Proceedings of the International Conference on Responsible, Risk-aware, and Regulated AI (RRRAI 2026)

International Conference on Responsible, Risk-aware, and Regulated AI (RRRAI 2026)

📍Pune, Maharashtra, India🗓️ 3-4 April 2026
<Previous Article In Volume
Next Article In Volume>

AI-Driven Concrete Quality: Automated Failure Analysis for Sustainable Construction

Authors
M. S. Patil1, *, R. B. Ghongade2, H. B. Dhonde3
1Assistant Professor, Indira College of Engineering and Management and Research Scholar at Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, India
2Professor, E&Tc Bharati Vidyapeeth(Deemed to be University) College of Engineering, Pune, India
3Director, C-Probe Technologies Pvt. Ltd., Pune, India
*Corresponding author. Email: meenakshi.madgunaki@indiraicem.ac.in
Corresponding Author
M. S. Patil
Available Online 14 July 2026.
DOI
10.2991/978-94-6239-723-1_36How to use a DOI?
Keywords
Concrete cube; Image processing; Machine learning; YOLOv10; sustainable practices; failure modes
Abstract

This research aims to develop a system which is used to identify the concrete cube failure mode as acceptable or non acceptable. In the given system we have used image processing algorithm to detect the cracks on concrete cube and machine learning algorithms like YOLO version 10 for image cropping, an-note and to analyse the cube images which are collected from lab experiments, on construction sites and some are augmented.

After implementing the system it is observed that the system above to detect the crack patterns and 90% accuracy in classifying the cube under acceptable and non acceptable category this reduces significantly the human error in classifying the cubes. Due to this f concrete evaluation become easier and faster and also this reduces the material waste and which in turn support sustainable construction practices. The future work includes increasing the dataset for more validity and developing a mobile application to make the process faster and user friendly.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the International Conference on Responsible, Risk-aware, and Regulated AI (RRRAI 2026)
Series
Advances in Intelligent Systems Research
Publication Date
14 July 2026
ISBN
978-94-6239-723-1
ISSN
1951-6851
DOI
10.2991/978-94-6239-723-1_36How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - M. S. Patil
AU  - R. B. Ghongade
AU  - H. B. Dhonde
PY  - 2026
DA  - 2026/07/14
TI  - AI-Driven Concrete Quality: Automated Failure Analysis for Sustainable Construction
BT  - Proceedings of the International Conference on Responsible, Risk-aware, and Regulated AI (RRRAI 2026)
PB  - Atlantis Press
SP  - 397
EP  - 411
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-723-1_36
DO  - 10.2991/978-94-6239-723-1_36
ID  - Patil2026
ER  -