The IoT-based real-time image processing for animal recognition and classification using deep convolutional neural network (DCNN)

Abstract

Human-Wildlife Conflict (HWC) is one of the crucial threats in Valparai and the surrounding region in Anamalai Tiger Reserves (ATR), Tamil Nadu, India. In this work, we projected an automatic unsupervised module for animal detection and discrimination from the animal image obtained from the camera. The captured animal images are stored in .jpeg format and are sent to the base station via Radio Frequency (RF) network. We have implemented the Deep Convolutional Neural Network (DCNN) for performing the task of feature extraction and classification. Once an animal is identified, this system will send an alert message through the Global System for Mobile Communication (GSM) to the mobile numbers of Ranger, Local people, and FM/Radio channels stored in the system. Here, the Internet of Things (IoT) plays a significant role where the results will be fed into a web page so forest officials can use this information whenever needed. This system will help to save people and wildlife.