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The sensable city: A survey on the deployment and management for smart city monitoring
KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems Engineering.ORCID iD: 0000-0002-1934-9208
(MIT Senseable City Laboratory)
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.ORCID iD: 0000-0002-5407-0835
(Department of Computer Science, Electrical and Space Engineering, Lulea University of Technology)
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(English)In: IEEE Communications Surveys and Tutorials, ISSN 1553-877X, E-ISSN 1553-877XArticle in journal (Refereed) Accepted
Abstract [en]

In last two decades, various monitoring systems have been designed and deployed in urban environments, toward the realization of the so called smart cities. Such systems are based on both dedicated sensor nodes, and ubiquitous but not dedicated devices such as smart phones and vehicles' sensors. When we design sensor network monitoring systems for smart cities, we have two essential problems: node deployment and sensing management. These design problems are challenging, due to large urban areas to monitor, constrained locations for deployments, and heterogeneous type of sensing devices. There is a vast body of literature from different disciplines that have addressed these challenges. However, we do not have yet a comprehensive understanding and sound design guidelines. This paper addresses such a research gap and provides an overview of the theoretical problems we face, and what possible approaches we may use to solve these problems. Specifically, this paper focuses on the problems on both the deployment of the devices (which is the system design/configuration part) and the sensing management of the devices (which is the system running part). We also discuss how to choose the existing algorithms in different type of monitoring applications in smart cities, such as structural health monitoring, water pipeline networks, traffic monitoring. We finally discuss future research opportunities and open challenges for smart city monitoring.

National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-240367DOI: 10.1109/COMST.2018.2881008ISI: 000470838000020Scopus ID: 2-s2.0-85056584676OAI: oai:DiVA.org:kth-240367DiVA, id: diva2:1271476
Note

QC 20190107

Available from: 2018-12-17 Created: 2018-12-17 Last updated: 2019-10-23Bibliographically approved

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Publisher's full textScopushttps://ieeexplore.ieee.org/document/8533352

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Xiao, MingFischione, Carlo

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