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Smart city article details
| Title | The Development Of A Prototype Solution For Detecting Wear And Tear In Pedestrian Crossings |
|---|---|
| ID_Doc | 55289 |
| Authors | Rosa G.J.M.; Afonso J.M.S.; Gaspar P.D.; Soares V.N.G.J.; Caldeira J.M.L.P. |
| Year | 2024 |
| Published | Applied Sciences (Switzerland), 14, 15 |
| DOI | http://dx.doi.org/10.3390/app14156462 |
| Abstract | 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. © 2024 by the authors. |
| Author Keywords | computer vision; convolutional neural networks; pedestrian crossings; performance evaluation; smart cities |
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