The Development of a Prototype Solution for Detecting Wear and Tear in Pedestrian Crossings

被引:0
|
作者
Rosa, Goncalo J. M. [1 ]
Afonso, Joao M. S. [1 ]
Gaspar, Pedro D. [2 ,3 ]
Soares, Vasco N. G. J. [1 ,4 ,5 ]
Caldeira, Joao M. L. P. [1 ,4 ]
机构
[1] Polytech Inst Castelo Branco, Av Pedro Alvares Cabral 12, P-6000084 Castelo Branco, Portugal
[2] Univ Beira Interior, Dept Electromech Engn, Rua Marques d'Avila e Bolama, P-62001001 Covilha, Portugal
[3] Ctr Mech & Aerosp Sci & Technol C MAST, Rua Marques d'Avila e Bolama, P-62001001 Covilha, Portugal
[4] Inst Telecomunicacoes, Rua Marques d'Avila e Bolama, P-6201001 Covilha, Portugal
[5] AMA Agencia Modernizacao Adm, Rua Santa Marta 55, P-1150294 Lisbon, Portugal
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 15期
关键词
pedestrian crossings; smart cities; computer vision; convolutional neural networks; performance evaluation;
D O I
10.3390/app14156462
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Crosswalks play a fundamental role in road safety. However, over time, many suffer wear and tear that makes them difficult to see. This project presents a solution based on the use of computer vision techniques for identifying and classifying the level of wear on crosswalks. The proposed system uses a convolutional neural network (CNN) to analyze images of crosswalks, determining their wear status. The design includes a prototype system mounted on a vehicle, equipped with cameras and processing units to collect and analyze data in real time as the vehicle traverses traffic routes. The collected data are then transmitted to a web application for further analysis and reporting. The prototype was validated through extensive tests in a real urban environment, comparing its assessments with manual inspections conducted by experts. Results from these tests showed that the system could accurately classify crosswalk wear with a high degree of accuracy, demonstrating its potential for aiding maintenance authorities in efficiently prioritizing interventions.
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页数:28
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