• Teja Kumar M S
• Sandeep vasan S
• Yeshwanth R
• Parthiban M A
• E Kamalanaban

Crop raiding by animals has become one of the most common human animal disputes as a result of human encroachment of wildlife habitats and deforestation. Wild animals can cause significant damage to agricultural crops and attack farmers working in the field. Farmers suffer huge crop loss due to crop raiding by wild animal like elephants, wild boar and deer. One of the main concerns of today's farmers is protecting crops from wild animals’ attacks. There are different traditional approaches to address this problem which can be lethal (e.g., shooting, trapping) and non-lethal (e.g., scarecrow, chemical repellents, organic substances, mesh, or electric fences).Farmers has tried many ways for preventing animals raid from lighting fire crackers to maintain a watch on the field through the night but none of these were effective. Nevertheless, some of the traditional methods have environmental pollution effects on both humans and ungulates, while others are very expensive with high maintenance costs, with limited reliability and limited effectiveness. In this project, we develop a system, that combines Computer Vision using DCNN for detecting and recognizing animal species, and specific ultrasound emission (i.e., different for each species) for repelling them. The edge computing device activates the camera, then executes its DCNN software to identify the target, and if an animal is detected, it sends back a message to the Animal Repelling Module including the type of ultrasound to be generated according to the category of the animal.

Animal Recognition, Repellent, Artificial Intelligence, Edge Computing, Animal Detection, Deep Learning, DCNN

"Trend of Data Endangered species using Logistic Regression Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 2, page no.b467-b473, February-2024, Available :http://www.jetir.org/papers/JETIR2402153.pdf

"Trend of Data Endangered species using Logistic Regression Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 2, page no. ppb467-b473, February-2024, Available at : http://www.jetir.org/papers/JETIR2402153.pdf