Smart Autonomous Agriculture Robot for Multipurpose Farming Application

摘要

Addressing the complexities of real-time collision-free route tracking for mobile robots operating in expansive and dynamic environments is paramount, particularly in the context of agriculture, a vital revenue source for India. Variables such as disease, insect infestations, and sudden climate fluctuations contribute to bacterial and fungal infections in crops. Early detection of these ailments is crucial for effective mitigation. The Agritech robot operates within this dynamic agricultural landscape, employing a sophisticated system to identify and address tomato plant diseases. Utilizing a convolutional neural network (CNN) for feature extraction and image classification, the robot traverses the agricultural terrain, capturing and categorizing plant images into healthy and unhealthy states. Upon detection of disease, the robot autonomously activates a pesticide sprayer, targeting infected plants with precision. The accompanying application facilitates the identification of eight prevalent tomato plant diseases, including Bacterial Blight, Leaf Spot, Anthracnose, Spider Mites, Yellow Leaf Curl, Leaf Mould, and Mosaic Virus. By integrating advanced technology with agricultural practices, autonomous robots mitigate the risks associated with human error, offering a promising solution for sustainable farming practices.