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|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|
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