Abstract

GONCALVES, Miguel et al. Prototype Solution for Detecting and Signaling Road Pavement Defects Based on Computer Vision Techniques. RISTI [online]. 2023, n.52, pp.25-44.  Epub Dec 31, 2023. ISSN 1646-9895.  https://doi.org/10.17013/risti.52.25-44.

This article presents a functional prototype to evaluate and validate the use of computer vision techniques to identify road pavement defects in the context of a smart city. A study is carried out to evaluate the performance of three convolutional neural networks, YoloV4-Tiny, SSD MobileNet and RetinaNet, applied to this scenario. Based on the results observed, the proposal and implementation process of the prototype is described, which is based on a Raspberry Pi 4 platform. The prototype is subject to validation and functional tests. Compared to the method currently used by Infraestruturas de Portugal to identify pavement defects, this approach is more agile, effective, and efficient, contributing to their rapid detection and notification.

Keywords : Smart Cities; Road Pavement; Defect Detection; Computer Vision; Convolutional Neural Networks; Object Detection; Prototype.

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