Year: 2025
Type: article
Abstract: Maintaining street infrastructure is extremely important in ensuring security and economic efficiency in modern transportation systems. Road surface damage and commuter risks such as cracks, pot holes, and road quality wear and tear. In this article, we explore the extended AI methods for KIS Intelligence detection, including road damage automation and cutting-edge object detection models focused on Yolov8. Yolov8 combines high accuracy and arithmetic efficiency to provide excellent damage detection performance. This study provides an overview of Yolov8 features and shows an application in real street assessment tasks and how its deployment leads to more intelligent and effective infrastructure management.
Authors: Mathan Kumar M, Gokilapriya S
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4408930336