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IQ-Based Smart City Evaluation Theory, Framework and Applications.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	IQ-Based Smart City Evaluation Theory, Framework and Applications./
作者:	Liu, Fangyao.
面頁冊數:	1 online resource (136 pages)
附註:	Source: Dissertations Abstracts International, Volume: 82-08, Section: B.
Contained By:	Dissertations Abstracts International82-08B.
標題:	Information technology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28150802click for full text (PQDT)
ISBN:	9798582502203

IQ-Based Smart City Evaluation Theory, Framework and Applications.
Liu, Fangyao.

IQ-Based Smart City Evaluation Theory, Framework and Applications. - 1 online resource (136 pages)

Source: Dissertations Abstracts International, Volume: 82-08, Section: B.

Thesis (Ph.D.)--University of Nebraska at Omaha, 2020.

Includes bibliographical references

A smart city plays an increasing role in citizen's daily life. There are six main components in the concept of a smart city, namely, smart mobility, smart economy, smart governance, smart living, smart environment, and smart people. For the past decades, government and organizations have initiated many smart city projects. Citizen's transportation, education, investment, and other activities have been shifted from traditional to smart models through emerging technologies and the internet. However, although there has been a significant amount of research work on smart cities, a comprehensive smart city evaluation is still missing. In this dissertation, following the earlier work of the Intelligent Quotient (IQ) test, we propose the concept of the definition for the intelligence of an information system, a smart city evaluation evolution theory, as well as a framework to measure a city's intelligence level. To evaluate such intelligence, 382 technology indicators have been developed. We have applied smart city IQ testing on the top 100 largest cities in the United States (according to 2017 population). K-means clustering analysis is used to group all the 100 smart cities into four categories (Leader, Contender, Challenger, Follower), and ANOVA analysis is used to verify the significance of the results. We have also defined a smart city IQ score in a way so that it is convertible to the age of a human being. Various text mining and data mining methods (including classification) have been applied. The results of our analysis indicate that the average smart city IQ score is like a 6-year-old child. We also show the breakdown of IQ scores in terms of the six main components. Although the evaluation of the smart city projects in the United States is still on-going, the results obtained so far as reported in this dissertation can shed important insights for research in this field, as well as intelligent information systems in general.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798582502203Subjects--Topical Terms:

532993
Information technology.
Subjects--Index Terms:

ClassificationIndex Terms--Genre/Form:

542853
Electronic books.

IQ-Based Smart City Evaluation Theory, Framework and Applications.
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520 $a A smart city plays an increasing role in citizen's daily life. There are six main components in the concept of a smart city, namely, smart mobility, smart economy, smart governance, smart living, smart environment, and smart people. For the past decades, government and organizations have initiated many smart city projects. Citizen's transportation, education, investment, and other activities have been shifted from traditional to smart models through emerging technologies and the internet. However, although there has been a significant amount of research work on smart cities, a comprehensive smart city evaluation is still missing. In this dissertation, following the earlier work of the Intelligent Quotient (IQ) test, we propose the concept of the definition for the intelligence of an information system, a smart city evaluation evolution theory, as well as a framework to measure a city's intelligence level. To evaluate such intelligence, 382 technology indicators have been developed. We have applied smart city IQ testing on the top 100 largest cities in the United States (according to 2017 population). K-means clustering analysis is used to group all the 100 smart cities into four categories (Leader, Contender, Challenger, Follower), and ANOVA analysis is used to verify the significance of the results. We have also defined a smart city IQ score in a way so that it is convertible to the age of a human being. Various text mining and data mining methods (including classification) have been applied. The results of our analysis indicate that the average smart city IQ score is like a 6-year-old child. We also show the breakdown of IQ scores in terms of the six main components. Although the evaluation of the smart city projects in the United States is still on-going, the results obtained so far as reported in this dissertation can shed important insights for research in this field, as well as intelligent information systems in general.
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