Automated Human - Wildlife Monitoring System using Deep Learning

INTRODUCTION

Human-wildlife conflict requires striking a balance between conservation of wild-animal and the needs of people who live with wildlife. Urbanization of our society has increased the personal interaction between human and wildlife. The problematic result is that our society is causing more problems from wildlife but becoming less concerned about the well-being of wildlife species. So, this project mainly aims forest border security which will consider well-being of both humans in the border region and wild animals. Here develops wildlife monitoring tool based on YOLOv3 and an animal repellent circuit. When the system detects the presence of animal it produces an alarm to inform the people and the forest rangers. So here further a system is designed which helps to repel animal back to the forest. Ultrasonic sensor is used for this purpose. We know that an ultrasonic sensor continuously produces ultrasonic wave. The frequency of ultrasonic wave is about 40 kHz, which is beyond the audible range of human being and animal can easily hear this sound. Which create a hostile and noisy environment for the animal and by hearing this noisy sound animal get repel back to the forest.