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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM44600
Volume:
9 |
4 |
Apr 2025
Pages:
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.
This paper presents HomeSafe, an AI-driven system for automated housing inspection using Machine Learning-based anomaly detection. The system detects structural cracks from images and estimates their severity, providing detailed reports for decision-making. A MobileNetV2-based CNN model is fine-tuned for crack detection, achieving high accuracy on a benchmark dataset. The system further estimates crack width and dimen sions using image processing techniques. A web-based interface (Streamlit) is developed for easy image uploads and report generation. The project aims to assist engineers, homeowners, and real estate professionals in conducting automated building inspections.
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Publication Date
4/15/2025
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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