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Article

Analyzing the Adoption Challenges of the Internet of Things (IoT) and Artificial Intelligence (AI) for Smart Cities in China

1
Department of Civil and Architectural Engineering, Qingdao University of Technology, Shandong 273400, China
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Building Information Technology Innovation Laboratory (BITI Lab), Solearth Architecture Research Center, Hong Kong 999077, China
3
Industrial Engineering and Manufacturing Systems, National Institute of Industrial Engineering, Mumbai 400087, India
4
School of Design and Architecture, Zhejiang University of Technology, Zhejiang 310023, China
*
Author to whom correspondence should be addressed.
Academic Editor: Fadi Al-Turjman
Sustainability 2021, 13(19), 10983; https://0-doi-org.brum.beds.ac.uk/10.3390/su131910983
Received: 10 August 2021 / Revised: 27 September 2021 / Accepted: 28 September 2021 / Published: 3 October 2021
Smart cities play a vital role in the growth of a nation. In recent years, several countries have made huge investments in developing smart cities to offer sustainable living. However, there are some challenges to overcome in smart city development, such as traffic and transportation management, energy and water distribution and management, air quality and waste management monitoring, etc. The capabilities of the Internet of Things (IoT) and artificial intelligence (AI) can help to achieve some goals of smart cities, and there are proven examples from some cities like Singapore, Copenhagen, etc. However, the adoption of AI and the IoT in developing countries has some challenges. The analysis of challenges hindering the adoption of AI and the IoT are very limited. This study aims to fill this research gap by analyzing the causal relationships among the challenges in smart city development, and contains several parts that conclude the previous scholars’ work, as well as independent research and investigation, such as data collection and analysis based on DEMATEL. In this paper, we have reviewed the literature to extract key challenges for the adoption of AI and the IoT. These helped us to proceed with the investigation and analyze the adoption status. Therefore, using the PRISMA method, 10 challenges were identified from the literature review. Subsequently, determination of the causal inter-relationships among the key challenges based on expert opinions using DEMATEL is performed. This study explored the driving and dependent power of the challenges, and causal relationships between the barriers were established. The results of the study indicated that “lack of infrastructure (C1)”, ”insufficient funds (C2)”, “cybersecurity risks (C3)”, and “lack of trust in AI, IoT” are the causal factors that are slowing down the adoption of AI and IoT in smart city development. The inter-relationships between the various challenges are presented using a network relationship map, cause–effect diagram. The study’s findings can help regulatory bodies, policymakers, and researchers to make better decisions to overcome the challenges for developing sustainable smart cities. View Full-Text
Keywords: smart cities; sustainability; Artificial Intelligence (AI); Internet of Things (IoT); expert opinions; DEMATEL; emerging economy smart cities; sustainability; Artificial Intelligence (AI); Internet of Things (IoT); expert opinions; DEMATEL; emerging economy
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MDPI and ACS Style

Wang, K.; Zhao, Y.; Gangadhari, R.K.; Li, Z. Analyzing the Adoption Challenges of the Internet of Things (IoT) and Artificial Intelligence (AI) for Smart Cities in China. Sustainability 2021, 13, 10983. https://0-doi-org.brum.beds.ac.uk/10.3390/su131910983

AMA Style

Wang K, Zhao Y, Gangadhari RK, Li Z. Analyzing the Adoption Challenges of the Internet of Things (IoT) and Artificial Intelligence (AI) for Smart Cities in China. Sustainability. 2021; 13(19):10983. https://0-doi-org.brum.beds.ac.uk/10.3390/su131910983

Chicago/Turabian Style

Wang, Ke, Yafei Zhao, Rajan K. Gangadhari, and Zhixing Li. 2021. "Analyzing the Adoption Challenges of the Internet of Things (IoT) and Artificial Intelligence (AI) for Smart Cities in China" Sustainability 13, no. 19: 10983. https://0-doi-org.brum.beds.ac.uk/10.3390/su131910983

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