Design And Application Of A Complex Event Processing Based Approach Of Target Level Data Fusion

The Internet of Things(IoT)has been widely applied in sensing systems,which connects various sensors and gathers their information.Data fusion,which is to integrate multiple data representing the same real-world object into a consistent and accurate representation,is an important issue.Most of existing approaches of data fusion involve various analytical procedures whose high computational complexity usually require massive computing resources.In this paper,an efficient data fusion approach is proposed.Stochastic models are presented to describe the measurements of detecting data,and quantitative analyses are given to evaluate the efficiency of data fusion.Complex event processing engine is applied to improve the efficiency of data transmission and processing to meet the real-time demands.Finally,simulation experiments are conducted to validate the efficacy of the approach.This paper introduces how to design and apply the above mentioned target recognition algorithm and complex event processing technology in a home security surveillance system.Home security surveillance system is a system based on multiple sensors network,and its main function is to monitor the house around to see whether there is any unknown target,in order to ensure the indoor safety conditions.This paper introduces system requirement analysis,system design,system implementation and testing sections.Three modules of the systemare implemented,which are:target recognition algorithm module,complex event processing module and user interface module.All the modules are developed by the Java language,and the complex event processing module takes use of one open source complex Event processing engine Esper and Event Processing Language(EPL).Besides,the user interface module is implemented based on the Java EE platform,using the SSH framework to access data,and using HTML5+CSS3+JavaScript technology for the visual display of the sensor data.Finally,the system is tested form both functional and performance aspects,which validates the effectiveness and efficiency of the approach.