Research And Design Of Smart Home Security Based On Multi-sensor Data Fusion

As the pace of modern life accelerates and work pressure increases,more and more people are eager to have a safe,comfortable and intelligent haven.With the rapid development of Internet of Things,wireless communication,embedded technology and data fusion,which has made this wish possible,so that the intelligent and secure home life no longer out of reach.In order to meet the current needs of smart home security,and taking into account some of the shortcomings of today’s smart home security,this paper presents a smart home security detection method based on multi-sensor data fusion to monitor home abnormalities in real time.Installing fire sensors,gas leaks and anti-theft sensor detection devices at home,and at the same time,the intelligent gateway uses the data fusion algorithm to fuse the data collected by these sensors to get the final abnormal result.While the user can log on the phone client to view the home security situation in real time,which including the time and type of abnormalities,as well as exceptionally abnormal scene shot.The main research work and innovation of this paper are as follows:(1)Most smart home security system detection modules only based on the data detected by a single sensor to determine whether it is anomalies,especially the detection of fire,which make the result be not accurate,there are false alarm and missed alarm situation.In this paper,the detection method based on multi-sensor data fusion is proposed to monitor the fire,gas and infrared in the home.The multi-sensor data fusion method is used to fuse the data collected by the sensor.Finally,the decision result is obtained through the fusion process.The simulation test shows that the method has high detection accuracy and has certain feasibility.(2)Although the neural network can have the function of self-organizing learning and self-adaptation,it also has some shortcomings of local optimization.However,fuzzy logic reasoning has the ability of imitating people’s comprehensive judgment reasoning,but not self-organizing learning ability.The advantages and disadvantages of complementarity to be combined,thereby improving the accuracy of the algorithm.(3)Construction of real-time monitoring and alarm platform for smart home security based on multi-sensor data fusion.The use of multi-sensor detection module for real-time monitoring of fire,gas,and human infrared at home.Then the data detected by the system is sent to the data fusion center for processing.The results of the processing are uploaded to the cloud through the Ethernet.When an abnormal situation occurs,the user can check the abnormal alarm result by logging in to the mobile client.In summary,this paper presents a smart home security detection method based on multi-sensor data fusion,which can accurately detect the abnormal conditions in home,and timely alarm and early warning of abnormal conditions,suitable for smart home security detection.