Real Time Crop Prediction and Fertilizer Recommendations System using Machine Learning and IOT

TITLE	Real Time Crop Prediction and Fertilizer Recommendations System using Machine Learning and IOT
ABSTRACT	Lack of appropriate facilities to test soil and lack of agronomic recommendations often make farmers to find it difficult to choose on the right crop and fertilizer to use. Old practices of measuring soil quality and level of fertilizers needed are time-consuming and expensive. The present paper suggests a real-time system capable of predicting crops and calculating a fertilizer recommendation with the use of Internet of Things (IoT) devices and Machine Learning (ML) algorithms. The system uses sensors to gather soil and other environmental information that is further processed with models like Naive Bayes and random forest that predict optimal crop. It also prescribes fertilizers that suit the soil nutrient balance. The system showed more than 80% real-life prediction accuracy aspiring to assist farmers in making data-backed decision making, lower the input costs, and increase agricultural output.
AUTHOR	Prasad S Department of Masters of Computer Applications, CMR Institute of Technology, Bengaluru, India
PUBLICATION DATE	2025-09-10
VOLUME	12
DOI	DOI:10.15680/IJARETY.2025.1204086
PDF	86_Real Time Crop Prediction and Fertilizer Recommendations System using Machine Learning and IOT.pdf
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