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IOT based Crop Health Monitoring and Controlling Smart Agriculture System in Machine Learning
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M.Leeban Moses , S.Karthikeyan , P.Ramya , Tharun K T, Raahul Prasath P and Mounaguru P


85% of the population in my country, Ethiopia, where there are 94 million people, work in agriculture, which accounts for 45% of the country's GDP. Because traditional farming methods are insufficient to meet the country's growing demand, farmers are forced to use harmful pesticides more frequently, which harms the soil. This paper concentrates on emerging different automation practices like IoT, Wireless Communications, Machine learning, Artificial Intelligence, and Deep learning as part of the industry's technological evolution in order to Understand and predict crop performance under various environmental situations that will boost farm productivity.

Keywords— Soil monitoring, Humidity level, Temperature, Health monitoring, Machine Learning, Cloud Services.

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