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Methodological Proposals for the Development of Services in a Smart City: A Literature Review
- Source :
- Sustainability, Vol 12, Iss 10249, p 10249 (2020)
- Publication Year :
- 2020
- Publisher :
- MDPI AG, 2020.
-
Abstract
- This literature review analyzes and classifies methodological contributions that answer the different challenges faced by smart cities. This study identifies city services that require the use of artificial intelligence (AI); which they refer to as AI application areas. These areas are classified and evaluated, taking into account the five proposed domains (government, environment, urban settlements, social assistance, and economy). In this review, 168 relevant studies were identified that make methodological contributions to the development of smart cities and 66 AI application areas, along with the main challenges associated with their implementation. The review methodology was content analysis of scientific literature published between 2013 and 2020. The basic terminology of this study corresponds to AI, the internet of things, and smart cities. In total, 196 references were used. Finally, the methodologies that propose optimization frameworks and analytical frameworks, the type of conceptual research, the literature published in 2018, the urban settlement macro-categories, and the group city monitoring–smart electric grid, make the greater contributions.
- Subjects :
- Knowledge management
smart cities
Geography, Planning and Development
lcsh:TJ807-830
lcsh:Renewable energy sources
02 engineering and technology
Scientific literature
Management, Monitoring, Policy and Law
Terminology
Development (topology)
Human settlement
Smart city
0202 electrical engineering, electronic engineering, information engineering
Sociology
lcsh:Environmental sciences
lcsh:GE1-350
Government
Renewable Energy, Sustainability and the Environment
business.industry
lcsh:Environmental effects of industries and plants
020206 networking & telecommunications
city services
Grid
artificial intelligence
internet of things
lcsh:TD194-195
Content analysis
020201 artificial intelligence & image processing
business
Subjects
Details
- Language :
- English
- ISSN :
- 20711050
- Volume :
- 12
- Issue :
- 10249
- Database :
- OpenAIRE
- Journal :
- Sustainability
- Accession number :
- edsair.doi.dedup.....49d4bf2899c53d6238d91c2b92d8d3f0