Abstract
In monitoring applications the accuracy of data is paramount. When considering wireless sensor networks the quality of readings taken from the environment may be hampered by outliers in raw data collected from transmitters attached to nodes’ analogue-to-digital converter ports. To improve the data quality sent to the base-station, a real-time data analysis should be implemented at nodes’ level, while taking into account their computing power and storage limitations. This paper deals with the problem of outliers detection and accommodation in raw data. The proposed approach relies on univariate statistics within an hierarchical multi-agent framework. Results from experiments on a real monitoring scenario, at a major oil refinery plant, show the relevance of the proposed approach.
Original language | English |
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Title of host publication | Proceedings of IACSIT Hong Kong Conferences |
Place of Publication | Hong Kong |
Pages | 321-327 |
Number of pages | 7 |
DOIs | |
Publication status | Published - 1 Jan 2014 |
Event | 6th International Conference on Computer Technology and Development (ICCTD) - Duration: 1 Jan 2014 → … |
Conference
Conference | 6th International Conference on Computer Technology and Development (ICCTD) |
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Period | 1/01/14 → … |
Keywords
- wireless sensor networks
- multi-agent systems
- Oil refinery plant
- real-time monitoring
- outliers detection and accommodation