Cotton Pest Trap Using Machine Learning Models

One of the most important fiber and cash crops of India is cotton, which plays a dominant role in the industrial and agricultural economy of the country. The basic raw material for the cotton industry is the cotton fiber. However, the cotton cultivation globally faces severe pest challenges, causing significant yield losses annually. This work proposes an innovative solution of integrating advanced technology with ecoconsciousness to combat cotton pests effectively. Utilizing YOLOv8 machine learning and IoT devices like ESP32-CAM, our system enables real- time pest identification and targeted trapping. Smart traps, activated upon detection, reduce reliance on chemical pesticides. Extensive field testing and data augmentation demonstrate the model's accuracy and adaptability. Early pest detection and precise management promise increased yields and profitability while advocating sustainable farming practices. This work serves as a pioneering example of technology- driven ecological solutions, promoting economic stability and environmental preservation.