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作者

Fangyao Liu;Yong Shi;Zhengxin Chen

来源

JOURNAL OF URBAN PLANNING AND DEVELOPMENT,Vol.147,Issue1

语言

英文

关键字

作者单位

Ph.D. Candidate, School of Electrical and Information Engineering, Southwest Minzu Univ., #16, South Section, 1st Ring Rd., Chengdu, Sichuan 610041, China; Dept. of Information Systems and Quantitative Analysis, Univ. of Nebraska Omaha, 6001 Dodge St., Omaha, NE 68182 (corresponding author). ORCID: https://orcid.org/0000-0002-6340-3291. Email: [email protected];Professor, School of Electrical and Information Engineering, Southwest Minzu Univ., #16, South Section, 1st Ring Rd., Chengdu, Sichuan 610041, China; Dept. of Information Systems and Quantitative Analysis, Univ. of Nebraska Omaha, 6001 Dodge St., Omaha, NE 68182; Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China. Email: [email protected];Professor, Dept. of Computer Science, Univ. of Nebraska Omaha, 6001 Dodge St., Omaha, NE 68182. Email: [email protected]

摘要

A smart city plays an increasing role in citizens’ daily life. A smart city has six main components, namely smart mobility, smart economy, smart governance, smart living, smart environment, and smart people. For the past several decades, government and organizations throughout the world have initiated many smart city projects. Citizens’ transportation, education, investment, and other activities have been shifted from traditional to smart models through emerging technologies and the internet. In this paper, following the pioneering work of the intelligent quotient (IQ) test, we propose a framework to measure a city's intelligence level. We also propose a definition for the intelligence of an information system. 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). In addition, the smart city IQ score is designed 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 that of an eight-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 ongoing, the results obtained so far as reported in this paper can provide important insights for research in this particular field, as well as intelligent information systems in general. Supplemental Materials supplemental_material_up.1943-5444.0000637_liu.pdf (429 KB)