Recommendation of Crops and Fertilizer, Detection of Crop Weed, Pest and Diseases using Machine Learning

摘要

The term “smart farming” refers to the management of farms using contemporary information and communication technologies to improve product quality and quantity while diminishing the requirement of human labor and the possibility of undesirable results and loss of time and cost. Modern farmers are equipped with various technologies, including software, sensors, robotics, and data analytics. The farmers can use these to make farming a data-driven process. Conventional farming practices involve poor analysis, heavy labor, and time and financial waste. Therefore, we suggest a system that would assist farmers in combining their current farming practices with cutting-edge technologies like deep learning, machine learning, and remote sensing built using an open technology stack of Angular for the frontend, Flask for the backend, and MySQL and Google Earth for the database. Our application guides the farmers by recommending the best crop to grow and fertilizer to use using machine learning techniques, detects pests, weeds, and crop diseases using deep learning techniques, performs remote sensing analysis using GEE by obtaining the area name, and provides weather details by obtaining the city name.