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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
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← Back to VOLUME 15, ISSUE 1, JANUARY 2026

WildGuard: A Smart Guardian for Wildlife Using YOLOv8 and Audio Classification

Mahalakshmi C V, Catherine Ananya M, Supriya L J, Supritha Jogin, Sushmitha S

DOI: 10.17148/IJARCCE.2026.15127

Abstract: WildGuard is an intelligent, real-time surveillance system designed to protect wildlife and forest ecosystems. It integrates state-of-the-art computer vision using YOLOv8 and audio classification based on MFCC features and machine learning classifiers to detect humans, vehicles, animals, and gunshot sounds from live camera and microphone feeds. The system automates threat detection, provides instant email alerts, and stores event evidence in a centralized database with a web-based dashboard for monitoring and analysis. This paper presents the system objectives, architecture, modules, algorithms, implementation details, and experimental outcomes.

Keywords: Wildlife Monitoring, YOLOv8, MFCC, Audio Classification, Real-Time Detection, Flask

How to Cite:

[1] Mahalakshmi C V, Catherine Ananya M, Supriya L J, Supritha Jogin, Sushmitha S, “WildGuard: A Smart Guardian for Wildlife Using YOLOv8 and Audio Classification,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2026.15127