Review of urban computing in air quality management as smart city service: An integrated IoT, AI, and cloud technology perspective

Kaginalkar, Akshara; Kumar, Shashi Bhushan; Gargava, Prashant; Niyogi, Dev

doi:10.1016/j.uclim.2021.100972

Cited by 93 publications

(45 citation statements)

References 192 publications

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“…The analyzed papers prove that data-driven smart cities have a potential to enable emission reductions and climate change mitigation [ 73 ]. Therefore, data and data-based solutions should be used to tackle climate issues such as transportation efficiency and changes in travel behavior [ 71 ].…”

Section: Resultsmentioning

confidence: 99%

“…Fortunately, AI enables newer methods of urban data acquisition using IoT, mobile phones, crowd sourcing, and social media [ 73 ]. The case studies analysis proves the importance of the ‘Fourth Industrial Revolution’ (4IR) technologies such as the Internet of Things (IoT), big data, artificial intelligence, smartphones, and cloud computing, which are influencing urban development as they allow air quality monitoring, following urban flows, and improving quality of life by overcoming communication barriers [ 73 ]. Even blockchain frameworks are used to shape people-oriented smart mobility systems [ 74 ].…”

Section: Resultsmentioning

confidence: 99%

“…Smart mobility is therefore largely permeated by ICT, used in both backward and forward applications, to support the optimization of traffic flows and also to collect citizens’ opinions about livability in cities or the quality of local public transport services [ 70 ]. Additionally, AI-based solutions allow real-time mitigation governance [ 73 ], which can lead to more efficient public transportation models and to changes in the mobility behavior of urban dwellers. Surely, the new possibilities of connectivity; exceptional processing power; and the growing role of emerging technologies such as AI, IoT, robotics, and self-driving vehicles will advance intelligent mobility in the coming years [ 76 ].…”

Section: Resultsmentioning

confidence: 99%

“…Artificial-intelligence-based applications are becoming meaningful tools for disaster prediction and management [ 78 ]. When analyzing selected case studies, we found AI as supportive in the following aspects: In terms of improving the urban microclimate and responding to the challenge of urban heat islands [ 73 ]; In analyses of major environmental threats, e.g., flooding [ 84 , 85 ], heat waves, and air quality [ 73 , 88 ]; In the enhancement of efficient land use management [ 89 ] and emission reduction and decarbonization [ 88 , 100 ]. …”

Section: Resultsmentioning

confidence: 99%

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Greencoin as an AI-Based Solution Shaping Climate Awareness

Obracht-Prondzyńska

Duda

Anacka

et al. 2022

IJERPH

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Our research aim was to define possible AI-based solutions to be embedded in the Greencoin project, designed as a supportive tool for smart cities to achieve climate neutrality. We used Kamrowska-Załuska’s approach for evaluating AI-based solutions’ potential in urban planning. We narrowed down the research to the educational and economic aspects of smart cities. Furthermore, we used a systematic literature review. We propose solutions supporting the implementation process of net zero policies benefiting from single actions of urban dwellers based on the Greencoin project developed by us. By following smart city sectors, the paper introduces AI-based solutions which can enrich Greencoin by addressing the following needs: (1) shaping pro-environmental behaviors, (2) introducing instruments to reinforce the urban management process, (3) supporting bottom-up initiatives allowing to shape urban resilience, (4) enhancing smart mobility, (5) shaping local economies supporting urban circularity, and (6) allowing better communication with residents. Our research fills the gap in the limited group of studies focused on shaping climate awareness, enhancing smart governance, and supporting social participation and inclusion. It proves that AI-based educational tools can be supportive when implementing adaptation policies toward climate neutrality based on our proposed AI-based model shaping climate awareness.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Greencoin as an AI-Based Solution Shaping Climate Awareness

Obracht-Prondzyńska

Duda

Anacka

et al. 2022

IJERPH

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“…As is well understood, cloud services provide cost-effective options to access, process, and disseminate data and information in real-time [49,50]. For AirDMS, the cloud-based system consists of four parts: (a) the web-based system, which displays real time data on a 5-min basis on the web site, (b) the Remote Communication System, which can collect or provide data in an automated way to authorized users, (c) the AirDMS Service, which provides the diagnostic measurements of the analyzers and stations' operating status (e.g., internal temperature, current voltage, door status), and (d) the AirDMS Alerts.…”

Section: Cloud-based Information Systemmentioning

confidence: 99%

Cloud-Based Decision Support System for Air Quality Management

Evagelopoulos

Charisiou²,

Logothetis³

et al. 2022

Climate

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Air quality is important for the protection of human health, the environment and our cultural heritage and it is an issue that will acquire increased significance in the future due to the adverse effects of climate change. Thus, it is important to not simply monitor air quality, but to make information immediately available to those responsible for monitoring the networks, to policy/decision makers, but also to the general population. Moreover, the development of information technologies over the last couple of decades has allowed the proliferation of real-time pollution monitoring. The work presented herein concerns the development of an effective way of monitoring environmental parameters using dedicated software. It offers a complete suite of applications that support environmental data collection management and reporting for air quality and associated meteorology. It combines modern technologies for the proper monitoring of air quality networks, which can consist of one or more measuring stations. Innovatively, it also focuses on how to effectively present the relevant information, utilizing modern technologies, such as cloud and mobile applications, to network engineers, policy/decision managers, and to the general public at large. It also has the capability of notifying appropriate personnel in the event of failures, overruns or abnormal values. The system, in its current configuration, handles information from six networks that include over 55 air pollution monitoring stations that are located throughout Greece. This practical application has shown that the system can achieve high data availability rates, even higher than 99% during the year.

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