiple modules, including weather forecasting, yield prediction, crop disease detection, an intelligent agricultural chatbot, a farmer-government communication interface, and a wealth of information about crops and animals, are integrated into this all-in-one platform. Early intervention and decreased crop loss are made possible by the crop disease detection module’s high-accuracy disease identification based on deep learning analysis of plant photos. To assist farmers in making well-informed planning decisions, the yield prediction module makes use of machine learning algorithms based on historical and environmental data. Users may get ready for weather conditions that could impact their fields with the help of real-time weather predictions. Expert assistance is always available thanks to the AI-powered chatbot’s user-friendly responses to agricultural questions. Furthermore, by enabling users to voice concerns, access polls, and receive information straight from authorities, AgriNama improves contact between farmers and government representatives. With comprehensive information about crops, animals, and best practices, the app also functions as a teaching tool.AgriNama wants to transform the agricultural ecosystem and improve the farming community by fusing artificial intelligence, real-time data, and user-centric design.
KEYWORDS
Publication Date
12/4/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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