Artificial Intelligence based Crop Recommendation System
M. Jagadeeswari, C. S. Manikandababu, S Kavya, R Prasanna, S Madumitha
Abstract
Agriculture is the main source of income for Indians. It plays an important role in the country's economy. But today, due to the migration of people from rural to urban areas, agriculture is hindered. Environmental monitoring isn't a perfect answer for increasing agricultural productivity. A multitude of variables contribute to even lower output. As a result, automation in agriculture must be applied to address these issues. Automated irrigation systems save farmers time, money and energy. Traditional agricultural irrigation techniques require manual intervention. With automatic irrigation technology, human intervention can be minimized Continuous crop sensing and monitoring is accomplished by converging sensors with the Internet of Things (IoT) and periodically informing farmers of crop growth, harvest time, and, increase crop yield and also ensure correct product delivery to consumers. In this project, we proposed a smart agricultural technique using IoT and prediction methodology is done using Artificial Intelligence (AI). The hardware includes many sensors like temperature, humidity, moisture, pH sensor and level sensor. Real time data are collected using sensors from the field and the training data are collected from the publicly available dataset and validation is done using real time dataset based on the condition of soil moisture, environment temperature, humidity and pH The proposed Multi-Layer Perceptron (MLP) algorithm identifies and implements the process to be carried out and predicts what type of crop can be grown in the soil.