Big Data Analytics for Smart Cities

Bassoo, Vandana; Ramnarain-Seetohul, Vidasha; Hurbungs, V.; Fowdur, Tulsi Pawan; Beeharry, Yogesh

doi:10.1007/978-3-319-60435-0_15

Cited by 12 publications

(6 citation statements)

References 18 publications

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“…Earlier research, e.g., [47], implies that cities need to consider how to design intelligent applications and solutions to be informed and easy to use. Locals say that simple solutions have a positive effect on the perceived value [48] as well as on its actual use [22]. For testing the possible ease of use of applications and solutions for residents, we propose the hypothesis: Hypothesis 2 (H2).…”

Section: Methodsmentioning

confidence: 99%

“…In the case of intelligent solutions, a wide range of services, products and services offered to residents is becoming more and more important. Applications in their simplest form may provide easy operation, but also more complex services may not be a problem for the user [7,22,49]. Service variability within smart cities includes the availability of various ancillary services [50] with the extension of the highest level of service variability in those systems, which give the opportunity to use of services, personalized services and marketing messages targeted at specific individuals [13,49,51,52].…”

Section: Methodsmentioning

confidence: 99%

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Perception of the Quality of Smart City Solutions as a Sense of Residents’ Safety

Żywiołek

Schiavone

2021

Energies

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Personalization, mobility, artificial intelligence, corporate life transferred to the online world—all these elements will shape all intelligent solutions, including those for cities in the future also in the field of energy management. A necessary condition is to determine which specific repetitive behaviors and features smart cities will have to meet in order to build an image among residents and adapt to their preferences and requirements and energy requirements. Smart cities were created to support residents in using various services, to give them the possibility of easy communication without time and local barriers. Therefore, high-quality smart solutions in cities significantly affect trust in the city and can affect its reputation. Given that the purpose of the article is to examine the perception of intelligent solutions also in the field of energy and their impact on the sense of privacy and security, different exchanges of perceptions of quality, the risks they pose to residents and their perception of what gives a picture, have been studied. The results of empirical research clearly showed that the safety and level of satisfaction with the activities carried out by the city have a significant impact on the perceived quality, which in turn has a positive impact on reputation. The authors proposed a methodology based on the Kano model for examining residents’ satisfaction in order to investigate undefined desires and identified and confirmed needs and to study the analysis of risk and potential threats. The study was in the form of a proprietary questionnaire that can be used in similar surveys on the satisfaction of residents; 2685 correctly completed questionnaires were analyzed and the results obtained after submission were included in management action plans. The city government has expressed an interest that the measures taken will be reviewed after one to two years.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Perception of the Quality of Smart City Solutions as a Sense of Residents’ Safety

Żywiołek

Schiavone

2021

Energies

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“…In the past few years big data analytics has emerged as an important disruptive technology in enabling the “smartness” of smart cities (Bassoo, Ramnarain‐Seetohul, Hurbungs, Fowdur, & Beeharry, ). Other disruptive technologies such as Internet of Things (IoT) generate big data that needs to be processed and analyzed in short amounts of time to enable smart city governments to react to emerging patterns and trends in an efficient manner.…”

Section: Big Data Analytics In Smart Citiesmentioning

confidence: 99%

Smart city big data analytics: An advanced review

Soomro

Bhutta

Khan

et al. 2019

WIREs Data Min & Knowl

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With the increasing role of ICT in enabling and supporting smart cities, the demand for big data analytics solutions is increasing. Various artificial intelligence, data mining, machine learning and statistical analysis-based solutions have been successfully applied in thematic domains like climate science, energy management, transport, air quality management and weather pattern analysis. In this paper, we present a systematic review of the literature on smart city big data analytics. We have searched a number of different repositories using specific keywords and followed a structured data mining methodology for selecting material for the review. We have also performed a technological and thematic analysis of the shortlisted literature, identified various data mining/machine learning techniques and presented the results. Based on this analysis we also present a classification model that studies four aspects of research in this domain. These include data models, computing models, security and privacy aspects and major market drivers in the smart cities domain. Moreover, we present a gap analysis and identify future directions for research. For the thematic analysis we identified the themes smart city governance, economy, environment, transport and energy. We present the major challenges in these themes, the major research work done in the field of data analytics to address these challenges and future research directions.

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“…Tripathi [6] posit that, in the majority of these cities, the safe city concept is promoted as being able to help achieve safety, security and privacy in cities amongst other things; hence, a plethora of strategies are employed to achieve it. These strategies often include a paradigm shift to smart cities where different urban components and fabrics are interlinked through the help of ICT and a wide array of advanced technologies such as the Internet of Things (IoT) [7,8], Artificial Intelligence (AI) [9], Big Data [10,11] and Blockchain technology [12] amongst others [13]. In particular, the concept of smart cities is hailed for the emphasis on different smart sensors, cameras and other smart devices in various areas that help in capturing vital data paramount in securing both human and emerging patterns within cities.…”

Section: Introductionmentioning

confidence: 99%

The Emergence of Anti-Privacy and Control at the Nexus between the Concepts of Safe City and Smart City

Allam

2019

Smart Cities

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The emergence of Big Data, accelerated through the Internet of Things (IoT) and Artificial Intelligence, from the emerging, contemporary concept of smart cities coupled with that of the notion for safe cities is raising concerns of privacy and good governance that are impacting on socio-economic and liveability dimensions of urban fabrics. As these gain ground, largely due to economic pressures from large ICT providers, there is a notable increase towards the need for inclusion of human dimensions, complemented by the use of technology. However, the latter is seen as catalysing elements of control and propaganda which are thriving through oversimplified and non-inclusive urban IT policy measures. This paper dwells on the intersecting subjects of smart and safe cities and explores the highlighted issues that are deemed to cause concern and further explore the need for transparency and inclusivity in urban processes and systems. This paper is oriented towards urban planners and policy makers looking at the implementation of smart and safe cities concepts.

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Big Data Analytics for Smart Cities

Cited by 12 publications

References 18 publications

Perception of the Quality of Smart City Solutions as a Sense of Residents’ Safety

Perception of the Quality of Smart City Solutions as a Sense of Residents’ Safety

Smart city big data analytics: An advanced review

The Emergence of Anti-Privacy and Control at the Nexus between the Concepts of Safe City and Smart City

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