Airep: Ai And Iot Based Animal Recognition And Repelling System For Smart Farming

Abstract

Agriculture automation has been on the rise leveraging, among others, Deep Neural Networks (DNN) and IoT for the
development and deployment of many controlling, monitoring and tracking applications at a fine-grained level. In this rapidly
evolving scenario, managing the relationship with the elements external to the agriculture ecosystem, such as wildlife, is a relevant
open issue. 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 and non-lethal 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 AI 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.