Complex event detection in an intelligent surveillance system using CAISER platform
Rabiah Adawiyah Shahad, Leow Gaen Bein, Mohamad Hanif Md Saad, Aini Hussain · 2016
Interest about security and asset safety escalates due to the increasing crimes in this century. However, almost all existing surveillance systems have limited self-learning ability that only allow real time monitoring and are unable to identify the actual events that take place in the monitored ambient. As such, this research aims to implement a smart surveillance system with embedded Complex Event Processing (CEP) technology to assist the intrusion detection by correlating raw data extracted from different sources. Four classifiers are used in the CEP engine to predict the event occurrences from the raw data sequence pattern acquired from the door sensors and surveillance camera via intelligent rule template matching algorithm. Confusion matrix in terms of sensitivity, specificity and average detection accuracy as well as ROC plot are employed in classifier performance evaluation to quantify the efficiency of the surveillance system developed.