NDLI: Finding abnormal events in home sensor network environment using correlation graph

Content Provider	IEEE Xplore Digital Library
Author	Huey-Ming Lee Ching-Hao Mao
Copyright Year	2009
Description	Author affiliation: Department of Information Management, Chinese Culture University, Taipei, Taiwan (Huey-Ming Lee; Ching-Hao Mao)
Abstract	Anomaly detection in sensor network seems a challenge when encountering the limitation of the energy requirement and dynamics environments. It is to rapidly analyze and identify the abnormal events among the extreme volume data. Using correlation graph representation to correlate the events generated by sensor networks is capable to find the intentional dependency behavior's insight for detecting home sensor network abnormal events. In this study, we proposed an anomaly detection mechanism based on correlation graphs of sensor networks for rapidly identifying abnormal home events. The proposed mechanism which makes the following contributions: (a) it is automatically identify the abnormal event under home sensor network environment (b) it eliminates irrelevant events for saving the computation power (c) it is easily to apply on different machine learning classifiers for enhancement. The evaluation from Intel Berkeley Research lab sensor network data set. The proposed mechanism performs well in sensor events elimination and abnormal event detection.
Starting Page	1852
Ending Page	1856
File Size	231456
Page Count	5
File Format	PDF
ISBN	9781424427932
ISSN	1062922X
DOI	10.1109/ICSMC.2009.5346248
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Event detection Home appliances Intelligent sensors Intelligent agent Home automation Computer networks Fuzzy neural networks Sensor systems Information management Internet artificial intelligent Sensor network correlation graph anomaly detection information applicances
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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