IoT-Based Intelligent System for Internal Crack Detection in Building Blocks

Author:

Babu J. Chinna1,Kumar M. Sandeep2,Jayagopal Prabhu2ORCID,Sathishkumar V. E.3ORCID,Rajendran Sukumar2,Kumar Sanjeev4,Karthick Alagar5ORCID,Mahseena Akter Meem6ORCID

Affiliation:

1. Department of Electronics and Communications Engineering, Annamacharya Institute of Technology and Sciences, Rajampet, 516126 Andhra Pradesh, India

2. School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu 632014, India

3. Department of Industrial Engineering, Hanyang University, Seoul, Republic of Korea

4. Department of Civil Engineering, Graphic Era (Deemed to Be University), Bell Road, Clement Town, 248002 Dehradun, Uttarakhand, India

5. Renewable Energy Lab, Department of Electrical and Electronics Engineering, KPR Institute of Engineering and Technology, Coimbatore, 641407 Tamil Nadu, India

6. Department of Electrical and Electronic Engineering, Daffodil International University, Ashulia, Savar, Dhaka 1207, Bangladesh

Abstract

Cracks that are detected in concrete structures represent significant damage, and they can lead to a detrimental effect on the structure’s durability. Their identification in a timely manner can help ensure structural safety and guide in-depth maintenance operation. Automatic detection of such cracks has been proposed using internal crack detection utilizing ultrasonic sensors in concrete. Cracks within the concrete can be detected using ultrasonic sensors. In this investigation, we introduced an intelligent method that is aimed at developing a crack detection scheme using ultrasonic sensors. These ultrasonic sensors are used for the detection of cracks in buildings which cannot be seen with our naked eyes; they are capable of alerting authorities via SMS message and providing the cracks’ location via GSM and GPS modules. To monitor internal cracks in the concrete cubes and cylinders, the ultrasonic sensors can be fixed at the centre of the cube which will be used for interval crack monitoring based on crack detection technology. The grade of concrete used for testing is M25, and it is well mixed with the ingredients of cement, fine aggregate, coarse aggregate, and water. The concrete is placed in the cube moulds having the dimensions 150 mm × 150 mm × 150 mm . The cylinders used in the case of the experimental analysis are of the dimensions of 150 mm diameter and 300 mm height. These specimens are cast and kept in the curing tank for 28 days to attain the maximum strength. After completion of the curing period, the specimens were taken out from the tank and weighed. After this weighing process, the cubes and cylinders are about 8.884 kg and 13.399 kg, respectively. The information about the cracks can be displayed on the LCD, and also, the transmitted short message about the cracks can be exchanged between the devices using IoT.

Publisher

Hindawi Limited

Subject

General Materials Science

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2. Deepcrack: A Deep Learning Approach for Image-Based Crack Prediction using MobileNet And Transfer Learning;2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT);2024-01-04

3. Google Appstore Data Classification Using ML Based Naïve’s Bayes Algorithm: A Review;Studies in Computational Intelligence;2024

4. Image processing and Machine learning in Concrete Cube Crack detection;2023 International Conference on New Frontiers in Communication, Automation, Management and Security (ICCAMS);2023-10-27

5. Mathematical Modeling of Spherical Piezoelectric Elements of Ultrasonic Sensors for Diagnostics of Urban Infrastructure Components;Smart Technologies in Urban Engineering;2023

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