Application of Artificial Intelligence in Predictive Maintenance of Urban Infrastructure

Abstract

This paper explores the application of artificial intelligence in predictive maintenance of urban infrastructure, with a particular focus on bridges. A machine learning model was trained using simulated data to detect anomalies, analyzing key factors such as temperature, load, and vibrations. The evaluation demonstrated high model accuracy, highlighting its potential for practical implementation. The discussion addresses integration with IoT sensors and scalability in real-world scenarios, providing recommendations for further development. Challenges related to the availability of real-world data and the need for adaptable solutions are also analyzed, laying the groundwork for future research and practical applications.

Keywords: Urban infrastructure, machine learning, predictive maintenance, artificial intelligence, Internet of Things

Published on website: 25.11.2024

Attached files: estojanovic.pdf