Please use this identifier to cite or link to this item:
|Title:||Modeling and detecting events for sensor networks|
|Citation:||Xue, W., Luo, Q., Pung, H.K. (2011). Modeling and detecting events for sensor networks. Information Fusion 12 (3) : 176-186. ScholarBank@NUS Repository. https://doi.org/10.1016/j.inffus.2010.11.001|
|Abstract:||Event detection is an essential element for various sensor network applications, such as disaster alarm and object tracking. In this paper, we propose a novel approach to model and detect events of interest in sensor networks. Our approach models an event using the kind of spatio-temporal sensor data distribution it generates, and specifies such distribution as a number of regression models over spatial regions within the network coverage at discrete points in time. The event is detected by matching the modeled distribution with the real-time sensor data collected at a gateway. Because the construction of a regression model is computation-intensive, we utilize the temporal data correlation in a region as well as the spatial relationships of multiple regions to maintain the models over these regions incrementally. Our evaluation results based on both real-world and synthetic data sets demonstrate the effectiveness and efficiency of our approach. © 2010 Elsevier B.V. All rights reserved.|
|Source Title:||Information Fusion|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on May 20, 2018
WEB OF SCIENCETM
checked on Apr 10, 2018
checked on Mar 12, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.