Intelligent surveillance system with integration of heterogeneous information for intrusion detection

  • Authors:

  • J. L. Castro;M. Delgado;J. Medina;M. D. Ruiz-Lozano

  • Affiliations:

  • University of Granada, School of Computer Science, Department of Computer Science and Artificial Intelligent, C/Periodista Daniel Saucedo Aranda s/n E-18071, Granada, Spain;University of Granada, School of Computer Science, Department of Computer Science and Artificial Intelligent, C/Periodista Daniel Saucedo Aranda s/n E-18071, Granada, Spain;University of Granada, School of Computer Science, Department of Computer Science and Artificial Intelligent, C/Periodista Daniel Saucedo Aranda s/n E-18071, Granada, Spain;University of Granada, School of Computer Science, Department of Computer Science and Artificial Intelligent, C/Periodista Daniel Saucedo Aranda s/n E-18071, Granada, Spain

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2011

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Abstract

Recently, interest about security in public and private spaces has increased in favour of social welfare. Surveillance systems are increasingly needed to provide security for citizens and infrastructures. Currently there are many buildings that are equipped with cameras, sensors or microphones. However, it is difficult to find tools that integrate the information from these sources in a homogeneous system. On the other hand, the intruder detection is increasingly demanded in the corporate, commercial or private sector. For these reasons, we propose a multi-sensor intelligent system that uses information from several sources analysis (video, audio and other sensors) to identify dangerous or interest intrusions. So, we have designed a generic ontology that allows to integrate in a homogeneous way all the input heterogeneous knowledge. To perform the intrusion analysis, we propose a rule-based model, which process all the information obtained from the monitored environment. This model is easily customizable and adjustable, since the rules that define an intrusion in a semantic way can be configured depending on the scenario and circumstances. The system generates an alarm whenever an intrusion is detected. Besides, this alarm is also notified via mobile devices. So, the system reports in real time according to device capabilities, generating a context-sensitive notification.