AI-Equipped IoT Applications in High-Tech Agriculture Using Machine Learning
M. V. Bazylev M. V., A. V. Senthil Kumar, Priyanka Sharma, Sarabjeet Kaur, Omar S. Saleh, H. R. Chennamma, Ankita Chaturvedi
Abstract
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. Farmers suffer huge crop loss due to crop raiding by wild animals like elephants, wild boar, and deer. One of the main concerns of today's farmers is protecting crops from wild animal attacks. 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 chapter, the authors develop a system that combines computer vision using DCNN for detecting and recognizing animal species and specific ultrasound emission 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.