Integrating Data-Based Strategies and Advanced Technologies with Efficient Air Pollution Management in Smart Cities

被引:15
作者
Myeong, Seunghwan [1 ]
Shahzad, Khurram [2 ]
机构
[1] Inha Univ, Dept Publ Adm, Incheon 22212, South Korea
[2] Inha Univ, Dept Ind Secur & Governance, Incheon 22212, South Korea
关键词
smart cities; artificial intelligence; Internet of Things; air pollution; ARTIFICIAL-INTELLIGENCE; SYSTEMS; PERSPECTIVE; ENVIRONMENT; FRAMEWORK; QUALITY;
D O I
10.3390/su13137168
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The COVID-19 pandemic has demonstrated that creative leadership based on data and citizen volunteers is more significant than vaccines themselves, so this study focuses on the collaboration of sophisticated technologies and human potential to monitor air pollution. Air pollution contributes to critical environmental problems in various towns and cities. With the emergence of the smart city concept, appropriate methods to curb exposure to pollutants must be part of an appropriate urban development policy. This study presents a technologically driven air quality solution for smart cities that advertises energy-efficient and cleaner sequestration in these areas. It attempts to explore how to incorporate data-driven approaches and citizen participation into effective public sector pollution management in smart cities as a major component of the smart city definition. The smart city idea was developed as cities became more widespread through communication devices. This study addresses the technical criteria for implementing a framework that public administration can use to prepare for renovation of public buildings, minimizing energy use and costs and linking smart police stations to monitor air pollution as a part of an integrated city. Such a digital transition in resource management will increase public governance energy performance and provide a higher standard for operations and a healthier environment. The study results indicate that complex processes lead to efficient and sustainable smart cities. This research discovered an interpretive pattern in how public agencies, private enterprises, and community members think and what they do in these regional contexts. It concludes that economic and social benefits could be realized by exploiting data-driven smart city development for its social and spatial complexities.
引用
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页数:14
相关论文
共 51 条
[1]   On big data, artificial intelligence and smart cities [J].
Allam, Zaheer ;
Dhunny, Zaynah A. .
CITIES, 2019, 89 :80-91
[2]   Crowdsensing in Smart Cities: Overview, Platforms, and Environment Sensing Issues [J].
Alvear, Oscar ;
Calafate, Carlos T. ;
Cano, Juan-Carlos ;
Manzoni, Pietro .
SENSORS, 2018, 18 (02)
[3]  
Aslam T., 2018, INT J ADV RES DEV, V3, P58
[4]   Artificial intelligence and smart cities [J].
Batty, Michael .
ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE, 2018, 45 (01) :3-6
[5]   Smart Mobility and Smart Environment in the Spanish cities [J].
Baucells Aleta, Neus ;
Moreno Alonso, Concepcion ;
Arce Ruiz, Rosa M. .
3RD CONFERENCE ON SUSTAINABLE URBAN MOBILITY (3RD CSUM 2016), 2017, 24 :163-170
[6]  
Bhatt J.G., 2020, AUTOMATION BASED SMA
[7]   An urbanization bomb? Population growth and social disorder in cities [J].
Buhaug, Halvard ;
Urdal, Henrik .
GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS, 2013, 23 (01) :1-10
[8]   Energy Sustainability in Smart Cities: Artificial Intelligence, Smart Monitoring, and Optimization of Energy Consumption [J].
Chui, Kwok Tai ;
Lytras, Miltiadis D. ;
Visvizi, Anna .
ENERGIES, 2018, 11 (11)
[9]   Applying a Systems Perspective on the Notion of the Smart City [J].
Colding, Johan ;
Wallhagen, Marita ;
Sorqyist, Patrik ;
Marcus, Lars ;
Hillman, Karl ;
Samuelsson, Karl ;
Barthel, Stephan .
SMART CITIES, 2020, 3 (02) :420-429
[10]   Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review [J].
Di Vaio, Assunta ;
Palladino, Rosa ;
Hassan, Rohail ;
Escobar, Octavio .
JOURNAL OF BUSINESS RESEARCH, 2020, 121 :283-314