Bayesian Localization of Water Distribution System Contamination Intrusion Events Using Inline Mobile Sensor Data-Reference-Cited by-同舟云学术

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Bayesian Localization of Water Distribution System Contamination Intrusion Events Using Inline Mobile Sensor Data

Published:2019-08 Issue:8 Volume:145 Page:04019029
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Sankary Nathan¹,Ostfeld Avi²^ORCID

Affiliation:

1. Ph.D. Student, Faculty of Civil and Environmental Engineering, Technion—Israel Institute of Technology, Haifa 3200, Israel (corresponding author).

2. Professor, Faculty of Civil and Environmental Engineering, Technion—Israel Institute of Technology, Haifa 3200, Israel. ORCID:

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29WR.1943-5452.0001086

Reference19 articles.

1. De Sanctis A. E. D. L. Boccelli F. Shang and J. G. Uber. 2008. “Probabilistic approach to characterize contamination sources with imperfect sensors.” In Proc. World Environmental and Water Resources Congress 2008. Reston VA: ASCE.

2. Water Contamination Impact Evaluation and Source-Area Isolation Using Decision Trees

3. Mobile sensor networks for optimal leak and backflow detection and localization in municipal water networks

4. Hart W. J. Berry E. Boman R. Murray C. Phillips L. A. Riesen and J.-P. Watson. 2008. “The TEVA-SPOT toolkit for drinking water contaminant warning system design.” In Proc. World Environmental and Water Resources Congress. Reston VA: ASCE.

5. Efficient Sensor Placement Optimization for Securing Large Water Distribution Networks

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