Preventing Monkey Menace Using YOLO Based Object Detection Model
P.Rohit Reddy, Mrityunjay Kumar, Kajal Kumari, T. Prathima, Sugamya Katta · 2023
Monkey menace is a serious problem in many urban and rural areas, where monkeys cause damage to property, crops, and attack humans. YOLOv5 (You Only Look Once version 5) is a computer vision technique that can be used to detect monkeys in images and video frames, which can help in mitigating the monkey menace. YOLOv5 uses deep learning to detect objects in real-time, and it has achieved state-of-the-art results in various object detection tasks. In monkey detection, YOLOv5 can accurately detect and classify different types of monkeys such as Rhesus macaques, Bonnet macaques, and Langurs. The algorithm uses a pre-trained model that has been trained on a large dataset of images of different monkeys, and it can also be fine-tuned on a smaller dataset of specific monkeys to improve its performance. YOLOv5 performs monkey detection by dividing an image into grids and applying a convolutional neural network to each grid to detect the presence of a monkey. The algorithm then generates bounding boxes around the detected monkeys, and it can also classify the monkeys based on their species. After Detecting the Monkeys, it produces an alert message and alarm instantly.