Habeeb Ur. Rehman,
Mohammed Nouman,
Muhammed Thajuddin Sanad,
Rabeeh T. A.,
Sheik Rifaz Ali,
- Assistant Professor, Department of Computer Science Engineering, P. A. College of Engineering (PACE) Mangalore, Mangalore, Karnataka, India
- UG Scholar, Department of Computer Science and Engineering, P. A. College of Engineering (PACE) Mangalore, Mangalore, Karnataka, India
- UG Scholar, Department of Computer Science and Engineering, P. A. College of Engineering (PACE) Mangalore, Mangalore, Karnataka, India
- UG Scholar, Department of Computer Science and Engineering, P. A. College of Engineering (PACE) Mangalore, Mangalore, Karnataka, India
- UG Scholar, Department of Computer Science and Engineering, P. A. College of Engineering (PACE) Mangalore, Mangalore, Karnataka, India
Abstract
The Animal Intrusion Prevention System employs advanced YOLO v8 object detection technology to address human-wildlife conflicts, a growing concern due to human encroachment into natural habitats. Featuring a Raspberry Pi mounted on a rotating head for 360-degree surveillance, the system accurately identifies animals such as monkeys, elephants, and wild boars in real-time. Upon detection, it activates non-invasive light and sound deterrents to prevent wildlife intrusions, ensuring minimal harm to animals. Solar power integration enhances sustainability, enabling deployment in remote areas. Beyond immediate conflict mitigation, the system provides valuable data on wildlife behavior and intrusion patterns, supporting research and conservation efforts. By combining technological innovation with ecological awareness, the Animal Intrusion Prevention System aims to promote harmonious coexistence between humans and wildlife. This project represents a holistic approach to wildlife management, leveraging technology not only for human protection but also for the preservation and coexistence of diverse ecosystems and species.
Keywords: Yolo V8, Human-Wildlife Conflict, Raspberry Pi, Wildlife Deterrents, Ecological Conservation
[This article belongs to Journal of Artificial Intelligence Research & Advances (joaira)]
Habeeb Ur. Rehman, Mohammed Nouman, Muhammed Thajuddin Sanad, Rabeeh T. A., Sheik Rifaz Ali. Animal Intrusion Prevent System: Using YoloV8 and Raspberry Pi. Journal of Artificial Intelligence Research & Advances. 2024; 11(03):-.
Habeeb Ur. Rehman, Mohammed Nouman, Muhammed Thajuddin Sanad, Rabeeh T. A., Sheik Rifaz Ali. Animal Intrusion Prevent System: Using YoloV8 and Raspberry Pi. Journal of Artificial Intelligence Research & Advances. 2024; 11(03):-. Available from: https://journals.stmjournals.com/joaira/article=2024/view=177232
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Journal of Artificial Intelligence Research & Advances
| Volume | 11 |
| Issue | 03 |
| Received | 28/09/2024 |
| Accepted | 30/09/2024 |
| Published | 07/10/2024 |