Condition Monitoring for Wireless Sensor Network-Based Automatic Weather Stations
Journal Title: EAI Endorsed Transactions on Internet of Things - Year 2018, Vol 4, Issue 14
Abstract
Wireless Sensor Network (WSN)-based Automatic Weather Stations (AWSs) perform automatic collection and transmission of weather data. These AWSs face challenges, which lower their performance. Hence, a need for regular monitoring to reduce down time. We propose condition monitoring, comprised of a data receiver, analyser, problem classifier and reporter and visualizer, to mine data relationships, identify possible causes of problems and perform reporting of AWS status. The data receiver uses an M/M/1/k queuing model. We use Successive Pairwise REcord Differences (SPREDs) algorithm to compare arrival rates and packet content so as to establish sensor, node and AWS level performance. We also perform a hybrid of Grubb outlier detection and correlations amongst related variables for data validation. Problems take on one of four states. One connection can receive data at a rate as low as 1ms, without loss while problem identification especially in high density network is improved.
Authors and Affiliations
Mary Nsabagwa, Julianne Sansa Otim, Roseline Nyongarwizi Akol, Grace Ninsiima, Robert Mwesigye, Maximus Byamukama, Björn Pehrson
Keywords
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- EP ID EP46614
- DOI http://dx.doi.org/10.4108/eai.20-12-2018.156083
- Views 246
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