An IOT-Based Smart Tractor Solution For Sustainable Crop Protection

Abstract

India is an agrarian economy with almost three-fourths of its population being involved in agriculture. Farmers usually grow several crops based on climatic conditions and local resources. But technical know-how and advanced technological support are needed to obtain high yield and good-quality products. One of the biggest challenges in agriculture is the early identification and treatment of crop diseases, which can largely affect productivity and post-harvest quality.
Crop diseases are usually the result of pathogens, and signs usually manifest on the leaves, stems, or branches. The identification and diagnosis of these diseases early on are important for efficient crop management. This can be done by taking pictures of the plants with a camera and interpreting them using machine learning algorithms. The system can identify the disease, find the infected location, recommend valid remedies, and trigger a pesticide sprayer that targets only the infected area. Such image-based disease detection systems have the ability to work in real time so that farmers could act immediately and avoid further spread of infections.
This intelligent, mechanized solution not only enhances efficiency in disease detection and treatment but also encourages safer agriculture, reduces the use of chemicals, and eventually increases crop yield and farmer revenue. Furthermore, the infusion of technology into conventional farming techniques bridges the gap between rural and contemporary agriculture, opening the way to sustainable and data- driven agriculture.