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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM55106

Advanced Defect Detection System

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM55106

Volume:

9 |

12 |

Dec 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM55106

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.

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Authors

PG

Prakruthi GR1

AP

A Prajwal2

KKR

Kiran Kumar R3

DK

Dhiraj K4

SS

Suraj S5

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Abstract

The Bridge and Boat Monitoring System is intended to improve safety and operational efficiency of both bridges and waterways, through two integrated modules: the Bridge and the Boat. It is a Bridge Module made by Arduino, equipped with IR sensors for detecting any vehicle approaching, a load cell to monitor weight, a water level sensor and motorized gates to gain access under control. The Boat Module, which is also Arduino-based, contains a wet sensor and a tilt sensor (ADXL345) to detect water entry and ensure stability. For crack detection and structural health assessment of the bridge, the system utilizes YOLO v5, which is a state-of-the-art deep learning algorithm that can accurately and timely identify problems. Zigbee technology provides seamless wireless communication, allowing for real time data sharing to support proactive maintenance and informed decision-making.

KEYWORDS

YOLOv5 Object Detection Model YOLOv5 Object Detection Model YOLOv5 Object Detection Model Severity and Risk Analysis Telegram Bot Alert System Annotated Image Generation Defect Classification Detection Count Analysis Automated PDF Report Generation Detection Count Analysis

Cite This Article

Prakruthi GR1, A Prajwal2, Kiran Kumar R3, Dhiraj K4, Suraj S5, "Advanced Defect Detection System," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 12, Dec 2025. https://doi.org/10.55041/IJSREM55106

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Publication Date

12/11/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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0

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2

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5

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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