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Stream/Area:
-
Subject:
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Paper ID:
IJSREM65018
Volume:
10 |
6 |
Jun 2026
Pages:
1-7
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 Electronics
Walchand College of Engineering
Department of Electronics
Walchand College of Engineering
This paper presents an AI-based animal detection and classification system designed for real-time monitoring appli-cations. The proposed system utilizes Raspberry Pi 5 integrated with a camera module, microphone sensor, PIR motion sensor, and buzzer for detecting and classifying wild, domestic, and farm animals. Image classification is performed using CNN and MobileNetV2 models, while audio analysis is carried out using YAMNet and MFCC feature extraction techniques. A custom dataset of animal images and sounds was used for training and testing. Experimental results demonstrated an overall classifi-cation accuracy of 83.33%, with successful real-time detection and alert generation. The developed system provides a low-cost, energy-efficient, and intelligent solution suitable for wildlife monitoring, smart agriculture, and rural safety applications.
KEYWORDS
An AI-based animal detection and classification system was successfully developed using Raspberry Pi 5. The proposed system combines image processing, audio analysis, motion sensing, and deep learning techniques to perform real-time animal monitoring. Experimental testing achieved an overall classification accuracy of 83.33%, demonstrating the effective-ness of the proposed approach. The developed system provides a low-cost, energy-efficient, and intelligent solution suitable for wildlife monitoring, smart agriculture, and rural safety applications.
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Publication Date
6/16/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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