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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM47625
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.
Agriculture remains the rural livelihoods backbone, particularly in developing countries. Yet, farmers frequently encounter resilient issues like unforeseen pest epidemics, poor access to trustworthy markets, and inadequate timely intervention for decision-making in farming. AgriSphere, as a one-stop, AI-based agricultural platform introduced here, aims to overcome such practical issues. The platform consolidates a number of smart features such as real-time crop disease detection using deep learning, predictive crop growth analytics, and a special digital marketplace that facilitates direct-to-consumer and business-to-business transactions. It also provides weather forecasts and an AI chatbot to facilitate well-informed decision-making in local languages. Developed with cloud services, scalable machine learning models, and accessible web technologies, AgriSphere is made to be accessible and flexible. Beyond being a technical solution, it seeks to improve farm productivity, reinforce disease management, and support rural development by bridging the technology gap. By bringing together innovation and on-the-ground requirements, AgriSphere encourages sustainable agriculture, improves food security, and supports the larger cause of digital inclusion in agriculture.
KEYWORDS
Publication Date
12/4/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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