Flash Flood Detection in Urban Cities Using Ultrasonic and Infrared Sensors

Handle URI:
http://hdl.handle.net/10754/618396
Title:
Flash Flood Detection in Urban Cities Using Ultrasonic and Infrared Sensors
Authors:
Mousa, Mustafa ( 0000-0001-9355-1343 ) ; Zhang, Xiangliang ( 0000-0002-3574-5665 ) ; Claudel, Christian
Abstract:
Floods are the most common type of natural disaster. Often leading to loss of lives and properties in the thousands yearly. Among these events, urban flash floods are particularly deadly because of the short timescales on which they occur, and because of the population density of cities. Since most flood casualties are caused by a lack of information on the impending flood (type, location, severity), sensing these events is critical to generate accurate and detailed warnings and short term forecasts. However, no dedicated flash flood sensing systems, that could monitor the propagation of flash floods, in real time, currently exist in cities. In the present paper, firstly a new sensing device that can simultaneously monitor urban flash floods and traffic congestion has been presented. This sensing device is based on the combination of ultrasonic range-finding with remote temperature sensing, and can sense both phenomena with a high degree of accuracy, using a combination of L1-regularized reconstruction and artificial neural networks to process measurement data. Secondly, corresponding algorithms have been implemented on a low-power wireless sensor platform, and their performance in water level estimation in a 6 months test involving four different sensors is illustrated. The results demonstrate that urban water levels can be reliably estimated with error less than 2 cm, and that the preprocessing and machine learning schemes can run in real-time on currently available wireless sensor platforms.
KAUST Department:
Electrical Engineering; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Citation:
Flash Flood Detection in Urban Cities Using Ultrasonic and Infrared Sensors 2016:1 IEEE Sensors Journal
Journal:
IEEE Sensors Journal
Issue Date:
19-Jul-2016
DOI:
10.1109/JSEN.2016.2592359
Type:
Article
ISSN:
1530-437X; 1558-1748; 2379-9153
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7516634
Appears in Collections:
Articles

Full metadata record

DC FieldValue Language
dc.contributor.authorMousa, Mustafaen
dc.contributor.authorZhang, Xiangliangen
dc.contributor.authorClaudel, Christianen
dc.date.accessioned2016-08-14T09:14:05Z-
dc.date.available2016-08-14T09:14:05Z-
dc.date.issued2016-07-19-
dc.identifier.citationFlash Flood Detection in Urban Cities Using Ultrasonic and Infrared Sensors 2016:1 IEEE Sensors Journalen
dc.identifier.issn1530-437X-
dc.identifier.issn1558-1748-
dc.identifier.issn2379-9153-
dc.identifier.doi10.1109/JSEN.2016.2592359-
dc.identifier.urihttp://hdl.handle.net/10754/618396-
dc.description.abstractFloods are the most common type of natural disaster. Often leading to loss of lives and properties in the thousands yearly. Among these events, urban flash floods are particularly deadly because of the short timescales on which they occur, and because of the population density of cities. Since most flood casualties are caused by a lack of information on the impending flood (type, location, severity), sensing these events is critical to generate accurate and detailed warnings and short term forecasts. However, no dedicated flash flood sensing systems, that could monitor the propagation of flash floods, in real time, currently exist in cities. In the present paper, firstly a new sensing device that can simultaneously monitor urban flash floods and traffic congestion has been presented. This sensing device is based on the combination of ultrasonic range-finding with remote temperature sensing, and can sense both phenomena with a high degree of accuracy, using a combination of L1-regularized reconstruction and artificial neural networks to process measurement data. Secondly, corresponding algorithms have been implemented on a low-power wireless sensor platform, and their performance in water level estimation in a 6 months test involving four different sensors is illustrated. The results demonstrate that urban water levels can be reliably estimated with error less than 2 cm, and that the preprocessing and machine learning schemes can run in real-time on currently available wireless sensor platforms.en
dc.language.isoenen
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7516634en
dc.rights(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.subjectARMAXen
dc.subjectArtificial Neural Networksen
dc.subjectFlood Detectionen
dc.subjectNonlinear Regressionen
dc.subjectWater Level Estimationen
dc.titleFlash Flood Detection in Urban Cities Using Ultrasonic and Infrared Sensorsen
dc.typeArticleen
dc.contributor.departmentElectrical Engineeringen
dc.contributor.departmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Divisionen
dc.identifier.journalIEEE Sensors Journalen
dc.eprint.versionPost-printen
dc.contributor.institutionThe University of Texas at Austinen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorMousa, Mustafaen
kaust.authorZhang, Xiangliangen
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.