Research On Fire Monitoring Personnel Location System Based On WiFi Fingerprint

In the context of the accelerated advancement of industrial intelligence,the AI intelligent auxiliary fire monitoring robot developed in response to the actual hot-work monitoring needs of the industrial site,which improved the safety production efficiency of industrial enterprises and relieved the pressure of fire monitoring staff.After the auxiliary fire-monitoring robot put into use in the factory,hot-work monitoring personnel relied heavily on the fire-monitoring robot,the activity area was not compliant,The inspection was not carried out as required.In order to improve the safety production efficiency of enterprises,a positioning method based on WiFi fingerprints is proposed and a positioning system is designed.The specific research content are as follows:(1)To solve the problem of low positioning accuracy caused by single-view clustering in WiFi fingerprint location based on clustering method,a WiFi fingerprint location method based on multi-view clustering is proposed.The threshold mean filtering is employed to process the original data,and K-means clustering with multi-view is used to partition multiple signal(RSSI and position).The basic classifier partitions the test signal,and K nearest signal points are obtained in the region according to the classification results.Then,the actual position of the signal is determined by the neighbors and the corresponding weight values.In experiments,one can see that the probability of WiFi fingerprint positioning accuracy within 4 meters is 83%,which is 12% higher than that of single view(RSSI or position).The results show that this method improves the positioning accuracy and provides a variety of ideas for the research of positioning field.(2)Aiming at the actual monitoring needs of complex industrial sites,a tracking system for hot-work monitoring personnel is designed.It mainly includes the design of the overall architecture of the positioning system,module development and experimental environment construction and test verification analysis.In the early stage,the built WiFi fingerprint library is written to the mobile terminal server and the positioning calculation algorithm is integrated on the device side.and the positioning and solving process is integrated in the device,which reduces the amount of calculation and shortens the time of data return,and improves the real-time performance of the system;The system uses multi-view clustering fingerprint positioning method to establish database,and then achieve the purpose of positioning.Its operation process is simple and easy to achieve,and the positioning accuracy is relatively high.According to the analysis of the positioning results,the system makes the inspection frequency,inspection track,inspection time and other parameters of the hot work monitoring personnel online attention,convenient for historical query,problem tracing and employee assessment,restricts the work behavior of the hot work monitoring personnel,improves the safety production coefficient of the enterprise and the high-level management system of the enterprise,and basically meets the development needs of the hot-work monitoring personnel positioning system.