CROP MONITORING WITH AI BASED AUTONOMOUS FARM ROVER

The land of India is home to 1.4 billion people. The agricultural industry always addresses the food demand of such an enormously increasing population. India is the agricultural powerhouse of the world. However, the erratic weather and unfavorable environmental conditions lead to myriads of crop diseases. The traditional agricaltural methods used to produce the yield make it challenging to keep track of the crops and prevent diseases. It can lead to a compromise in the food security of the Indian population. Hence, deploying a plant discase detection system with a surveillance system can enhance crop productivity by improving efficiency with minimal human intervention and assistance. This paper talks in depth about the model under development which monitors plant growth and detects any diseases at the carly stages of crop evolvement. The pre-trained model uses a Line Tracking algorithm to move around the farm to inspect every crop in detail. The pictures of the crops are taken and stored for monitoring and analyties of plant health to achieve real-time detection and information. The Convolutional Neural Networks and Transfer Leaming technique help scrutinize images for discases. A positive response to the presence of any disease outputs the name of the blight and immediate effective treatment for cure. The growth and development trends of healthy plants help to identify the challenges that occur during the exact crop yield for the next season of the plantation. Such techniques help refine agricultural practices and provide many opportunities for diverse innovations with effective and potential solutions.

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