A high performance, low power computational platform for complex sensing operations in smart cities

Handle URI:
http://hdl.handle.net/10754/622827
Title:
A high performance, low power computational platform for complex sensing operations in smart cities
Authors:
Jiang, Jiming; Claudel, Christian
Abstract:
This paper presents a new wireless platform designed for an integrated traffic/flash flood monitoring system. The sensor platform is built around a 32-bit ARM Cortex M4 microcontroller and a 2.4GHz 802.15.4802.15.4 ISM compliant radio module. It can be interfaced with fixed traffic sensors, or receive data from vehicle transponders. This platform is specifically designed for solar-powered, low bandwidth, high computational performance wireless sensor network applications. A self-recovering unit is designed to increase reliability and allow periodic hard resets, an essential requirement for sensor networks. A radio monitoring circuitry is proposed to monitor incoming and outgoing transmissions, simplifying software debugging. We illustrate the performance of this wireless sensor platform on complex problems arising in smart cities, such as traffic flow monitoring, machine-learning-based flash flood monitoring or Kalman-filter based vehicle trajectory estimation. All design files have been uploaded and shared in an open science framework, and can be accessed from [1]. The hardware design is under CERN Open Hardware License v1.2.
KAUST Department:
King Abdullah University of Science and Technology, Thuwal, 23955-6900 Kingdom of Saudi Arabia
Citation:
Jiang J, Claudel C (2017) A high performance, low power computational platform for complex sensing operations in smart cities. HardwareX. Available: http://dx.doi.org/10.1016/j.ohx.2017.01.001.
Publisher:
Elsevier BV
Journal:
HardwareX
Issue Date:
2-Feb-2017
DOI:
10.1016/j.ohx.2017.01.001
Type:
Article
ISSN:
2468-0672
Additional Links:
http://www.sciencedirect.com/science/article/pii/S2468067216300177
Appears in Collections:
Articles

Full metadata record

DC FieldValue Language
dc.contributor.authorJiang, Jimingen
dc.contributor.authorClaudel, Christianen
dc.date.accessioned2017-02-05T13:53:44Z-
dc.date.available2017-02-05T13:53:44Z-
dc.date.issued2017-02-02en
dc.identifier.citationJiang J, Claudel C (2017) A high performance, low power computational platform for complex sensing operations in smart cities. HardwareX. Available: http://dx.doi.org/10.1016/j.ohx.2017.01.001.en
dc.identifier.issn2468-0672en
dc.identifier.doi10.1016/j.ohx.2017.01.001en
dc.identifier.urihttp://hdl.handle.net/10754/622827-
dc.description.abstractThis paper presents a new wireless platform designed for an integrated traffic/flash flood monitoring system. The sensor platform is built around a 32-bit ARM Cortex M4 microcontroller and a 2.4GHz 802.15.4802.15.4 ISM compliant radio module. It can be interfaced with fixed traffic sensors, or receive data from vehicle transponders. This platform is specifically designed for solar-powered, low bandwidth, high computational performance wireless sensor network applications. A self-recovering unit is designed to increase reliability and allow periodic hard resets, an essential requirement for sensor networks. A radio monitoring circuitry is proposed to monitor incoming and outgoing transmissions, simplifying software debugging. We illustrate the performance of this wireless sensor platform on complex problems arising in smart cities, such as traffic flow monitoring, machine-learning-based flash flood monitoring or Kalman-filter based vehicle trajectory estimation. All design files have been uploaded and shared in an open science framework, and can be accessed from [1]. The hardware design is under CERN Open Hardware License v1.2.en
dc.publisherElsevier BVen
dc.relation.urlhttp://www.sciencedirect.com/science/article/pii/S2468067216300177en
dc.rights© 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectWireless sensor networken
dc.subjectEmbedded systemen
dc.subjectArtificial Neural Networksen
dc.titleA high performance, low power computational platform for complex sensing operations in smart citiesen
dc.typeArticleen
dc.contributor.departmentKing Abdullah University of Science and Technology, Thuwal, 23955-6900 Kingdom of Saudi Arabiaen
dc.identifier.journalHardwareXen
dc.eprint.versionPost-printen
dc.contributor.institutionUniversity of Texas at Austin, 301E E Dean Keeton St C1761 Austin, TX 78712 USAen
kaust.authorJiang, Jimingen
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