Intelligent Surveillance and Protection System for Farmlands from Animals
Shashi Raj K, Basavaraj S. Sannakashappanavar, Monesh Kumar, Guruprasada Shridhar Hegde, MISHRA MEGHA · 2024
Agriculture is an important area for growing crops, as food is the main source of sustainability. India, with its vast agricultural area, has a wide variety of crops, from food grains to vegetables. However, few crops are destroyed by animal attacks, so a proper monitoring system is needed to protect the crops from animals. Crops are mainly damaged by animals such as buffalo, cattle, goats, birds, and wild elephants. This causes huge losses to farmers. The farmer cannot protect the crops if animals stay in the field for more than 24 hours. To address this issue, an animal detection system that detects the presence of animals has been developed. It provides the warning and redirects animals without harming them by using Machine learning and Image processing technique. The proposed system is deployed in the fields with a camera which continuously monitors. When an animal enters the field, it receives a short urge, which only threatens the animal to leave the field but doesn't harm the animal by using a laser beam instead of a fence that can harm the animal. In addition, the animal is redirected by playing sound of certain frequency and the same is intimated through SMS for quick notification to farmer. Light-dependent resistance sensors (LDRs) are often used for distance measurement. This system is also excellent at detection of various obstacles (wood, plastic, mirrors, plywood, concrete, etc.). The minimum obstacle size that the system can detect is about 5cmx5cm. The proposed developed model is a lab scale and can be scaled for further use. The overall safety of the crop was ensured from the animals by this system and thus protects the losses that occurred to farmers. To detect and monitor the movements of animals the developed system uses laser beam. Further, this model ensures the complete safety of the crop from the animals and prevents the loss of the farmer.