Contextual reasoning under uncertainty in sensor data stream monitoring

Kolomvatsos, K., Anagnostopoulos, C. and Hadjiefthymiades, S. (2016) Contextual reasoning under uncertainty in sensor data stream monitoring. International Journal of Monitoring and Surveillance Technologies Research (IJMSTR), 3(2), pp. 1-19. (doi: 10.4018/IJMSTR.2015040101)

Abstract

Contextual data streams monitoring plays an important role in the identification of abnormalities in many application domains. Abnormalities are related to negative effects that, consequently, affect people’s quality of living. A number of sensors could be placed in various locations undertaking the responsibility of monitoring specific phenomena. Sensors report their measurements to a central system that is capable of situational reasoning. The system, through decision making, responds to any event related to the observed phenomena. In this paper, we propose a mechanism that builds on top of the sensors measurements and derives the appropriate decisions for the immediate identification of events. The proposed system adopts data fusion and prediction (time series regression) methods for efficiently aggregating sensors observations. We also adopt Fuzzy Logic for handling the uncertainty on the decision making. We perform a set of simulations over real data and report on the advantages and disadvantages of the proposed system.

• Item Type: Articles
• Additional Information: This work has been co‐financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) in the scope of the Research Funding Program: THALES-UOA-Sensor Web Fire Shield (SWeFS). .D.: 180 THALIS Mis: 375785 NSRF Code: Diavgeia: ΑΔΑ: Β4ΩΚ9-Ν5Δ Link: http://excellence.minedu.gov.gr/thales/en/thalesprojects/375785
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Anagnostopoulos, Dr Christos and Kolomvatsos, Dr Kostas
• Authors: Kolomvatsos, K., Anagnostopoulos, C., and Hadjiefthymiades, S.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: International Journal of Monitoring and Surveillance Technologies Research (IJMSTR)
• Publisher: IGI Global
• ISSN: 2166-7241
• ISSN (Online): 2166-725X