Abstract
Pavement Management Systems (PMS) offers a systematic collection, storage, analysis, and modeling of road condition data to optimize resources across a road network. Adding artificial intelligence (AI) and augmented reality (AR) to PMS could improve their technical or visual aspects. This paper tries to identify a method to improve the understanding of the consequences of the city council’s decisions in the urban pavement management system field. This paper establishes the potential of AR. It provides future maintenance and rehabilitation (M&R) actions needed based on the recommendation of the future distress in the study area. The road cracks are discovered through technical analysis, and a CityEngine model is established based on the PMS results. Additionally, in terms of visualization, this paper’s unique feature delivers the result as an AR experience. Applying the Unity game engine and importing the built CityEngine model and the embedded textures as input empowered us to provide a dynamic product in terms of data and analysis and a real-time Decision Support System (DSS) for the final users. This paper concludes that researchers need many different modules to design and implement an efficient PMS to move toward a smart PMS. The smart city concept is meaningless without a tight collaboration between all distinctive parts of each urban infrastructure management system. Additionally, this paper attempts to provide answers for researchers and an outlook for future research, the development of the proposed method, and its application in other fields
Subject
Building and Construction,Civil and Structural Engineering,Architecture
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