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Frontiers of Engineering Management    2019, Vol. 6 Issue (4) : 485-502     https://doi.org/10.1007/s42524-019-0057-9
RESEARCH ARTICLE
The development trend and practical innovation of smart cities under the integration of new technologies
Xiaohong CHEN()
Institute of Big Data and Internet Innovation, Hunan University of Technology and Business, Changsha 410205, China; Business School, Central South University, Changsha 410083, China
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Abstract

Smart cities have rapidly developed in the context of the integration of new digital technologies such as big data, Internet of Things, artificial intelligence, blockchains, and virtual reality. These cities have conducted practical innovations and typical cases in many sectors, such as in government, transportation, environmental protection, energy, medical care, and logistics, and have produced many social, economic, and ecological benefits. However, there are still some problems that continue to hinder the construction of smart cities. This paper examines such problems in depth and proposes some relevant countermeasures and suggestions.

Keywords new technology integration      smart city      big data      practical innovation     
最新录用日期:    在线预览日期:    发布日期: 2019-12-05
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引用本文:   
Xiaohong CHEN. The development trend and practical innovation of smart cities under the integration of new technologies[J]. Front. Eng, 2019, 6(4): 485-502.
网址:  
https://journal.hep.com.cn/fem/EN/10.1007/s42524-019-0057-9     OR     https://journal.hep.com.cn/fem/EN/Y2019/V6/I4/485
Fig.1  “2N41” conceptual framework of smart cities.
Fig.2  Overall framework of the construction of a smart city under the integration of new technologies.
Fig.3  Overall trend of smart city development.
Fig.4  Ping An smart government solution.
Fig.5  Operation process of smart city construction based on open data (source: Fudan University digital and mobile governance laboratory).
Fig.6  Spatial traceability analysis of potential sources of PM2.5 in the Chang-Zhu-Tan urban agglomeration.
Fig.7  Temporal variation of four major heavy metal contents in Xiangjiang River (Each line represents a city in Hunan. CS, ZZ, XT, YY, HY, CZ, YZ and LD means Changsha, Zhuzhou, Xiangtan, Yueyang, Hengyang, Chenzhou, Yongzhou, and Loudi, respectively.).
Fig.8  Smart city strategy index.
1 V Albino, U Berardi, R M Dangelico (2015). Smart cities: Definitions, dimensions, performance, and initiatives. Journal of Urban Technology, 22(1): 3–21
https://doi.org/10.1080/10630732.2014.942092
2 S E Bibri, J Krogstie (2017). Smart sustainable cities of the future: An extensive interdisciplinary literature review. Sustainable Cities and Society, 31: 183–212
https://doi.org/10.1016/j.scs.2017.02.016
3 S P Caird, S H Hallett (2019). Towards evaluation design for smart city development. Journal of Urban Design, 24(2): 188–209
https://doi.org/10.1080/13574809.2018.1469402
4 J S Cardoso, M J Cardoso (2007). Towards an intelligent medical system for the aesthetic evaluation of breast cancer conservative treatment. Artificial Intelligence in Medicine, 40(2): 115–126
https://doi.org/10.1016/j.artmed.2007.02.007 pmid: 17420117
5 G Q Chen, G Wu, Y D Gu, B J Lu, Q Wei (2018a). The challenges for big data driven research and applications in the context of managerial decision-making: Paradigm shift and research directions. Journal of Management Sciences in China, 21(7): 1–10 (in Chinese)
6 X H Chen, G D Yi, J Liu, X Liu, Y Chen (2018b). Evaluating economic growth, industrial structure, and water quality of the Xiangjiang River Basin in China based on a spatial econometric approach. International Journal of Environmental Research and Public Health, 15(10): 2095–2112
https://doi.org/10.3390/ijerph15102095 pmid: 30257427
7 D J Cook (2012). How smart is your home? Science, 335(6076): 1579–1581
https://doi.org/10.1126/science.1217640 pmid: 22461596
8 R Cowley, S Joss, Y Dayot (2018). The smart city and its publics: Insights from across six UK cities. Urban Research & Practice, 11(1): 53–77
9 X L Diao (2015). “Internet+” promotes the transformation and upgrading of smart city construction. Communications World, (11): 23 (in Chinese)
10 B Hammi, R Khatoun, S Zeadally, A Fayad, L Khoukhi (2018). IoT technologies for smart cities. IET Networks, 7(1): 1–13
https://doi.org/10.1049/iet-net.2017.0163
11 A Q Huang, M L Crow, G T Heydt, J P Zheng, S J Dale (2011). The future renewable electric energy delivery and management (FREEDM) system: The energy internet. Proceedings of the IEEE, 99(1): 133–148
https://doi.org/10.1109/JPROC.2010.2081330
12 M Joshi, A Vaidya, M Deshmukh (2018). Sustainable transport solutions for the concept of smart city. In: Gautam A, De S, Dhar A, Gupta J, Pandey A, eds. Sustainable Energy and Transportation. Energy, Environment, and Sustainability. Singapore: Springer, 21–42
13 J C Kenneth, A S William (1994). Vignettes: Medical wisdom. Science, 265(5175): 1115
https://doi.org/10.1126/science.265.5175.1115 pmid: 17832907
14 R K R Kummitha, N Crutzen (2017). How do we understand smart cities? An evolutionary perspective. Cities, 67: 43–52
https://doi.org/10.1016/j.cities.2017.04.010
15 J H Lee, R Phaal, S H Lee (2013). An integrated service-device-technology roadmap for smart city development. Technological Forecasting and Social Change, 80(2): 286–306
https://doi.org/10.1016/j.techfore.2012.09.020
16 J W Li, D A Gan (2001). The connotation, task and countermeasures of building digital city. China Industrial Economy, (10): 53–59 (in Chinese)
17 M Manousakas, H Papaefthymiou, E Diapouli, A Migliori, A G Karydas, I Bogdanovic-Radovic, K Eleftheriadis (2017). Assessment of PM2.5 sources and their corresponding level of uncertainty in a coastal urban area using EPA PMF 5.0 enhanced diagnostics. Science of the Total Environment, 574: 155–164
18 K A Mogaji, H S Lim, K Abdullah (2015). Regional prediction of groundwater potential mapping in a multifaceted geology terrain using GIS-based Dempster–Shafer model. Arabian Journal of Geosciences, 8(5): 3235–3258
19 M Mohammadi, A Al-Fuqaha (2018). Enabling cognitive smart cities using big data and machine learning: Approaches and challenges. IEEE Communications Magazine, 56(2): 94–101
https://doi.org/10.1109/MCOM.2018.1700298
20 B Ning (2018). A number of scientific and technical problems in intelligent transportation. SCIENTIA SINICA Informationis, 48(9): 1264–1269 (in Chinese)
https://doi.org/10.1360/N112018-00080
21 M O’Grady, G O’Hare (2012). How smart is your city? Science, 335(6076): 1581–1582
https://doi.org/10.1126/science.1217637 pmid: 22461597
22 Y Q Qi (2016). Research on Smart City Evaluation Algorithm Based on Analytic Hierarchy Process. Dissertation for the Master Degree. Beijing: Beijing University of Technology (in Chinese)
23 K E Skouby, P Lynggaard (2014). Smart home and smart city solutions enabled by 5G, IoT, AAI and CoT services. In: 2014 International Conference on Contemporary Computing and Informatics (IC3I). Mysore: IEEE, 874–878
24 J T D Souza, A C D Francisco, C M Piekarski, G F D Prado (2019). Data mining and machine learning to promote smart cities: A systematic review from 2000 to 2018. Sustainability, 11(4): 1077–1090
https://doi.org/10.3390/su11041077
25 Q Y Sun, L Q Yang, H G Zhang (2018). Smart energy—Applications and prospects of artificial intelligence technology in power system. Control and Decision, 33(5): 938–949 (in Chinese)
26 X B Tang, X H Chen, Y Tian (2017). Chemical composition and source apportionment of PM2.5—A case study from one year continuous sampling in the Chang-Zhu-Tan urban agglomeration. Atmospheric Pollution Research, 8(5): 885–899
https://doi.org/10.1016/j.apr.2017.02.004
27 Tencent Research Institute (2018). The 2018 China “Internet+” Index Report. Available at: new.qq.com/omn/20190101/20190101A08H D5.html
28 E P Trindade, M P F Hinnig, E Moreira da Costa, J S Marques, R C Bastos, T Yigitcanlar (2017). Sustainable development of smart cities: A systematic review of the literature. Journal of Open Innovation: Technology, Market, and Complexity, 3(1): 11–24
https://doi.org/10.1186/s40852-017-0063-2
29 R Y Wang, Q Liang, G Q Li (2018). Virtual agglomeration: A new form of the spatial agglomeration under the deep integration of a new generation of information technology and the real economy. Management World, 34(2): 13–21 (in Chinese)
30 S Yamamura, L Y Fan, Y Suzuki (2017). Assessment of urban energy performance through integration of BIM and GIS for smart city planning. Procedia Engineering, 180: 1462–1472
https://doi.org/10.1016/j.proeng.2017.04.309
31 J Zawieska, J Pieriegud (2018). Smart city as a tool for sustainable mobility and transport decarbonisation. Transport Policy, 63: 39–50
https://doi.org/10.1016/j.tranpol.2017.11.004
32 P Zhang (2005). Practice of foreign water resources management and its reference to China. Zhihuai, 27(3): 6–7 (in Chinese)
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