Paper Info
Title
DisCPAQ: Distributed Context Acquisition and Reasoning for Personalized Indoor Air Quality Monitoring in IoT-Based Systems.
Abstract
The 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.
Year
Venue
Field
2017
NEW2AN
Data stream mining,Architecture,Computer science,Context model,Context awareness,Air quality index,Multimedia,Indoor air quality,Wireless sensor network,Environmental monitoring
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
7
5
Name
Order
Citations
PageRank
Tamara Belyakhina100.34
Arkady B. Zaslavsky2943168.27
Karan Mitra316917.84
Saguna, S.4135.07
Prem Prakash Jayaraman537844.66