Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7455
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dc.contributor.authorYi, Wei-Yingen_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.contributor.authorLeung, Yeeen_US
dc.contributor.authorMeng, Mei-Lingen_US
dc.contributor.authorMak, Terrenceen_US
dc.date.accessioned2023-03-02T09:31:19Z-
dc.date.available2023-03-02T09:31:19Z-
dc.date.issued2016-
dc.identifier.citation2016 IEEE SENSORS, 2016, pp. 1-3en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7455-
dc.description.abstractAir pollution attracts extensive attention globally due to its critical impacts on human life. Monitoring systems providing real-time micro-level pollution information have been developed to provide authorities with data to mitigate these impacts. However, current systems are usually application-specific with fixed hardware and software configurations. They are inconvenient in maintenance, infeasible in reconfiguration, and unexpandable in sensing capabilities. This paper proposes a novel Modular Sensor System (MSS), which aims at tackling these issues by adopting the proposed Universal Sensor Interface (USI) and modular design in a sensor node. A compact MSS senor node with expandable plug-and-play sensor modules and multiple Wireless Sensor Networks (WSNs) compatibility is implemented and evaluated. Results indicate that MSS sensor node can be deployed in different scenarios while dynamically adapting to reconfigurations and monitoring air pollution at low concentration levels with high energy efficiency. We anticipate that MSS is able to relax the efforts on system maintenance, adaptation, and evolution in real-life large-scale deployment situation.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2016 IEEE SENSORSen_US
dc.titleModular sensor system (MSS) for urban air pollution monitoringen_US
dc.typeConference Paperen_US
dc.identifier.doi10.1109/ICSENS.2016.7808924.-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
Appears in Collections:Applied Data Science - Publication
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