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@article{175375,
        author = {Ms.G.Sasikala and N.Sowmiya and S.Subadharshini and S.Reshma},
        title = {Wildlife Defence System :Leveraging AI and IOT for Real-Time Detection and Conflict Mitigatiom},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {2905-2913},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175375},
        abstract = {Human-animal conflicts in forested areas are becoming a major concern, particularly as human settlements are increasingly encroaching upon wildlife habitats. The AI-driven Wildlife Proximity Alert System uses YOLO (You Only Look Once) technology to deliver a dynamic and effective conflict prevention solution to address this difficulty. Cutting-edge object detection technology called YOLO provides real-time tracking and identification of wildlife near populated areas. The system works by detecting specific animals, such as elephants and cows, through a combination of Python-based code and embedded hardware components, including a microcontroller, IR sensor, and buzzer. The IR sensor plays a critical role by detecting the presence of animals, while the YOLO technology continuously scans the environment for specific animals. Once an animal is detected, the system triggers an immediate alert, which activates the buzzer and informs humans of potential danger. The aim is to provide real-time alerts to prevent conflicts and reduce the likelihood of human injuries or harm to wildlife. In addition to these primary components, the system integrates an MQTT Alert System for efficient communication. MQTT (Message Queuing Telemetry Transport) is a lightweight messaging protocol that is ideal for sending real-time alerts over networks. With this integration, the system can send notifications to remote devices, such as mobile phones or centralized monitoring systems, ensuring that the right individuals or authorities are notified immediately when a wildlife threat is detected.},
        keywords = {Human-Animal conflict, AI-based detection, YOLO object detection, Real-time alerts, MQTT communication, Infrared (IR) sensor, Microcontroller integration, Wildlife monitoring, Sensor integration, Predictive analytics, Scalability, Remote deployment.},
        month = {April},
        }