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Article

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

Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China
*
Author to whom correspondence should be addressed.
This paper is an extended version of Sun, C.; Yu, Y.; Li, V.O.; Lam, J.C. Optimal Multi-type Sensor Placements in Gaussian Spatial Fields for Environmental Monitoring. In Proceedings of the 4th International Conference on Smart Cities, Kansas City, MO, USA, 16–19 September 2018; pp. 420–429.
Sensors 2019, 19(1), 189; https://doi.org/10.3390/s19010189
Received: 30 November 2018 / Revised: 27 December 2018 / Accepted: 2 January 2019 / Published: 7 January 2019
(This article belongs to the Special Issue Selected Papers from ISC2 2018)
As 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. View Full-Text
Keywords: multi-type sensor placement; submodular optimization; gaussian process multi-type sensor placement; submodular optimization; gaussian process
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MDPI and ACS Style

Sun, C.; Yu, Y.; Li, V.O.K.; Lam, J.C.K. Multi-Type Sensor Placements in Gaussian Spatial Fields for Environmental Monitoring. Sensors 2019, 19, 189. https://doi.org/10.3390/s19010189

AMA Style

Sun C, Yu Y, Li VOK, Lam JCK. Multi-Type Sensor Placements in Gaussian Spatial Fields for Environmental Monitoring. Sensors. 2019; 19(1):189. https://doi.org/10.3390/s19010189

Chicago/Turabian Style

Sun, Chenxi, Yangwen Yu, Victor O.K. Li, and Jacqueline C.K. Lam. 2019. "Multi-Type Sensor Placements in Gaussian Spatial Fields for Environmental Monitoring" Sensors 19, no. 1: 189. https://doi.org/10.3390/s19010189

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