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DisCPAQ: distributed context acquisition and reasoning for personalized indoor air quality monitoring in IoT-based systems
conference contribution
posted on 2017-01-01, 00:00 authored by T Belyakhina, Arkady ZaslavskyArkady Zaslavsky, K Mitra, S Saguna, P P JayaramanThe rapidly emerging Internet of Things supports many diverse applications including environmental monitoring. Air quality, both indoors and outdoors, proved to be a significant comfort and health factor for people. This paper proposes a smart context-aware system for indoor air quality monitoring and prediction called DisCPAQ. The system uses data streams from air quality measurement sensors to provide real-time personalised air quality service to users through a mobile app. The proposed system is agnostic to sensor infrastructure. The paper proposes a context model based on Context Spaces Theory, presents the architecture of the system and identifies challenges in developing large scale IoT applications. DisCPAQ implementation, evaluation and lessons learned are all discussed in the paper.
History
Event
IEEE Communications Society Russia Northwest Chapter. Conference (2017 : St. Petersburg, Russia)Volume
LNCS 10531Series
IEEE Communications Society Russia Northwest Chapter ConferencePagination
75 - 86Publisher
SpringerLocation
St. Petersburg, RussiaPlace of publication
Cham, SwitzerlandPublisher DOI
Start date
2017-08-28End date
2017-08-30ISSN
0302-9743eISSN
1611-3349ISBN-13
9783319673790Language
engPublication classification
E Conference publication; E1.1 Full written paper - refereedCopyright notice
2017, Springer International Publishing AGEditor/Contributor(s)
O Galinina •, S Andreev, S Balandin, Y KoucheryavyTitle of proceedings
ruSMART 2017, NsCC 2017, NEW2AN 2017 : Proceedings of the 2017 10th Conference on Internet of Things and Smart Spaces, the Third International Workshop on Nano-scale Computing and Communications and the 17th International Conference on Next Generation Wired/Wireless NetworkingUsage metrics
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