Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/1097
Title: A methodology for extracting temporal properties from sensor network data streams
Authors: Lymberopoulos, Dimitrios K.
Bamis, Athanasios
Savvides, Andreas 
Issue Date: 2009
Publisher: ACM
Source: Proceedings of the 7th international conference on Mobile systems, applications, and services, 2009.pp 193-206
Abstract: The extraction of temporal characteristics from sensor data streams can reveal important properties about the sensed events. Knowledge of temporal characteristics in applications where sensed events tend to periodically repeat, can provide a great deal of information towards identifying patterns, building models and using the timing information to actuate and provide services. In this paper we outline a methodology for extracting the temporal properties, in terms of start time and duration, of sensor data streams that can be used in applications such as human, habitat, environmental and traffic monitoring where sensed events repeat over a time window. Its application is demonstrated on a 30-day dataset collected from one of our assisted living sensor network deployments.
URI: http://ktisis.cut.ac.cy/handle/10488/1097
http://hdl.handle.net/10488/1097
ISBN: 9781605585666
DOI: http://doi.acm.org/10.1145/1555816.1555836
Rights: © 2009 ACM, Inc.
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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