Design And Development of Solar Powered Intelligent Weed Removal system for Sustainable Farming using ESP32

Abstract: Farming is the source of income for more than half of the Indian population. One of the serious issues in agriculture is the control of weeds growing among the plantation crops. At present weeds are being removed manually by farmers wherever possible, or weed killers/herbicides are being sprayed all over the field to keep them under control. This technique is very inefficient because chemicals are being sprayed on plantation crops also, which leads to, polluting the environment and health problems in humans. To avoid these consequences, a smart weed control system should be deployed. This project presents a solar-powered autonomous robotic system capable of detecting and mechanically removing weeds using edge-based TinyML inference on an ESP32-CAM module. The system captures field images, classifies them using a machine learning model trained via Edge Impulse, and activates a mechanical cutter upon weed detection. The integration of renewable solar energy enhances sustainability and field usability.

Keywords: Weed Detection, TinyML, Edge AI, Real-Time Image Classification, Autonomous Agricultural Robot.