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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM40582
Volume:
9 |
1 |
Jan 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 faces challenges like unpredictable weather, resource scarcity, and inefficient practices. Agripulse addresses these issues by integrating Machine Learning (ML) and IoT to develop a smart farming solution. IoT sensors enable real-time monitoring of soil, crops, and environment, while ML algorithms optimize irrigation, fertilizer use, and pest control. The platform provides cost-effective, data-driven insights, empowering farmers to boost productivity and conserve resources. With edge computing and cloud integration, it ensures reliable performance even in areas with limited connectivity. Agripulse promotes sustainable, eco-friendly farming by transforming traditional practices into efficient, automated systems, contributing to global food security and agricultural innovation.
KEYWORDS
Publication Date
5/23/2025
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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