Agricultural production monitoring platform based on cloud computing

Abstract

As a coastal state, agricultural instability reduces output in Tamil Nadu. Agricultural traits and features provide data that may be used to get insights into Agri-facts. With the advent of the information technology world, various highlights in agricultural sciences are being pushed to supply farmers with critical agricultural information. Machine Learning Techniques use data to build a well-defined model that assists us in making predictions. Crop forecasting, rotation, water requirements, fertilizer requirements, and crop protection are all hurdles that may be overcome. Because of the changing climatic components in the environment, it is vital to have an effective approach to promote crop growth and aid farmers in their management and output. This might assist prospective farmers in improving their farming practices. Data analytics provides the path for extracting valuable information from agricultural statistics. Crop data was evaluated, and crop recommendations were developed based on productivity and season.