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Article: Multi-Type Sensor Placements in Gaussian Spatial Fields for Environmental Monitoring

TitleMulti-Type Sensor Placements in Gaussian Spatial Fields for Environmental Monitoring
Authors
Issue Date2019
PublisherMolecular Diversity Preservation International. The Journal's web site is located at http://www.mdpi.net/sensors
Citation
Sensors, 2019, v. 19 n. 1, article no. 189 How to Cite?
AbstractAs citizens are increasingly concerned about the surrounding environment, it is important for modern cities to provide sufficient and accurate environmental information to the public for decision making in the era of smart cities. Due to the limited budget, we often need to optimize the sensor placement in order to maximize the overall information gain according to certain criteria. Existing work is primarily concerned with single-type sensor placement; however, the environment usually requires accurate measurements of multiple types of environmental characteristics. In this paper, we focus on the optimal multi-type sensor placement in Gaussian spatial field for environmental monitoring. We study two representative cases: the one-with-all case when each station is equipped with all types of sensors and the general case when each station is equipped with at least one type of sensor. We propose two greedy algorithms accordingly, each with a provable approximation guarantee. We evaluated the proposed approach via an application in air quality monitoring scenario in Hong Kong and experimental results demonstrate the effectiveness of the proposed approach.
Persistent Identifierhttp://hdl.handle.net/10722/275014
ISSN
2017 Impact Factor: 2.475
2015 SCImago Journal Rankings: 0.546
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorSun, C-
dc.contributor.authorYu, Y-
dc.contributor.authorLi, VOK-
dc.contributor.authorLam, JCK-
dc.date.accessioned2019-09-10T02:33:41Z-
dc.date.available2019-09-10T02:33:41Z-
dc.date.issued2019-
dc.identifier.citationSensors, 2019, v. 19 n. 1, article no. 189-
dc.identifier.issn1424-8220-
dc.identifier.urihttp://hdl.handle.net/10722/275014-
dc.description.abstractAs citizens are increasingly concerned about the surrounding environment, it is important for modern cities to provide sufficient and accurate environmental information to the public for decision making in the era of smart cities. Due to the limited budget, we often need to optimize the sensor placement in order to maximize the overall information gain according to certain criteria. Existing work is primarily concerned with single-type sensor placement; however, the environment usually requires accurate measurements of multiple types of environmental characteristics. In this paper, we focus on the optimal multi-type sensor placement in Gaussian spatial field for environmental monitoring. We study two representative cases: the one-with-all case when each station is equipped with all types of sensors and the general case when each station is equipped with at least one type of sensor. We propose two greedy algorithms accordingly, each with a provable approximation guarantee. We evaluated the proposed approach via an application in air quality monitoring scenario in Hong Kong and experimental results demonstrate the effectiveness of the proposed approach.-
dc.languageeng-
dc.publisherMolecular Diversity Preservation International. The Journal's web site is located at http://www.mdpi.net/sensors-
dc.relation.ispartofSensors-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleMulti-Type Sensor Placements in Gaussian Spatial Fields for Environmental Monitoring-
dc.typeArticle-
dc.identifier.emailLi, VOK: vli@eee.hku.hk-
dc.identifier.emailLam, JCK: h9992013@hkucc.hku.hk-
dc.identifier.authorityLi, VOK=rp00150-
dc.identifier.authorityLam, JCK=rp00864-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3390/s19010189-
dc.identifier.scopuseid_2-s2.0-85070866369-
dc.identifier.hkuros302921-
dc.identifier.volume19-
dc.identifier.issue1-
dc.identifier.spagearticle no. 189-
dc.identifier.epagearticle no. 189-
dc.identifier.isiWOS:000458574600189-
dc.publisher.placeSwitzerland-

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