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Big Data Mining and Analytics  2021, Vol. 4 Issue (3): 155-172    DOI: 10.26599/BDMA.2020.9020029
    
A Survey on Algorithms for Intelligent Computing and Smart City Applications
Zhao Tong1,*(),Feng Ye1(),Ming Yan2(),Hong Liu1(),Sunitha Basodi3()
College of Information Science and Engineering, Hunan Normal University, Changsha 410012, China
Agency for Science Technology and Research, Singapore 999002, Singapore
Department of Computer Science, Georgia State University, Atlanta 30302, GA, USA
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Abstract  

With the rapid development of human society, the urbanization of the world’s population is also progressing rapidly. Urbanization has brought many challenges and problems to the development of cities. For example, the urban population is under excessive pressure, various natural resources and energy are increasingly scarce, and environmental pollution is increasing, etc. However, the original urban model has to be changed to enable people to live in greener and more sustainable cities, thus providing them with a more convenient and comfortable living environment. The new urban framework, the smart city, provides excellent opportunities to meet these challenges, while solving urban problems at the same time. At this stage, many countries are actively responding to calls for smart city development plans. This paper investigates the current stage of the smart city. First, it introduces the background of smart city development and gives a brief definition of the concept of the smart city. Second, it describes the framework of a smart city in accordance with the given definition. Finally, various intelligent algorithms to make cities smarter, along with specific examples, are discussed and analyzed.



Key wordscyber physical systems      Internet of Things (IoT)      intelligent computing algorithm      Quality of Service (QoS)      smart city     
Received: 21 September 2020      Published: 20 May 2021
Fund:  National Natural Science Foundation of China(62072174);National Natural Science Foundation of Hunan Province, China(2020JJ5370);Scientific Research Fund of Hunan Provincial Education Department, China(17C0959)
Corresponding Authors: Zhao Tong     E-mail: tongzhao@hunnu.edu.cn;yfcloud@smail.hunnu.edu.cn;yan_ming@ihpc.a-star.edu.sg;liuhong@hunnu.edu.cn;sbasodi1@student.gsu.edu
About author: Zhao Tong received the PhD degree in computer science from Hunan University, China in 2014. He was a visiting scholar at the Georgia State University from 2017 to 2018. He is currently an associate professor at the College of Information Science and Engineering of Hunan Normal University. His research interests include modeling and scheduling for parallel and distributed computing systems. He has published more than 15 research papers in international conferences and journals, such as IEEE Transactions on Parallel and Distributed Systems, Information Sciences, Neural Computing and Applications, and Journal of Parallel and Distributed System. He is a member of CCF.|Feng Ye received the BE degree from Hunan Institute of Science and Technology, Yueyang, China in 2018. He is currently a master student at the College of Information Science and Engineering, Hunan Normal University, Changsha, China. His research interests include cloud computing, mobile edge computing, objective optimization, task scheduling, machine learning, and artificial intelligence.|Ming Yan received the PhD degree from Sichuan University, Chengdu, China in 2018. He was a visiting PhD at Georgia State University in 2018. He is currently a scientist at Agency for Science Technology and Research, Singapore. His research interests include neural networks and natural language processing. He has published several papers on ACL, KBS, etc.|Hong Liu received the MS degree from National University of Defense Technology, Changsha, China in 1988. He is currently a full professor at the College of Information Science and Engineering, Hunan Normal University. His research interests include artificial intelligence and distribute system. He has published more than 10 research papers in international conferences and journals, such as the Information Sciences, Neural Computing and Applications, Journal of Parallel and Distributed System, and Soft Computing.|Sunitha Basodi received the BS degree from the Jawaharlal Nehru Technological University, Hyderabad, India in 2010 and the PhD drgree in computer science from Georgia State University, Atlanta, USA in 2019. She has worked in Amazon Inc., India, as a software developer. Her research focuses on improving machine learning and deep learning methods, and their applications in neuroimaging, bioinformatics, and smart grid domains.
Cite this article:

Zhao Tong,Feng Ye,Ming Yan,Hong Liu,Sunitha Basodi. A Survey on Algorithms for Intelligent Computing and Smart City Applications. Big Data Mining and Analytics, 2021, 4(3): 155-172.

URL:

http://bigdata.tsinghuajournals.com/10.26599/BDMA.2020.9020029     OR     http://bigdata.tsinghuajournals.com/Y2021/V4/I3/155

Fig. 1 Number of smart cities under construction across the world.
Fig. 2 Smart city framework.
Fig. 3 Compound annual growth rates of smart city segments.
Fig. 4 Adaptive control traffic signal workflow.
Fig. 5 Framework of reinforcement learning.
Fig. 6 Energy management framework for smart cities.
Fig. 7 Structure of the CNN model.
Fig. 8 Smart healthcare framework based on edge computing.
Fig. 9 Smart agriculture framework based on edge computing.
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