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Anomaly Detection in Streaming Sensor Data
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Author(s): Alec Pawling (University of Notre Dame, USA), Ping Yan (University of Notre Dame, USA), Julián Candia (Northeastern University, USA), Tim Schoenharl (University of Notre Dame, USA)and Greg Madey (University of Notre Dame, USA)
Copyright: 2012
Pages: 19
Source title:
Wireless Technologies: Concepts, Methodologies, Tools and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-61350-101-6.ch403
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Abstract
This chapter considers a cell phone network as a set of automatically deployed sensors that records movement and interaction patterns of the population. The authors discuss methods for detecting anomalies in the streaming data produced by the cell phone network. The authors motivate this discussion by describing the Wireless Phone Based Emergency Response (WIPER) system, a proof-of-concept decision support system for emergency response managers. This chapter also discusses some of the scientific work enabled by this type of sensor data and the related privacy issues. The authors describe scientific studies that use the cell phone data set and steps we have taken to ensure the security of the data. The authors also describe the overall decision support system and discuss three methods of anomaly detection that they have applied to the data.
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