Crop Defect Detection Robot with Automatic Pesticide Spraying System
Prof. Karuna Mahajan1, Mr. Tejas Bijewar2, Miss. Rutuja Dhope3, Mr. Aditya Gaikwad4,
Mr. Harshad Hebule5
1Prof. Karuna Mahajan, Zeal College of Engineering and Research, Pune
2Tejas Bijewar, Zeal College of Engineering and Research, Pune
3Rutuja Dhope, Zeal College of Engineering and Research, Pune
4Aditya Gaikwad, Zeal College of Engineering and Research, Pune
5Harshad Hebule, Zeal College of Engineering and Research, Pune
Abstract
The goal of the research paper "Crop Defect Detection Robot with Automatic Pesticide Spraying System" is to create an intelligent agricultural robot for smart farming applications by combining image processing, artificial intelligence, and the Internet of Things. Manual labor, excessive chemical use, and direct human exposure to hazardous materials are all part of traditional pesticide spraying techniques. These traditional methods are labor-intensive, ineffective, and frequently cause environmental harm because of their uncontrolled spraying. An ESP32-CAM module serves as the central vision unit in the suggested system, which takes real-time pictures of crop leaves. It detects crop diseases such as fungal infections, brown spotting, or yellow leaves through the use of image
processing techniques based on artificial intelligence.Upon detecting any defect in the crops, the robot automatically triggers its pesticide spraying technique, which is applied selectively to the infected part.Farmers can check on the health of their crops and the work being done by the robot via a mobile or web application that connects with the system using its Wi-Fi capabilities, due to the incorporation of the IoT platform. With this innovative approach, costs are reduced, less manual labor is required, less pesticide is used, and sustainable practices are encouraged. The paper demonstrates how modern automation is revolutionizing traditional agriculture through smart precision agriculture utilizing low-cost embedded devices, artificial intelligence, and IoT technologies.
Keywords: Internet of Things (IoT), ESP32-CAM, Smart Agriculture, Image Processing, Artificial Intelligence, Crop Disease Detection, Automatic Pesticide Spraying, Sustainable Farming.
