IOT Based Smart Agriculture Management System using Machine Learning Classification Algorithms - Ashok Tatapudi, P. Suresh Varma (International Journal of Advanced Science and Technology, 2020)
India being a horticultural nation, the most piece of economy is relies upon yield development. Farming, is to a great extent relies upon downpour water, and furthermore relies upon differing soil boundaries to be specific nitrogen, phosphorous, potassium and climate viewpoints like temperature, precipitation and so forth. The innovative development in agribusiness will expand the harvest efficiency. Remote detecting frameworks like IOT frameworks are by and large more generally utilized in savvy cultivating frame works, these frameworks produce liberal measure of information. AI is a rising examination recorded to anticipate the yield dependent on the examples of the information. The proposed framework will coordinate the IOT sensors like Ph., Moisture, Rainfall, Temperature and Humidity sensors watch the information from those sensors and applying AI calculations: Logistic Regression, Decision Trees. An expectation of most appropriate harvests concurring the current ecological is made. This work gives a superior expectation for the ranchers to plant which sort of yields to their homestead field dependent on above notice boundaries to improve the profitability of Smart Farming.