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Making sense of smart city sensors
KTH, School of Industrial Engineering and Management (ITM), Industrial Ecology (moved 20130630).ORCID iD: 0000-0003-2621-4253
KTH, School of Industrial Engineering and Management (ITM), Industrial Ecology (moved 20130630).
2013 (English)In: Urban and Regional Data Management, UDMS Annual 2013 - Proceedings of the Urban Data Management Society Symposium 2013, Taylor & Francis Group, 2013, 117-127 p.Conference paper (Refereed)
Abstract [en]

The rapid emergence of smart cities and their sensor networks is being accompanied by an increasing demand for systems to interpret and use the vast amounts of new data they make available. This paper describes the key system design decisions that needed to be taken when developing a calculation engine for a pilot project entitled Smart City Stockholm Royal Seaport. The system design decisions confronting researchers ranged from dealing with data gaps and drawing system boundaries, to developing data structures and ontologies that allow for comparability among smart cities. Most of these decisions are currently being made on an ad hoc basis by system architects while the need for comparability and transparency, demands standardization. The success of standardization bodies and unifying organizations, such as City Protocol, is dependent on the smart city pilot projects being transparent with regards to these design decisions, so they ultimately can be used as a foundation for developing a common language for smart cities.

Place, publisher, year, edition, pages
Taylor & Francis Group, 2013. 117-127 p.
Keyword [en]
Common languages, Design decisions, Drawing system, KeY systems, Pilot projects, Smart cities, Stockholm, System architects, Data structures, Design, Information management, Sensor networks, Standardization, Systems analysis, Electronic commerce
National Category
Civil Engineering
URN: urn:nbn:se:kth:diva-125984ISI: 000342637800011ScopusID: 2-s2.0-84877656844ISBN: 978-113800063-6OAI: diva2:641426
Urban Data Management Society Symposium 2013, UDMS Annual 2013, 29 May 2013 through 31 May 2013, London

QC 20130816

Available from: 2013-08-16 Created: 2013-08-16 Last updated: 2015-11-20Bibliographically approved
In thesis
1. Smart Urban Metabolism: Toward a New Understanding of Causalities in Cities
Open this publication in new window or tab >>Smart Urban Metabolism: Toward a New Understanding of Causalities in Cities
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

For half a century, urban metabolism has been used to provide insights to support transitions to sustainable urban development (SUD). Internet and Communication Technology (ICT) has recently been recognized as a potential technology enabler to advance this transition. This thesis explored the potential for an ICT-enabled urban metabolism framework aimed at improving resource efficiency in urban areas by supporting decision-making processes. Three research objectives were identified: i) investigation of how the urban metabolism framework, aided by ICT, could be utilized to support decision-making processes; ii) development of an ICT platform that manages real-time, high spatial and temporal resolution urban metabolism data and evaluation of its implementation; and iii) identification of the potential for efficiency improvements through the use of resulting high spatial and temporal resolution urban metabolism data. The work to achieve these objectives was based on literature reviews, single-case study research in Stockholm, software engineering research, and big data analytics of resulting data. The evolved framework, Smart Urban Metabolism (SUM), enabled by the emerging context of smart cities, operates at higher temporal (up to real-time), and spatial (up to household/individual) data resolution. A key finding was that the new framework overcomes some of the barriers identified for the conventional urban metabolism framework. The results confirm that there are hidden urban patterns that may be uncovered by analyzing structured big urban data. Some of those patterns may lead to the identification of appropriate intervention measures for SUD.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. xiii, 73 p.
TRITA-IM, ISSN 1402-7615 ; 2015:01
industrial ecology, urban metabolism, smart cities, big data, data science
National Category
Other Environmental Engineering Environmental Analysis and Construction Information Technology
Research subject
Industrial Ecology
urn:nbn:se:kth:diva-176892 (URN)978-91-7595-737-1 (ISBN)
Public defence
2015-12-16, F3, Lindstedtsvägen 26, KTH, Stockholm, 14:00 (English)
Smart City SRS
VINNOVA, 2012-01148

QC 20151120

Available from: 2015-11-20 Created: 2015-11-11 Last updated: 2015-11-20Bibliographically approved

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