Smart Rice Yield Prediction Using IoT and AI

ABSTRACT: In today’s world, farming is becoming increasingly difficult due to unpredictable climate changes and limited access to real-time information. This project aims to support farmers by using modern technologies like the Internet of Things (IOT) and Artificial Intelligence (AI) to make rice farming smarter and more climate resilient. We have developed a system that can moniter key environmental factors such as soil Ph, temperature, humidity and water level suing sensors. These readings are collected and analyzed to help predict the yield of rice crops accurately. By combining sensors data with Ai based decision-making, our system not only helps in understanding the current conditions of the field but also guides farmers in making better farming decisions. This approach supports both kharif and rabi crops seasons, allowing farmers to adapt more easily to changing weather conditions and make the most out of their efforts. The overall goal is to make agriculture more efficient, climate-aware, and farmer friendly.

Authors

Publication Details

Journal
International Scientific Journal of Engineering and Management
Published
2025-04-22
DOI
https://doi.org/10.55041/isjem03020
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart Rice Yield Prediction Using IoT and AI

Ayush Dubey
International Scientific Journal of Engineering and Management
Smart Agriculture and AI
article

Smart Rice Yield Prediction Using IoT and AI

Ayush Dubey
article en

Abstract

ABSTRACT: In today’s world, farming is becoming increasingly difficult due to unpredictable climate changes and limited access to real-time information. This project aims to support farmers by using modern technologies like the Internet of Things (IOT) and Artificial Intelligence (AI) to make rice farming smarter and more climate resilient. We have developed a system that can moniter key environmental factors such as soil Ph, temperature, humidity and water level suing sensors. These readings are collected and analyzed to help predict the yield of rice crops accurately. By combining sensors data with Ai based decision-making, our system not only helps in understanding the current conditions of the field but also guides farmers in making better farming decisions. This approach supports both kharif and rabi crops seasons, allowing farmers to adapt more easily to changing weather conditions and make the most out of their efforts. The overall goal is to make agriculture more efficient, climate-aware, and farmer friendly.

International Scientific Journal of Engineering and ManagementVol. 04(04)
Openalex Percentile: Top 94%
Smart Agriculture and AI
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Smart Rice Yield Prediction Using IoT and AI — Ayush Dubey · International Scientific Journal of Engineering and Management (2025) | TGRS Research Map | TGRS