Automated Crop Field Surveillance using Computer Vision
Tejas Atul Khare, Anuradha C. Phadke

TL;DR
This paper proposes an automated crop field surveillance system using computer vision to enhance security and reduce crop losses due to trespassing animals, offering a cost-effective alternative to traditional fencing.
Contribution
It introduces a novel computer vision-based approach for crop field monitoring that automates security and addresses limitations of physical barriers.
Findings
Reduces crop damage caused by trespassing animals.
Automates crop field security with computer vision techniques.
Potentially lowers costs compared to traditional fencing methods.
Abstract
Artificial Intelligence is everywhere today. But unfortunately, Agriculture has not been able to get that much attention from Artificial Intelligence (AI). A lack of automation persists in the agriculture industry. For over many years, farmers and crop field owners have been facing a problem of trespassing of wild animals for which no feasible solution has been provided. Installing a fence or barrier like structure is neither feasible nor efficient due to the large areas covered by the fields. Also, if the landowner can afford to build a wall or barrier, government policies for building walls are often very irksome. The paper intends to give a simple intelligible solution to the problem with Automated Crop Field Surveillance using Computer Vision. The solution will significantly reduce the cost of crops destroyed annually and completely automate the security of the field.
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