Published Paper Details:

Wild animals become more aggressive when wounded because they're scared and confused and may think you're trying to capitalize on their vulnerable state. They're more likely to lash out and bite or scratch you than to accept your help. To address this, our project proposes an alerting system using YOLOv3, a real- time object detection algorithm based on deep convolutional neural networks, to classify and monitor animals that are hurt in Zoo or forests. This algorithm enables efficient identification and tracking of animals, aiding safeguarding wildlife observers and ensuring the preservation of wildlife in their natural habitats.By this wildlife monitoring robotic car using IOT, wildlife observers may get up and personal with wild creatures. An ESP32 is used in this system. The system receives these orders using a Wi-Fi module. We can capture the images of the wildlife continuously. And able to detect the wildlife.We are using the MLX9061an infrared thermometer designed for non-contact temperature sensing to measure the temperature of the animals and an ultrasonic non-contact type of sensor used to measure a wildlife's distance.