Integrated Wildlife Monitoring System for Real-Time Anti-Poaching and Conservation

To develop a wildlife monitoring system for anti poaching and conservation using YOLOv8 (You Only Look Once) with CSPDarknet (Cross Stage Partial Darknet) Backbone for real time object detection to identify and classify humans, animals from live image feeds which helps in detecting poaching activities. The system integrates various environmental sensors that act as transmitter side includes temperature, flame and acoustic sensor to monitor key changes that indicate forest fire. These sensors are connected through the LoRa (Long Range) network (Up To 10kms areas with clear line of sight) which efficiently transmits data to the central monitoring unit(here CMU Central Monitoring Unit refers to the forest ranger) that refers to a receiver module. In addition, the system comprises DFRobot Mini Player to trigger natural warning calls (Vocalizations that are produced by animals to alert their group and coordinate groups that are essential part of animal communication and survival strategy) based on the detected data to prompt animals not to be driven out of forest. Thus contributing environmental sustainability and habitat suitability for many species.