Heat Analysis Based On Fire Monitoring Data Tiered Storage Technique And Its Applications

Fire-fighting monitoring data can reflect the operating status and overall situation of each fire-fighting equipment on site,provide fire protection decision-making evidence for people,and get various fire-fighting monitoring data on site without missing important information,which plays an important role in the reliably operation of fire-fighting devices and system.However,from the existing types of fire-fighting monitoring and collection mechanisms and fire information systems,there's no difference in unified monitoring data push and storage mechanism from general information systems.The interactive resource allocation strategy of monitoring data is not reasonable,this will lead the packet loss and interactive response slowly and so on in the real-time monitoring activities.Therefore,people want to make rational strategies in the planning of storage resources for the firefighting data,in order to satisfy the real-time need in the application of fire-fighting monitoring data.This article takes the fire-fighting water system,aiming at the small sample and atypical real-time heterogeneous monitoring data in its monitoring system.Based on the idea of modular design,we design a functional structure which can be used to dynamically allocate storage resource and timely push monitoring data.Based on the structure,we utilize the expert evaluation method to pretreat and sort the real-time data,and we build the data-heat calculation model and use it to analyze the heat of monitoring data,get the sorting result of monitoring data heat and make relative strategies for storage resource allocation.This method ensures the faster access efficiency and lift up the performance of real-time interaction.And we research the fire-fighting monitoring information platform and design and implement a software platform,which is meaningful in monitoring system operation record,data analysis and implement accurate control decision.We arrange our main content in this article based on research of fire-fighting water monitoring system and data-heat calculation theory.According to the real-time interaction need and the feature of monitoring data in this system,we define our data-heat using the time difference and the level of abnormal data as the key indicators,and set adjustable coefficient for these two indicators.With expert evaluation method we get the data-heat sorted result,and then we use regression analysis to determine the 2 adjustable indicators based on the sorted result from expert evaluation method.And we get the final formula of data-heat and use it to calculate the data-heat of all monitoring data,and also get the sorted result.Compared with the expert evaluation method in the reverse order number's quantity,we can verify that the correct rate is high enough to calculate the data-heat and make the right sorting data.Then we divide the storage into two parts which has the faster read/writing speed stores the hot-data,and in contrast the storage district which has slower read/writing speed stores the other data.And we test the access performance and prove that the two parts storing strategy make the data access performance better.Finally,we design a software platform in line with the fire-fighting monitoring function and data analysis need,and introduce the platform in details.