A building disaster rescue planning system based on BIM

Abstract

The application discloses a kind of building disaster relief planning systems based on BIM, belong to building fire safety technical field, including building BIM module, internet of things sensor acquisition module and video acquisition module, the building BIM module is used to provide building information model, namely BIM, the internet of things sensor acquisition module is used to real-time acquisition building internal environment information, the video acquisition module is used to real-time acquisition building internal video image information, the system further includes disaster analysis module, virtual real scene display module and disaster command dispatch module, the disaster analysis module is used to analyze the information of building BIM module, internet of things sensor acquisition module and video acquisition module, and judges the trend of disaster development;The virtual real scene display module is used to show the result of disaster analysis module;The disaster command dispatch module is used to issue command dispatch information;The present application can effectively predict the trend of disaster development, provide more accurate guidance for rescue, thereby improve the probability of successful rescue.

Description

Technical Field

[0001] This invention patent belongs to the field of building fire safety technology, specifically relating to a BIM-based building disaster relief planning system. Background Technology

[0002] Building Information Modeling (BIM) uses various relevant information and data about a building as the foundation for creating a building model. It simulates the building's actual information through digital information. BIM encompasses information such as geometry, spatial relationships, geographic information systems, and the properties and quantities of various building components. The creation of BIM models provides a reference and simulation basis for planning emergency rescue plans for buildings.

[0003] The rapid development of IoT sensor technology and its widespread application in buildings provide a basis for data analysis and judgment to effectively understand the specific situation inside buildings in the event of a disaster.

[0004] Chinese invention patent CN115171321A discloses a BIM-based intelligent fire management system, comprising: a space construction module; a video monitoring module; an image processing module for analyzing image frames to obtain image information; a coordinate statistical analysis module for obtaining the number of people N corresponding to the access destination coordinate P; a fire detection module for real-time monitoring of the fire situation at the detection node location; a disaster analysis module for analyzing the fire situation at the detection node location and obtaining the coordinates of the fire impact range; and a route analysis module for determining the safety factor s of the escape route coordinates. i Sort by size from largest to smallest; Evacuation instruction module, used to instruct personnel on evacuation.

[0005] The aforementioned invention patent, while applying BIM to a fire management system, only provides basic building information. Its disaster analysis module only roughly provides the coordinates of the fire impact range based on the temperature monitored on-site. The route analysis module provides the safest escape route, which has some guiding role in disaster relief and escape. However, most importantly, its disaster analysis module does not combine real-time building information obtained from other modules with detailed building information provided by BIM to analyze and judge the development trend of the disaster. It only provides a broad fire impact range coordinate. The escape route with the highest safety factor provided by the entire system may still be unsafe, reducing the chance of successful rescue. Summary of the Invention

[0006] The purpose of this invention is to solve the problems mentioned in the background art and provide a BIM-based building disaster relief planning system that can effectively predict the development trend of disasters, provide more accurate guidance for rescue, and thus improve the success rate of rescue.

[0007] To achieve the above-mentioned technical objectives, the technical solution adopted by the present invention is as follows:

[0008] A BIM-based building disaster relief planning system includes a building BIM module, an IoT sensor acquisition module, and a video acquisition module. The building BIM module provides a building information model (BIM). The IoT sensor acquisition module collects real-time information about the building's interior environment. The video acquisition module collects real-time video images of the building's interior. The system also includes a disaster analysis module, a virtual reality display module, and a disaster command and dispatch module. The disaster analysis module analyzes the information from the building BIM module, the IoT sensor acquisition module, and the video acquisition module, and predicts the development trend of the disaster. The virtual reality display module displays the results of the disaster analysis module. The disaster command and dispatch module issues command and dispatch information.

[0009] Preferably, the disaster command and dispatch module allows commanders to issue command and dispatch information based on the information displayed by the virtual reality display module and their rescue experience.

[0010] Preferably, the BIM includes a digitized model of building structure information, building material information, building spatial geometry information, building pipeline information, building cable information, and building equipment information.

[0011] Preferably, the environmental information includes information on temperature, humidity, smoke concentration, toxic gases, and the presence or absence of personnel.

[0012] Preferably, the disaster analysis module combines the real-time environmental information of dynamic changes within the building collected by the IoT sensor acquisition module and the real-time video image information collected by the video acquisition module with the building BIM module to complete a comprehensive analysis of the trapped personnel and the distribution of the disaster. Based on this analysis, and combined with the detailed building information in the building BIM module, the module predicts the development trend of the disaster.

[0013] Preferably, the virtual reality display module displays the disaster analysis module's assessment of the distribution of trapped personnel and the disaster situation, as well as its prediction of the disaster's development.

[0014] Preferably, the virtual reality display module includes a mobile terminal, a PC terminal, a VR or AR terminal.

[0015] Preferably, the disaster analysis module includes a video analysis server, a data aggregation and analysis server, and a disaster analysis server. The video analysis server is used to analyze and identify real-time video image information; the data aggregation and analysis server is used for area division and estimation of blind spot information of the video acquisition module; and the disaster analysis server is used to combine BIM, environmental information, and information analyzed and identified by the video analysis server to simulate and judge the development trend of the disaster.

[0016] The beneficial effects of this invention are:

[0017] The disaster analysis module, by combining real-time building information collected by the IoT sensor acquisition module and video acquisition module with detailed building information provided by the building BIM module, can scientifically and effectively determine the development trend of the disaster. Compared with existing technologies, it can more effectively determine safe rescue routes and increase the chances of successful rescue. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the system modules of the present invention;

[0019] Figure 2 This is a schematic diagram showing the distribution of sensors and video acquisition devices within the building;

[0020] Figure 3 This is a flowchart analyzing the distribution of people trapped inside the building;

[0021] Figure 4 This is a flowchart for disaster risk analysis within buildings;

[0022] Figure 5 It is a flowchart of disaster relief planning within a building. Detailed Implementation

[0023] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0024] It should be noted that the terms such as "upper", "lower", "left", "right", "front", and "back" used in the invention are only for clarity of description and are not intended to limit the scope of the invention. Changes or adjustments to their relative relationships, without substantially altering the technical content, should also be considered within the scope of the invention.

[0025] like Figure 1 As shown, a BIM-based building disaster relief planning system includes a building BIM module, an IoT sensor acquisition module, a video acquisition module, a disaster analysis module, a virtual reality display module, and a disaster command and dispatch module.

[0026] The building BIM module is used to provide building information model, which includes a data model of building-related information such as building structure information, building material information, building spatial geometry information, building pipeline information, building cable information, and building equipment information, providing detailed reference for disaster analysis and rescue plan formulation;

[0027] The IoT sensor acquisition module is used to collect real-time environmental information inside the building, including information on temperature, humidity, smoke concentration, toxic gases, and the presence or absence of people. The collected information is then sent to the disaster analysis module for comprehensive analysis.

[0028] The video acquisition module is used to acquire video image information of the area covered by the camera equipment inside the building in real time, and send the acquired video information to the disaster analysis module for comprehensive analysis.

[0029] The disaster analysis module combines real-time environmental information collected by the IoT sensor acquisition module and real-time video image information collected by the video acquisition module with the building BIM module to conduct a comprehensive analysis of the trapped personnel and the distribution of the disaster. Based on this analysis and the detailed building information in the building BIM module, it predicts the development trend of the disaster. The disaster analysis module includes a video analysis server, a data aggregation and analysis server, and a disaster analysis server. The video analysis server is used to analyze and identify real-time video image information. The data aggregation and analysis server is used for area division and estimation of blind spots of the video acquisition module. The disaster analysis server is used to simulate and judge the development trend of the disaster by combining BIM, environmental information, and video image information.

[0030] The virtual reality display module is used to display the results of the disaster analysis module on the distribution of trapped people and the disaster situation and the prediction of the disaster development; the virtual reality display module includes, but is not limited to, mobile terminals such as mobile phones, PC terminals, large-screen command terminals and VR / AR terminals.

[0031] The disaster command and dispatch module is used by commanders to issue command and dispatch information based on the information displayed by the virtual reality display module and their rescue experience.

[0032] The operation of this system is illustrated below using specific embodiments.

[0033] like Figure 2 As shown, several video surveillance devices and sensors are installed on each floor of the building to collect images and environmental information within the building.

[0034] like Figure 3 As shown, this system analyzes the distribution of trapped people inside a building through the following steps.

[0035] Step 1: The video surveillance equipment of the video acquisition module and the sensors of the IoT sensor acquisition module collect real-time information on the movement of people in the building, and send the collected video stream information to the video analysis server.

[0036] Step 2: The video analysis server uses facial and behavioral analysis to identify people and their directions, identifies each person individually, generates their corresponding path information, and sends it to the data aggregation and analysis server.

[0037] Step 3: Data aggregation and analysis server. First, the area is divided according to the normal situation of video surveillance. Then, the information recognition results of the video analysis server are combined with the personnel information of each area to calculate the personnel distribution of each area.

[0038] Step 4: The data aggregation and analysis server uses historical video analysis results and data from human body recognition sensors to estimate the distribution of people in the video blind spots.

[0039] Step 5: Display the distribution of trapped personnel based on data aggregation and analysis on the BIM using the virtual reality display module. This includes marking the area division, key blind spots, personnel area distribution, and estimated personnel distribution in blind spots, providing a reference for rescue personnel to organize rescue efforts and collect personnel information.

[0040] like Figure 4 As shown, this system analyzes the distribution of disasters within a building and predicts the development trend of disasters through the following steps.

[0041] Step 1: Collect real-time disaster data and related environmental data within the building using video surveillance equipment and sensors, and transmit them to the disaster analysis module.

[0042] Step 2: The video analysis server analyzes and identifies the flame situation, smoke situation, liquid flow direction, crack location and trend through flame recognition, smoke recognition, liquid recognition, crack recognition, etc., and transmits the relevant data to the disaster analysis server of the disaster analysis module.

[0043] Step 3: The disaster analysis server analyzes the building's terrain elevation, building materials, fire prevention measures, ventilation direction, and storage conditions using BIM information to identify flammable and explosive materials that could cause toxic gas spread (this mainly considers all stored items, building materials, decorations, and whether fire prevention measures are in place). Combined with information from the video analysis server regarding flame direction, liquid flow direction, and crack tendencies, the direction of the flames is determined. Environmental data such as airflow direction, smoke concentration, temperature, and humidity are also used to assess the detailed situation inside the building, identifying the most likely location for a new fire and simulating the scenario. Based on the comprehensive simulation analysis of these three types of information, and considering the possible disaster scenarios under the current development trend, the disaster trend prediction is finally completed.

[0044] like Figure 5 As shown in the rescue planning section, based on the analysis of the previous two steps, the distribution of trapped personnel and the disaster situation, as well as the development trend of the disaster (the same parts will not be repeated), are used to formulate a rescue plan:

[0045] Based on the distribution of trapped personnel, the current state and development trend of the disaster, the risks and scope of impact, building BIM information (i.e., existing internal routes and feasible routes), and combined with the comprehensive analysis and planning of rescue plans by rescue experts at the command center and historical rescue cases, the rescue team is given real-time instructions through the disaster command and dispatch module to guide the rescue implementation.

[0046] In conjunction with the execution of disaster relief efforts and the distribution of rescue teams, iterative simulation analysis is conducted on the disaster analysis server to complete real-time prediction and analysis of disaster trends, detection and warning of probabilistic events, real-time tracking of the rescue process, and full guidance until the rescue is successful.

[0047] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A BIM-based building disaster relief planning system, comprising a building BIM module, an IoT sensor acquisition module, and a video acquisition module, wherein the building BIM module is used to provide a building information model (BIM), the IoT sensor acquisition module is used to acquire real-time building interior environmental information, and the video acquisition module is used to acquire real-time video image information of the building interior, characterized in that: The system also includes a disaster analysis module, a virtual reality display module, and a disaster command and dispatch module. The disaster analysis module is used to analyze information from the building BIM module, the Internet of Things sensor acquisition module, and the video acquisition module, and to predict the development trend of the disaster. The virtual reality display module is used to display the results of the disaster analysis module; the disaster command and dispatch module is used to release command and dispatch information. The disaster analysis module combines the real-time environmental information of the building dynamic changes collected by the IoT sensor acquisition module and the real-time video image information collected by the video acquisition module with the building BIM module to complete a comprehensive analysis of the trapped personnel and the distribution of the disaster. Based on this analysis and combined with the detailed building information in the building BIM module, the module predicts the development trend of the disaster. The disaster analysis module includes a video analysis server, a data aggregation and analysis server, and a disaster analysis server. The video analysis server is used to analyze and identify real-time video image information. The data aggregation and analysis server is used for area division and estimation of blind spot information of the video acquisition module. The disaster analysis server is used to combine BIM, environmental information, and information analyzed and identified by the video analysis server to simulate and judge the development trend of the disaster. Specifically, the prediction of the disaster situation's development trend includes: Step 1: Collect real-time disaster data and related environmental data inside the building through video surveillance equipment and sensors, and transmit them to the disaster analysis module; Step 2: The video analysis server analyzes and identifies the flame situation, smoke situation, liquid flow direction, and crack location and trend through flame recognition, smoke recognition, liquid recognition, and crack recognition, and transmits the relevant data to the disaster analysis server of the disaster analysis module. Step 3: The disaster analysis server analyzes the building's elevation, building materials, fire prevention measures, ventilation, and storage conditions using BIM information to identify flammable and explosive materials that could cause toxic gas spread. Combined with information from the video analysis server regarding flame direction, liquid flow, and crack tendencies, it determines the flame's direction. Environmental data such as airflow direction, smoke concentration, temperature, and humidity information are used to assess the detailed situation inside the building, identifying the most likely location for a new fire and conducting scenario simulations. Based on the comprehensive simulation analysis of these three types of information, and considering the potential disaster scenarios under the current development trend, a disaster trend prediction is ultimately completed. The comprehensive analysis of trapped personnel includes: Step 1: The video surveillance equipment of the video acquisition module and the sensors of the IoT sensor acquisition module collect real-time information on the movement of people in the building, and send the collected video stream information to the video analysis server. Step 2: The video analysis server uses facial and behavioral analysis to identify people and their directions, identifies each person individually, generates their corresponding path information, and sends it to the data aggregation and analysis server. Step 3: Data aggregation and analysis server. First, the area is divided according to the normal situation of video surveillance. Then, the information recognition results of the video analysis server are combined with the personnel information of each area to calculate the personnel distribution of each area. Step 4: The data aggregation and analysis server uses historical video analysis results and data from human body recognition sensors to estimate the distribution of people in the video blind spots. Step 5: Display the distribution of trapped personnel based on data aggregation and analysis on the BIM using the virtual reality display module. This includes marking the area division, key blind spots, personnel area distribution, and estimated personnel distribution in blind spots, providing a reference for rescue personnel to organize rescue efforts and collect personnel information.

2. The BIM-based building disaster relief planning system according to claim 1, characterized in that: The disaster command and dispatch module allows commanders to issue command and dispatch information based on information displayed by the virtual reality display module and their rescue experience.

3. The BIM-based building disaster relief planning system according to claim 2, characterized in that: The BIM includes a data model of building structure information, building material information, building spatial geometry information, building piping information, building cable information, and building equipment information.

4. The BIM-based building disaster relief planning system according to claim 3, characterized in that: The environmental information includes information on temperature, humidity, smoke concentration, toxic gases, and the presence or absence of personnel.

5. The BIM-based building disaster relief planning system according to claim 4, characterized in that: The virtual reality display module shows the disaster analysis module's assessment of the trapped personnel, the distribution of the disaster, and the prediction of the disaster's development.

6. The BIM-based building disaster relief planning system according to claim 5, characterized in that: The virtual reality display module includes mobile terminals, PC terminals, VR or AR terminals.

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