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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63987
Volume:
10 |
5 |
May 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of CSE(Artifitical Intelligence And Data Sceience)
Shree Siddheshwar Women's College of Engineering, Solapur
Department of CSE(Artifitical Intelligence And Data Sceience)
Shree Siddheshwar Women's College of Engineering, Solapur
Department of CSE(Artifitical Intelligence And Data Sceience)
Shree Siddheshwar Women's College of Engineering, Solapur
Human-wildlife conflict has become a major issue in areas located near forests and agricultural lands. Wild animals entering villages, farms, and highways can cause damage to property and pose risks to human life. Traditional monitoring methods require continuous human supervision and are often inefficient. This research paper presents a Smart Wildlife Protection System that uses Artificial Intelligence and computer vision for real-time animal detection and alert generation. The system employs the YOLOv8 object detection model integrated with Python and OpenCV to identify animals from live camera footage. Once an animal is detected, the system generates an immediate alert through a buzzer or notification, helping people take preventive action. The proposed solution improves wildlife monitoring, reduces human effort, and provides a cost-effective way to minimize human-animal conflict. Experimental results show that the system performs effectively in real-time detection with good accuracy.
KEYWORDS
The Smart Wildlife Protection System is an intelligent AI-based solution designed to reduce human-animal conflict by detecting animals in real time and generating immediate alerts. By using YOLOv8, Python, and OpenCV, the system provides accurate animal detection with improved speed and efficiency. The project demonstrates that Artificial Intelligence can play an important role in wildlife monitoring and public safety. It offers a practical and cost-effective solution for protecting people, crops, and property in areas affected by wildlife movement.
1. Research papers on AI-based object detection 2. YOLOv8 documentation 3. OpenCV official documentation 4. Wildlife monitoring studies using computer vision 5. Python machine learning libraries documentation Faster detection response Reduced false alarms Improved recognition accuracy Better performance in multiple scenarios However, performance may reduce in poor lighting conditions or when animals are partially hidden.
Publication Date
5/25/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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