Harnessing the Power of Digital Twin Technologies for Smart Cities: Pioneering Real-Time Urban Management, Predictive Maintenance, and Sustainable Development Strategies
Harnessing the Power of Digital Twin Technologies for Smart Cities: Pioneering Real-Time Urban Management, Predictive Maintenance, and Sustainable Development Strategies
Author(s): Gheorghe H. Popescu, Miloš Poliak, Cristian Florin Ciurlău, Nikola Ćurčić, Alexandru BogdanSubject(s): Information Architecture, Electronic information storage and retrieval, Rural and urban sociology, Sociology of Culture, ICT Information and Communications Technologies, Socio-Economic Research
Published by: Addleton Academic Publishers
Keywords: digital twin technology; smart cities; predictive maintenance; sustainable development; resource optimization; urban management; real-time data integration;
Summary/Abstract: This study focuses on the use of digital twin (DT) technologies in the development of smart cities, which is specifically related to predictive maintenance, resource use, and sustainability. This integrates real-time data, predictive analytics, and simulation models to develop better management and integration of urban systems. The application of digital twins enables the urban challenges of infrastructure underperformance, overconsumption of resources, and environmental durability to be addressed. The research explains how using predictive maintenance through digital twins will reduce the overall time the infrastructure is out of work and the costs related to it. The paper makes practical suggestions as well, such as creating proper data link infrastructures, developing PPP projects, and making training and skill development activities a major focus. This paper argues that digital twins should be placed at the heart of smart city projects for the reason that they provide the best tools for city management, city maintenance, and even resource optimization during future growth.
Journal: Journal of Self-Governance and Management Economics
- Issue Year: 11/2023
- Issue No: 3
- Page Range: 42-69
- Page Count: 28
- Language: English
- Content File-PDF