Multi-source dataset for urban computing in a Smart City
| Autor: | Ashkan Sami, Ali Reza Honarvar |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Urban computing
Computer science Internet of Things Big data lcsh:Computer applications to medicine. Medical informatics Transport engineering 03 medical and health sciences 0302 clinical medicine Urban planning Smart city lcsh:Science (General) 030304 developmental biology 0303 health sciences Multidisciplinary Land use business.industry Data resources Computer Science Smart City Parking lot lcsh:R858-859.7 business 030217 neurology & neurosurgery Multi-source lcsh:Q1-390 |
| Zdroj: | Data in Brief, Vol 22, Iss, Pp 222-226 (2019) Data in Brief |
| ISSN: | 2352-3409 |
| DOI: | 10.1016/j.dib.2018.09.113 |
| Popis: | It is vital to capture and analyze, from various sources in smart cities, the data that are beneficial in urban planning and decision making for governments and individuals. Urban policy makers can find a suitable solution for urban development by using the opportunities and capacities of big data, and by combining different heterogeneous data resources in smart cities. This paper presents data related to urban computing with an aim of assessing the knowledge that can be obtained through integration of multiple independent data sources in Smart Cities. The data contains multiple sources in the city of Aarhus, Denmark from August 1, 2014 to September 30, 2014. The sources include land use, waterways, water barriers, buildings, roads, amenities, POI, weather, traffic, pollution, and parking lot data. The published data in this paper is an extended version of the City Pulse project data to which additional data sources collected from online sources have been added. Keywords: Smart City, Internet of Things, Big data, Urban computing |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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