Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7441
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dc.contributor.authorYi, Wei-Yingen_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.contributor.authorLeung, Yeeen_US
dc.date.accessioned2023-03-02T02:50:54Z-
dc.date.available2023-03-02T02:50:54Z-
dc.date.issued2018-
dc.identifier.citationSensors, 2018, 18(1), 7en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7441-
dc.description.abstractUrban air pollution has caused public concern globally because it seriously affects human life. Modern monitoring systems providing pollution information with high spatio-temporal resolution have been developed to identify personal exposures. However, these systems’ hardware specifications and configurations are usually fixed according to the applications. They can be inconvenient to maintain, and difficult to reconfigure and expand with respect to sensing capabilities. This paper aims at tackling these issues by adopting the proposed Modular Sensor System (MSS) architecture and Universal Sensor Interface (USI), and modular design in a sensor node. A compact MSS sensor node is implemented and evaluated. It has expandable sensor modules with plug-and-play feature and supports multiple Wireless Sensor Networks (WSNs). Evaluation results show that MSS sensor nodes can easily fit in different scenarios, adapt to reconfigurations dynamically, and detect low concentration air pollution with high energy efficiency and good data accuracy. We anticipate that the efforts on system maintenance, adaptation, and evolution can be significantly reduced when deploying the system in the field.en_US
dc.language.isoenen_US
dc.relation.ispartofSensorsen_US
dc.titleA modular plug-and-play sensor system for urban air pollution monitoring: Design, implementation and evaluationen_US
dc.typePeer Reviewed Journal Articleen_US
dc.identifier.doi10.3390/s18010007-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
Appears in Collections:Applied Data Science - Publication
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