Urban fire risk dynamic prediction monitoring method and system

Abstract

The invention provides an urban fire risk dynamic prediction monitoring method and system. The method comprises the steps that 1 based on prior knowledge and collected relevant fire data, disaster-inducing factors associated with fire are determined, and massive fire cases and disaster-inducing factor data corresponding to the cases are collected to generate an original data training set; 2 disaster-inducing factors highly associated with the fire probability are screened out; 3 data preprocessing is carried out on the highly associated disaster-inducing factors; 4 according to a data training set generated by data preprocessing, an urban fire dynamic prediction model is built; and 5 the dynamic fire risk level based on model prediction is associated with a building model as an attribute value to update the fire risk level of a building. The urban fire risk dynamic prediction monitoring method and system have the advantages of high prediction result accuracy, high credibility and clear result, and use a data visualization technology in combination with two-dimensional and three-dimensional maps.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a method and system for dynamic prediction and monitoring of urban fire hazards. Background technique [0002] With the development of cities, the resident population of large and medium-sized cities has increased rapidly, and the "three old" areas have a large area to be renovated. The high-density population and large-area fire hazard gathering places have brought great difficulty to monitoring fire safety. At the same time, as cities continue to develop towards digitization, intelligence, and intelligence, the sources of data are becoming more and more diverse, and the content contained in the data is becoming more and more abundant. How to screen out reasonable and accurate disaster-causing factors in the face of massive amounts of data? Detection is also a great challenge. The current urban fire remote monitoring system is complex in structure and very simple in fun...

AI Technical Summary

Problems solved by technology

Generally speaking, this type of system has a single source of data, and it is difficult to perform in-depth data processing, and cannot effectively predict fire hazards, let alone support fire rescue plans

[0003] In the context of the era of big data, with the continuous development of information technology and the continuous improvement of the application level of urban informatization, the construction of smart cities has emerged as the times require. The system cannot meet the fire protection needs of smart cities

Images