INTELLIGENT RESPONSIVE INDOOR SYSTEM (IRIS): A POTENTIAL SHOPLIFTER SECURITY ALERT SYSTEM

Authors

  • Mohamad Kuzahier Mohd Zahari School of Computer Sciences Universiti Sains Malaysia, Malaysia
  • Zarul Fitri Zaaba School of Computer Sciences Universiti Sains Malaysia, Malaysia

Keywords:

Security, face recognition, biometrics, security alerts, intelligent system, Human Computer Interaction

Abstract

Shoplifting can occur at any time and any place. From the big mall to a small shop, many security measures have been put in place as prevention tools. Apparently, there are numbers of shoplifting prevention tools in the market such as the Closedcircuit Television (CCTV), Electronic Article Surveillance (EAS) and Future Attribute Screening Technology (FAST). However, the cost issues and the ease of use always become the main concerns for the shopkeepers. Therefore CCTV was widely accepted because of the ease and affordable price. Although the CCTV is their main preference, it can be noted that CCTV operates in a static way where it can only records and monitor the incidents. This paper highlights the conventional CCTV issues and proposes the Intelligent Responsive Indoor System (IRiS) the as security crime prevention tool that uses face detection, recognition and behavior analysis to detect potential shoplifting intentions. Six small shop owners were interviewed to understand their insights on the problems and the need to further enhance the current CCTV. In addition, detailed discussions were provided in relation to the development of IRiS. Therefore, it can be suggested that IRiS provides a significant foundation and promises to be a security prevention tool to improve the conventional functions of the CCTV.

 

Additional Files

Published

06-11-2017

How to Cite

Mohd Zahari, M. K., & Zaaba, Z. F. (2017). INTELLIGENT RESPONSIVE INDOOR SYSTEM (IRIS): A POTENTIAL SHOPLIFTER SECURITY ALERT SYSTEM. Journal of Information and Communication Technology, 16(2), 262–282. Retrieved from https://e-journal.uum.edu.my/index.php/jict/article/view/8232