CN117953642B - BIM-based intelligent building monitoring method and system - Google Patents
BIM-based intelligent building monitoring method and system Download PDFInfo
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Abstract
The invention relates to the technical field of building monitoring, in particular to a BIM-based intelligent building monitoring method and system, which can provide accurate, rapid and intelligent escape guidance for people when a fire disaster occurs, and ensure the life safety of the people to the greatest extent; the method comprises the following steps: based on BIM technology, respectively assigning index addresses to each smoke sensor and each safety outlet in a building; acquiring an index address of a first smoke sensor triggering an alarm; traversing index addresses of all smoke sensors, screening out a second smoke sensor and a third smoke sensor which are closest to the first smoke sensor, wherein the second smoke sensor and the third smoke sensor are respectively positioned on two sides of the first smoke sensor; collecting the smoke concentration monitored by the second smoke sensor and the third smoke sensor in a set time, and carrying out trend analysis to obtain a smoke spreading trend; and acquiring image information at all the safety exits.
Description
Technical Field
The invention relates to the technical field of building monitoring, in particular to a smart building monitoring method and system based on BIM.
Background
BIM is a building information model, which is a novel technical application capable of realizing data sharing and collaborative work by modeling and centralizing and presenting all real information of a building through a digital technology based on various relevant information data of a building engineering project; in the subsequent operation and maintenance stage of the building, the BIM model can realize overall process management and monitoring, and the state, equipment operation condition, environmental factors and the like of the building can be monitored in real time by combining the BIM model with technologies such as a sensor, the Internet of things and the like, so that the intellectualization and refinement of the operation and maintenance of the building are realized.
For the fire monitoring method, most buildings adopt fire or smoke sensors to monitor in real time and give an alarm when the fire occurs. However, when a fire occurs in an aggregated population, such as a convention center, an indoor stadium, etc. The single smoke sensor monitoring mode is difficult to conduct effective escape route guidance for people around the ignition point, so that the optimal escape time is missed. Therefore, there is a need for a smart building monitoring method based on BIM.
Disclosure of Invention
In order to solve the technical problems, the invention provides the intelligent building monitoring method based on BIM, which can provide accurate, rapid and intelligent escape guidance for people when a fire disaster occurs and furthest ensure the life safety of the people.
In a first aspect, the present invention provides a smart building monitoring method based on BIM, the method comprising:
Based on BIM technology, respectively assigning index addresses to each smoke sensor and each safety outlet in a building;
acquiring an index address of a first smoke sensor triggering an alarm;
Traversing index addresses of all smoke sensors, screening out a second smoke sensor and a third smoke sensor which are closest to the first smoke sensor, wherein the second smoke sensor and the third smoke sensor are respectively positioned on two sides of the first smoke sensor;
Collecting the smoke concentration monitored by the second smoke sensor and the third smoke sensor in a set time, and carrying out trend analysis to obtain a smoke spreading trend;
acquiring image information of all safety exits; sequentially inputting the image information of all the safety exits into a pre-trained safety exit blockage recognition model to obtain the blockage degree of each safety exit;
traversing index addresses of all the safety exits, and calculating escape distances between all the safety exits and the first smoke sensor;
According to the smoke spreading trend and the blocking degree of the safety outlets, calculating a first decision parameter and a second decision parameter of each safety outlet; the first decision parameter is determined by the position relation between the safety outlet and the first smoke sensor and by combining the smoke spreading trend; the second decision parameter is determined by the degree of blockage of the safety exit;
Inputting the escape distance, the first decision parameter and the second decision parameter corresponding to the safety exit into an escape safety index calculation model to obtain an escape safety index of the safety exit;
Traversing escape safety indexes of all the safety exits, taking the safety exits with the escape safety indexes exceeding a preset safety threshold as preferred safety exits, and informing the preferred safety exits to masses around the ignition point.
Further, the core calculation formula of the escape safety index calculation model is as follows:
K＝ω1×F(di)-1+ω2×G(pi1)+ω3×H(pi2)-1
Wherein K represents an escape safety index; d i denotes an escape distance between the ith safety vent and the first smoke sensor; p i1 denotes the first decision parameter of the ith secure exit; p i2 denotes a second decision parameter for the ith secure exit; omega 1 represents the influence weight of escape distance on the K value; omega 2 represents the impact weight of the first decision parameter on the K value; omega 3 represents the impact weight of the second decision parameter on the K value; f (d i) represents a function of normalizing the escape distance; g (p i1) represents a function normalizing the first decision parameter; h (p i2) represents a function that normalizes the second decision parameter.
Further, the value of the first decision parameter is: the first smoke sensor is taken as a vertex, the direction of the smoke spreading trend is taken as one side, the connecting line between the safety outlet and the first smoke sensor is taken as the other side, the formed included angle is the first decision parameter, the value range of the first decision parameter is 0-180 degrees, and the larger the first decision parameter is, the larger the calculated escape safety index is.
Further, the second smoke sensor and third smoke sensor screening method comprises:
Acquiring index addresses of all smoke sensors, and traversing the index addresses of all smoke sensors;
For each smoke sensor, the system measures its distance from the first trigger smoke sensor;
The system screens out the two nearest sensors as second and third smoke sensors, respectively.
Further, the smoke spread trend analysis method includes:
the system collects the smoke concentration data monitored by the second smoke sensor and the third smoke sensor in a set time period;
Preprocessing the collected smoke concentration data, including denoising, data smoothing and calibration;
comparing the monitoring data of the second smoke sensor with the monitoring data of the third smoke sensor, and calculating the smoke concentration difference between the two sensors;
Analyzing the time sequence of the data to determine the increasing and decreasing trend of the smoke concentration;
Estimating a propagation path and a velocity of smoke using a mathematical model;
Determining short-term and long-term trends of smoke spread;
visualizing the results of the trend analysis in the form of a graph;
based on the results of the trend analysis, the system predicts the spreading trend of the smoke, including the direction and speed of the spreading.
Further, the clogging degree evaluating method includes:
Deploying an image capturing apparatus around each security exit within the building;
The image capturing device captures images in real time and transmits image data to the central server for processing;
carrying out data preprocessing on the image data, including image denoising, brightness and contrast adjustment and image enhancement;
Sequentially inputting the images of each safety outlet into a safety outlet blockage recognition model, analyzing the images by the model, recognizing an outlet area, and evaluating the blockage degree of the outlet;
based on the model output, each outlet will be evaluated and assigned a blockage score.
Further, the escape distance calculating method between the safety exit and the first smoke sensor comprises the following steps:
acquiring an index address of each safety outlet, and determining position information of each safety outlet;
Acquiring an index address of a first smoke sensor triggering an alarm, and determining the position of the first smoke sensor through the index address;
For each safety exit, calculating an escape distance by measuring a distance between its position and the position of the first smoke sensor;
and integrating the distances between all the safety outlets and the first smoke sensor to form an escape distance data set.
In another aspect, the present application also provides a smart building monitoring system based on BIM, the system comprising:
And a data integration module: based on BIM technology, the system is used for assigning index addresses to each smoke sensor and each safety outlet in a building, integrating data in BIM and transmitting the data;
Fire trigger detection module: the system comprises a first smoke sensor, a second smoke sensor, a first alarm and a second alarm, wherein the first smoke sensor is used for receiving integrated index address data, detecting the triggering condition of a fire disaster or a smoke sensor, acquiring an index address of the first smoke sensor triggering an alarm and sending the index address;
Sensor cooperation module: the method comprises the steps of receiving index addresses of first smoke sensors, traversing the index addresses of all the smoke sensors, screening out second smoke sensors and third smoke sensors which are closest to the first smoke sensors, wherein the second smoke sensors and the third smoke sensors are respectively positioned on two sides of the first smoke sensors, and sending the second smoke sensors and the third smoke sensors;
And a spreading trend analysis module: the method comprises the steps of receiving information of a second smoke sensor and a third smoke sensor, collecting smoke concentrations monitored by the second smoke sensor and the third smoke sensor in a set time, carrying out trend analysis, obtaining a smoke spreading trend, and sending;
A safety exit state identification module: the method is used for acquiring image information of all safety exits; sequentially inputting image information of all safety exits into a pre-trained safety exit blockage recognition model, obtaining the blockage degree of each safety exit, and sending the blockage degree;
The escape distance calculation module: for receiving the integrated index address data and the index address of the first smoke sensor, and then traversing the index addresses of all the security exits, calculating escape distances between all the safety exits and the first smoke sensor, and sending the escape distances;
decision parameter calculation module: the method comprises the steps of receiving a smoke spreading trend and the blocking degree of each safety outlet, and calculating a first decision parameter and a second decision parameter of each safety outlet according to the smoke spreading trend and the blocking degree of the safety outlet, wherein the first decision parameter is determined by the position relation between the safety outlet and a first smoke sensor and by combining the smoke spreading trend; the second decision parameter is determined by the blockage degree of the safety outlet and is sent;
The escape safety index calculation module is used for receiving escape distances, first decision parameters and second decision parameters between the safety outlets and the first smoke sensor, inputting the escape distances, the first decision parameters and the second decision parameters corresponding to each group of safety outlets into the escape safety index calculation model, obtaining escape safety indexes of all the safety outlets, and sending the escape safety indexes;
a safety outlet selection module: the safety system comprises a safety exit, a safety point detection module and a safety point detection module, wherein the safety point detection module is used for detecting the safety point of a person, the safety point detection module is used for detecting the safety point of the person, and the safety point detection module is used for detecting the safety point of the person.
In a third aspect, the present application provides an electronic device comprising a bus, a transceiver, a memory, a processor and a computer program stored on the memory and executable on the processor, the transceiver, the memory and the processor being connected by the bus, the computer program when executed by the processor implementing the steps of any of the methods described above.
In a fourth aspect, the application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of any of the methods described above.
Compared with the prior art, the invention has the beneficial effects that: the method utilizes BIM technology in combination with sensor and image recognition, and can intelligently recognize the position of fire occurrence, the smoke spreading trend and the blockage situation of a safety exit, thereby providing intelligent escape route guidance for the masses and avoiding specific escape information which is difficult to provide by the traditional smoke sensor; by combining BIM technology and real-time monitoring of a sensor, the method can quickly react after a fire disaster occurs, identify the nearest safety exit and provide real-time escape suggestions, so that the most accurate escape information is ensured to be obtained in the shortest time;
By comprehensively considering a plurality of factors such as smoke spreading trend, the position and the blocking degree of the safety outlets and the like, the method can carry out comprehensive analysis, calculate escape safety indexes for each safety outlet, and improve the scientificity and the accuracy of an escape scheme; according to the method, the specific structure and layout in the building are considered, personalized and customized route guidance can be provided for escaping in different areas and on different floors, and the escaping is more efficient; when the preferred safety exit is determined, the method can immediately give an alarm and inform surrounding people, ensure people to quickly obtain escape information, and improve the emergency response efficiency of fire accidents; because the method adopts modern digital technology, the method has high expandability; new sensors, more accurate models, more intelligent algorithms, etc. can be easily integrated, enabling the system to be upgraded and improved continuously with advances in technology;
In summary, the intelligent building monitoring method based on BIM combines information technology with building safety management, not only provides a high-efficiency fire monitoring system, but also provides accurate, rapid and intelligent escape guidance for people in the case of fire, and maximally ensures the life safety of people.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a flow chart of a second smoke sensor and third smoke sensor screening method;
FIG. 3 is a flow chart of a smoke spread trend analysis method;
FIG. 4 is a flow chart of a method of estimating clogging degree;
FIG. 5 is a flow chart of a method of escape distance calculation between a safety vent and a first smoke sensor;
FIG. 6 is a block diagram of a BIM-based intelligent building monitoring system.
Detailed Description
In the description of the present application, those skilled in the art will appreciate that the present application may be embodied as methods, apparatus, electronic devices, and computer-readable storage media. Accordingly, the present application may be embodied in the following forms: complete hardware, complete software (including firmware, resident software, micro-code, etc.), a combination of hardware and software. Furthermore, in some embodiments, the application may also be embodied in the form of a computer program product in one or more computer-readable storage media, which contain computer program code.
Any combination of one or more computer-readable storage media may be employed by the computer-readable storage media described above. The computer-readable storage medium includes: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of the computer readable storage medium include the following: portable computer magnetic disks, hard disks, random access memories, read-only memories, erasable programmable read-only memories, flash memories, optical fibers, optical disk read-only memories, optical storage devices, magnetic storage devices, or any combination thereof. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, device.
The technical scheme of the application obtains, stores, uses, processes and the like the data, which all meet the relevant regulations of national laws.
The application provides a method, a device and electronic equipment through flow charts and/or block diagrams.
It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions. These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
These computer readable program instructions may also be stored in a computer readable storage medium that can cause a computer or other programmable data processing apparatus to function in a particular manner. Thus, instructions stored in a computer-readable storage medium produce an instruction means which implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
The present application will be described below with reference to the drawings in the present application.
Example 1
As shown in fig. 1 to 5, the smart building monitoring method based on BIM of the present invention specifically includes the following steps:
s1, based on BIM technology, respectively giving index addresses to each smoke sensor and each safety outlet in a building;
The method for establishing the association of the BIM model index address comprises the following steps:
S11, respectively endowing each smoke sensor in a building with a unique index address by using a BIM model, wherein the index addresses are represented by numbers; combining the physical structure of the building and the BIM model, ensuring that the position of each sensor in the model can be accurately mapped into the actual building;
S12, respectively endowing each safety outlet in the building with a unique index address by using the BIM model, wherein the index address of each safety outlet corresponds to the position of the safety outlet in the BIM model, so that each safety outlet can be accurately positioned in the BIM model;
s13, integrating index addresses of the smoke sensor and the safety outlet into a BIM model, and establishing a data association so that the index address of each device is associated with the position and the attribute of each device in the BIM model;
And S14, visually displaying the integrated BIM model through a display device, and enabling information of the smoke sensor and the safety outlet to be used by other systems through data sharing, so that an operator can quickly search and locate information related to the specific sensor and the specific outlet.
In the step, by distributing unique index addresses for each smoke sensor and each safety outlet, accurate positioning and identification of the smoke sensors and the safety outlets can be realized, building management personnel and emergency service personnel are helped to quickly find out the equipment when needed, and the efficiency of emergency response is improved; integrating the index address into the BIM model, establishing data association, and associating the index address of each device with the position and the attribute of each device in the BIM model, so that the information of the devices is easy to manage and search; the integrated BIM model is visually displayed through the display equipment, so that an operator can check the positions and states of the smoke sensor and the safety outlet in the building in a visual interface, and the safety condition of the building can be conveniently known; the information of the smoke sensor and the safety outlet can be used by other systems through data sharing, so that a comprehensive building monitoring and emergency response system is realized, and the safety of a building is further improved;
BIM technology is combined with building monitoring, so that the overall safety of the building is improved. Through accurate equipment position information, the smoke sensor can monitor fire disasters more effectively, and accurate positioning of the safety exit is beneficial to effective escape decision; by associating index addresses, operators can more quickly find and locate information related to specific sensors and exits, which can greatly reduce the time of emergency response, helping people escape from the building more quickly and effectively;
In summary, the present step helps to improve building safety, improve emergency response efficiency, and enhance building monitoring and management capabilities through digital technology applications.
S2, acquiring an index address of a first smoke sensor triggering an alarm;
Step S2 is an important step in the whole smart building monitoring method based on BIM, which is capable of determining the source location of the fire, the BIM includes a central control system, and the following is a detailed explanation of this step:
s21, monitoring smoke concentration through a smoke sensor in a building, and triggering an alarm when a certain smoke sensor detects abnormal smoke concentration;
S22, the smoke sensor triggering the alarm sends an electronic signal to the central control system, wherein the signal comprises the identification of the triggering sensor, including an index address and an alarm type;
S23, the central control system receives signals from the trigger sensor, the system records the time stamp of the event, extracts the index address of the trigger sensor and determines the position of the fire alarm;
s24, the central control system correlates the index address of the trigger sensor with the corresponding sensor position in the BIM model.
In the step, by obtaining the index address of the sensor, the monitoring system can quickly and accurately locate the specific position of the fire alarm; by definitely positioning the first position for triggering the smoke sensor, the possibility of false alarm can be reduced, unnecessary evacuation and interference to normal activities in the building are prevented, and the reliability of fire alarm is improved;
the system records the time stamp of the event and the index address of the trigger sensor, so that the system is convenient for post-examination to know the development and the coping situation of the fire event, thereby improving the building safety and the fire emergency plan;
In summary, step S2 achieves rapid positioning of the fire source by acquiring the index address of the first triggering smoke sensor, improves the emergency response efficiency, reduces false alarm, enhances intelligent decision, and provides important information for subsequent data analysis.
S3, traversing index addresses of all the smoke sensors, and screening out a second smoke sensor and a third smoke sensor which are closest to the first smoke sensor, wherein the second smoke sensor and the third smoke sensor are respectively positioned on two sides of the first smoke sensor;
Step S3 is intended to determine other smoke sensors around the first trigger smoke sensor in order to more accurately evaluate the trend of fire propagation; by screening the nearest second and third smoke sensors, the system can establish a more accurate fire zone, thereby providing a more reliable escape route and decision support;
the second smoke sensor and third smoke sensor screening method comprises:
S31, acquiring index addresses of all smoke sensors, and traversing the index addresses of all smoke sensors;
s32, for each sensor, measuring the distance between the sensor and the first triggering smoke sensor by the system, and accurately measuring and calculating the distance between the smoke sensors by using the space coordinate information in the BIM;
s33, screening two nearest sensors as a second smoke sensor and a third smoke sensor by the system, wherein the two sensors are positioned on two sides of the first sensor so as to cover the fire source area comprehensively.
In this step, by measuring the distance between each sensor and the first trigger smoke sensor, the nearest sensor can be accurately determined, not just the nearest sensor, which enhances the accuracy assessment of the fire area and helps determine the fire spread trend; the second smoke sensor and the third smoke sensor are selected to be respectively positioned at two sides of the first sensor, so that the whole coverage of a fire source area is ensured, a more accurate fire source area model can be constructed, and understanding of fire spreading is further improved;
Through accurate fire source area information, the system can better guide personnel to select escape routes and take necessary decisions, and the escape efficiency and safety are improved; the safety of personnel in the building is improved, and particularly in emergency situations such as fire and the like, a more reliable escape route and decision support are provided, so that the life and property safety is protected;
In summary, the step S3 provides more accurate fire spread information for the smart building monitoring method based on BIM by high-precision distance measurement and selecting the closest sensor, thereby improving the performance and life safety level of the fire monitoring system in the building.
S4, collecting the smoke concentration monitored by the second smoke sensor and the third smoke sensor in a set time, and carrying out trend analysis to obtain a smoke spreading trend;
the smoke spreading trend analysis method comprises the following steps:
s41, collecting smoke concentration data monitored by a second smoke sensor and a third smoke sensor in a set time period by the system;
S42, preprocessing the collected smoke concentration data, including denoising, data smoothing and calibration, so as to ensure the accuracy and reliability of the data, reduce unnecessary fluctuation and ensure the stability of analysis;
S43, comparing the monitoring data of the second smoke sensor and the third smoke sensor to determine the change trend of the smoke concentration, wherein the step comprises the steps of calculating the smoke concentration difference between the two sensors;
s44, analyzing the time sequence of the data to determine the increasing and decreasing trend of the smoke concentration, and further knowing the spreading speed of the smoke;
S45, estimating the propagation path and speed of smoke by using a mathematical model;
s46, determining short-term trend and long-term trend of smoke spreading;
S47, visualizing the trend analysis result in a chart form so that an operator can better understand the smoke spreading condition;
S48, based on the result of trend analysis, the system predicts the spreading trend of the smoke, including the spreading direction and speed.
In the step, by collecting and analyzing the smoke concentration data, the system can early warn the existence and spreading trend of smoke in a building in advance, help personnel to detect fire earlier, and further increase escape time; trend analysis allows the system to better understand the speed and direction of smoke propagation, and can provide more refined escape route guidance to avoid areas with higher smoke concentration; by knowing the smoke spreading trend in advance, confusion and panic during escape can be reduced, and people can take intelligent actions according to information to select the safest escape path; the trend analysis result enables the system to select the safest exit, not just the nearest exit, so that people are prevented from gathering at the exit with high smoke concentration, and escape efficiency is improved; analysis focuses not only on the immediate situation of smoke spreading, but also on long-term trends, which helps to program long-term escape strategies;
In summary, the step S4 can improve the safety in the case of fire in a building, reduce the potential life threat, provide better decision support, and ensure that personnel can escape more effectively.
S5, acquiring image information of all the safety exits; sequentially inputting the image information of all the safety exits into a pre-trained safety exit blockage recognition model to obtain the blockage degree of each safety exit;
the clogging degree evaluation method comprises the following steps:
s51, deploying an image pickup device around each safety exit in the building, wherein the installation position of the image pickup device enables the image pickup device to capture the area in front of and around the exit gate so as to acquire information about the smoothness of the exit;
s52, the image capturing equipment captures images in real time and transmits image data to a central server for processing;
s53, carrying out data preprocessing on the image data, including image denoising, brightness and contrast adjustment and image enhancement, so as to ensure the quality and consistency of the image;
S54, sequentially inputting the images of each safety outlet into a safety outlet blockage recognition model, wherein the model analyzes the images, recognizes outlet areas, and evaluates the blockage degree of the outlets, including detecting whether people or objects block the outlets and whether barriers exist;
s55, based on the model output, each outlet will be evaluated and assigned a blockage score, which represents the patency of the outlet, from unblocked to fully blocked;
By arranging the camera equipment around each safety exit and capturing images in real time, building management personnel can monitor the blocking degree of each exit in real time, so that the problem of blocking the exit can be found and solved in advance, and the personnel can escape rapidly and safely in case of fire or other emergency; through analysis and evaluation of the model, each safety outlet is given a specific blockage score which represents the smoothness level of the safety outlet, so that building management personnel can know which outlets are safe more accurately so as to take action in time;
the model outputs a blockage score, which can automatically select the best escape route or provide suggestions as to which exits can be used, thereby reducing human error and confusion; by accurately evaluating the smoothness of the exit, building management personnel can help personnel avoid selecting the blocked or unsafe exit, thereby improving the escape efficiency, reducing congestion and confusion and relieving the potential danger caused by fire; by monitoring and evaluating the status of the safety exits in real time, building management teams can take precautions to reduce the risk of exit blockage; the overall safety of the building is improved, the casualties risk under the condition of fire disaster or emergency is reduced, and the life safety of personnel is protected;
More specifically, the method for constructing the safety outlet blockage recognition model comprises the following steps:
A. collecting image information of a safety exit area through camera equipment;
B. marking the acquired image information, and classifying the smoothness of the outlet into different categories including smoothness, partial blockage and complete blockage;
C. Preprocessing the image data, including image scaling, brightness and contrast adjustment, to ensure consistency;
D. The safety exit blockage recognition model is usually based on a deep learning technology, and a convolutional neural network is selected;
E. Verifying the performance of the model using a set of labeled data, determining the accuracy and generalization ability of the model;
F. Deploying the verified model into an actual building monitoring system for real-time safety exit blockage identification.
By using a deep learning technology, the model can automatically identify the smoothness of a safety outlet without manual intervention, thereby reducing the burden of monitoring work and realizing uninterrupted monitoring; once the model detects a blockage of the safety exit, the relevant departments can immediately take measures to evacuate personnel or solve the problem to reduce potential risks and hazards;
By using the deep learning model, highly accurate blockage degree evaluation can be realized, and the possibility of false alarm is reduced; by monitoring and recording the state of the safety exit in real time, a building management team can make a more intelligent decision according to the data, so that the building safety and the coping efficiency under emergency conditions are improved; the building management team can better manage the safety exit, improve the safety of personnel in the building, and reduce the potential risk in emergency.
S6, traversing index addresses of all the safety exits, and calculating escape distances between all the safety exits and the first smoke sensor;
The escape distance calculating method between the safety outlet and the first smoke sensor comprises the following steps:
s61, acquiring an index address of each safety exit, and determining the position information of each safety exit;
S62, acquiring an index address of a first smoke sensor triggering an alarm, and determining the position of the first smoke sensor through the index address;
S63, for each safety exit, calculating escape distances by measuring the distance between the position of the safety exit and the position of the first smoke sensor;
s64, integrating the distances between all the safety outlets and the first smoke sensor to form an escape distance data set.
In the step, the distance between each safety outlet and the first smoke sensor is measured, so that the positions of the outlets which are closer to the fire source can be accurately determined, the safety smoke sensor can be used as a safer escape path, people are prevented from selecting outlets which are farther from the fire source, and escape efficiency is improved; the method can provide personalized escape suggestions for each person in the building according to the distance of each safety exit; clear escape suggestions and clear escape routes are provided, so that confusion and panic of people can be reduced;
In summary, the step S6 is to calculate the escape distance, so as to help to improve the survival chance of the personnel in the building in the event of fire or smoke, and provide intelligent and personalized escape decision support.
S7, calculating a first decision parameter and a second decision parameter of each safety outlet according to the smoke spreading trend and the blocking degree of the safety outlet; the first decision parameter is determined by the position relation between the safety outlet and the first smoke sensor and by combining the smoke spreading trend; the second decision parameter is determined by the degree of blockage of the safety exit;
the first decision parameter is determined according to the relative position between the safety outlet and the first smoke sensor, and the escape distance is determined by measuring the distance between the safety outlet and the first smoke sensor, so that the first decision parameter is determined;
The first decision parameter relates to the tendency of the smoke to spread, and in general, closer to the outlet of the smoke source will be considered more dangerous because the rate of smoke spreading is faster, then closer to the outlet of the smoke source will be considered more dangerous;
the value of the first decision parameter is as follows: the first smoke sensor is taken as a vertex, the direction of the smoke spreading trend is taken as one side, the connecting line between the safety outlet and the first smoke sensor is taken as the other side, the formed included angle is a first decision parameter, the value range of the first decision parameter is 0-180 degrees, and the larger the first decision parameter is, the larger the calculated escape safety index is;
the second decision parameter is determined according to the blockage degree of each safety exit, and is obtained through a safety exit blockage recognition model, and the exit with higher blockage degree is not the optimal escape path, so the parameter can be used for judging which exits are blocked;
The value of the second decision parameter is as follows: the ratio between the blocking width of the safety outlet and the self width of the safety outlet is a second decision parameter, and the value range of the second decision parameter is 0-1; the larger the second decision parameter is, the smaller the calculated escape safety index is.
By calculating the first decision parameter and the second decision parameter, a quantitative escape safety assessment parameter is provided, which enables more accurate determination of which safety exits are the safest choices in the event of fire or smoke, improves the accuracy of escape decisions for people, and reduces potential risks; by considering the smoke spreading trend and the blocking degree, people can be guided to select the safest escape route conveniently, so that the escape efficiency is improved;
By comprehensively considering a plurality of factors, more accurate escape suggestions are provided for personnel in the building, the survival rate of fire or smoke events in the building is hopefully improved, and casualties and confusion are reduced.
S8, inputting the escape distance, the first decision parameter and the second decision parameter corresponding to the safety exit into an escape safety index calculation model to obtain an escape safety index of the safety exit;
the escape safety index calculation model converts input parameters into an escape safety index, wherein the higher the index is, the safer the exit is, and the model needs to comprehensively consider escape distance, position relation, smoke spreading trend and blockage degree;
Taking the length of the escape path into consideration, assigning a weight to the escape distance, wherein the weight is a positive number, and the shorter the escape distance is, the better the escape distance is, and the higher the score is obtained at an outlet with the shorter escape distance;
the first decision parameter reflects the position relation and the smoke spreading trend of the outlet relative to the smoke sensor, and a weight is designed to reflect the influence of the smoke sensor on escape, and the weight is changed according to the position relation and the spreading trend of the safety outlet;
the second decision parameter relates to the degree of blockage of the outlet, and a weight is allocated to consider the factor, if the outlet is blocked, the weight is reduced, and the lower availability of the outlet is reflected;
The core calculation formula of the escape safety index calculation model is as follows:
K＝ω1×F(di)-1+ω2×G(pi1)+ω3×H(pi2)-1
Wherein K represents an escape safety index; d i denotes an escape distance between the ith safety vent and the first smoke sensor; p i1 denotes the first decision parameter of the ith secure exit; p i2 denotes a second decision parameter for the ith secure exit; omega 1 represents the influence weight of escape distance on the K value; omega 2 represents the impact weight of the first decision parameter on the K value; omega 3 represents the impact weight of the second decision parameter on the K value; f (d i) represents a function of normalizing the escape distance; g (p i1) represents a function normalizing the first decision parameter; h (p i2) represents a function that normalizes the second decision parameter.
In the step, the model comprehensively considers a plurality of key factors such as escape distance, position relation, smoke spreading trend, blocking degree and the like, so that the model can comprehensively consider actual conditions in a building when evaluating a safety exit, and the evaluation accuracy is improved; by giving the escape distance an appropriate weight, the model takes the short-distance escape path into consideration, which is helpful for preferentially selecting more easily-accessible exits, and improves the efficiency and safety of personnel escape; the first decision parameter reflects the positional relationship of the outlet relative to the smoke sensor and the smoke propagation trend; by introducing corresponding weights into the model, it is possible to ensure that the relative safety of the outlet is assessed in case of smoke propagation; the second decision parameter relates to the degree of blockage of the outlet, which is one of the key factors in assessing the availability of the outlet; by assigning a corresponding weight, the model can distinguish between outlets with different blocking degrees, so as to ensure that only those unobstructed outlets are selected as the preferred safety outlets;
by normalizing each parameter, the influence of different parameters can be uniformly processed in the model; in addition, the importance of different parameters can be clearly embodied by introducing the weight, so that the safety of each safety outlet can be more accurately evaluated;
in conclusion, the design of the model enables the safest escape exit to be selected more intelligently under emergency conditions such as fire disaster and the like, effective escape guidance is provided for personnel, and the building safety and the guarantee of personnel life safety are improved;
S9, traversing escape safety indexes of all the safety exits, taking the safety exits with the escape safety indexes exceeding a preset safety threshold as preferred safety exits, and informing the preferred safety exits to masses around the ignition point;
the preferred method for selecting the safety exit comprises the following steps:
S91, obtaining escape safety indexes of all safety exits;
s92, setting a preset safety threshold value;
s93, traversing all safety exits, comparing escape safety indexes of all safety exits with a preset threshold value, and regarding the exits with the scores higher than the preset safety threshold value as the safest exits, wherein the exits are selected as the preferred safety exits;
S94, once the safest safety exit is determined, taking measures to inform nearby people, wherein the informing modes comprise an audio alarm, a display screen and a mobile application program to ensure that escape route information is provided for the people as soon as possible;
The preset safety threshold is a key parameter that determines which escape exits are considered safe enough for personnel to use; the preset safety threshold setting influencing factors comprise:
Building types, different types of buildings, requiring different safety thresholds, they have different evacuation requirements and risk levels;
Building structures and materials, the structures of the building and the materials used can influence the spread speed and intensity of fire, thereby influencing the setting of a safety threshold;
The personnel density in the building is considered by the preset safety threshold value, because in a crowded environment, a higher threshold value needs to be set;
Regulations and standards local building regulations and safety standards may also affect the setting of preset safety thresholds, as regulations and standards dictate the minimum safety requirements for a particular type of building.
In the step, by comparing the escape safety index with a preset safety threshold value, the system can rapidly identify and select the safest escape exit; selecting the safest escape exit helps to minimize the risk of injury or entrapment of personnel; this improves the overall evacuation efficiency, ensuring that personnel find access to the safe area more easily; the calculation of escape safety indexes can be adjusted according to real-time conditions and building characteristics; this means that it is possible to provide personalized evacuation guidance to provide an optimal escape route for different persons depending on the current situation; by explicitly selecting the safest exit and providing this information to the person, the likelihood of confusion and panic can be reduced; people can easily follow the guidance in a cool and quiet way, and the casualties risk in accidents is reduced;
This step encompasses a variety of notification modes including audible alarms, display screens, and mobile application notifications; the diversity ensures the multi-way transmission of information and improves the chance that people receive escape guidance; the setting of the preset safety threshold value is to comprehensively consider various factors such as building type, structure, materials, personnel density, regulations and standards and the like; this ensures that the choice of the safest exit is based on comprehensive and rational basis to meet the needs of different scenes and environments;
In summary, the step S9 provides key escape decision support for personnel in the building, so that the personnel can safely and effectively cope with emergency situations such as fire disaster; this helps to reduce the rate of casualties, reduce confusion and panic, and improve overall evacuation efficiency.
Example two
As shown in fig. 6, the smart building monitoring system based on BIM of the present invention specifically includes the following modules;
And a data integration module: based on BIM technology, the system is used for assigning index addresses to each smoke sensor and each safety outlet in a building, integrating data in BIM and transmitting the data;
Fire trigger detection module: the system comprises a first smoke sensor, a second smoke sensor, a first alarm and a second alarm, wherein the first smoke sensor is used for receiving integrated index address data, detecting the triggering condition of a fire disaster or a smoke sensor, acquiring an index address of the first smoke sensor triggering an alarm and sending the index address;
Sensor cooperation module: the method comprises the steps of receiving index addresses of first smoke sensors, traversing the index addresses of all the smoke sensors, screening out second smoke sensors and third smoke sensors which are closest to the first smoke sensors, wherein the second smoke sensors and the third smoke sensors are respectively positioned on two sides of the first smoke sensors, and sending the second smoke sensors and the third smoke sensors;
And a spreading trend analysis module: the method comprises the steps of receiving information of a second smoke sensor and a third smoke sensor, collecting smoke concentrations monitored by the second smoke sensor and the third smoke sensor in a set time, carrying out trend analysis, obtaining a smoke spreading trend, and sending;
A safety exit state identification module: the method is used for acquiring image information of all safety exits; sequentially inputting image information of all safety exits into a pre-trained safety exit blockage recognition model, obtaining the blockage degree of each safety exit, and sending the blockage degree;
The escape distance calculation module: for receiving the integrated index address data and the index address of the first smoke sensor, and then traversing the index addresses of all the security exits, calculating escape distances between all the safety exits and the first smoke sensor, and sending the escape distances;
decision parameter calculation module: the method comprises the steps of receiving a smoke spreading trend and the blocking degree of each safety outlet, and calculating a first decision parameter and a second decision parameter of each safety outlet according to the smoke spreading trend and the blocking degree of the safety outlet, wherein the first decision parameter is determined by the position relation between the safety outlet and a first smoke sensor and by combining the smoke spreading trend; the second decision parameter is determined by the blockage degree of the safety outlet and is sent;
The escape safety index calculation module is used for receiving escape distances, first decision parameters and second decision parameters between the safety outlets and the first smoke sensor, inputting the escape distances, the first decision parameters and the second decision parameters corresponding to each group of safety outlets into the escape safety index calculation model, obtaining escape safety indexes of all the safety outlets, and sending the escape safety indexes;
a safety outlet selection module: the safety system comprises a safety exit, a safety point detection module and a safety point detection module, wherein the safety point detection module is used for detecting the safety point of a person, the safety point detection module is used for detecting the safety point of the person, and the safety point detection module is used for detecting the safety point of the person.
The system realizes real-time monitoring of building states, equipment operation, environmental factors and the like by integrating advanced technologies such as BIM technology, sensors, the Internet of things and the like; this enables the monitoring system to manage the building more intelligently and finely; the system comprises a plurality of modules, and through mutual cooperative work, the system integrates data to fire triggering detection and then to safety exit selection, so that the omnibearing monitoring and response to a fire event are realized; such modular design helps to increase the scalability and flexibility of the system; when a fire disaster occurs, the system can rapidly detect and respond in real time, and the smoke sensor triggers the detection module to acquire the information of the first smoke sensor, so that the position of the fire disaster can be rapidly determined, and an alarm can be sent to surrounding masses;
The system can accurately determine the fire spreading condition through the sensor cooperation module and the spreading trend analysis module, and provide the best escape route guidance for the masses, so that escape difficulty caused by confusion when the masses of people have a fire disaster in a gathering place is avoided; by means of the safety exit status recognition module, the system can monitor the status of the safety exits in real time, including the degree of blockage, thereby ensuring that the safest exit can be selected when a fire event occurs; through the decision parameter calculation module, the system can calculate the decision parameter of each safety outlet according to the smoke spreading trend and the blockage degree of the safety outlet, and a scientific basis is provided for escape decision; the escape safety index calculation module is used for calculating the escape safety index of each safety exit by comprehensively considering the escape distance, the position of the safety exit, the smoke spreading trend and other factors, so that the preferred safety exit is determined; once the preferred secure exit is determined, the system can communicate information to the nearby masses through a variety of notification means, including audible alarms, display screens, and mobile application notifications, ensuring that they can obtain escape route information in time;
in summary, the intelligent building monitoring system based on BIM combines advanced technology and intelligent monitoring method, provides comprehensive fire monitoring and response, and thus greatly improves the safety and emergency response capability of building fire events.
The various modifications and embodiments of the BIM-based intelligent building monitoring method in the first embodiment are equally applicable to the BIM-based intelligent building monitoring system of the present embodiment, and those skilled in the art will be aware of the implementation method of the BIM-based intelligent building monitoring system of the present embodiment through the foregoing detailed description of the BIM-based intelligent building monitoring method, so that the details of the implementation method will not be described in detail herein for brevity.
In addition, the application also provides an electronic device, which comprises a bus, a transceiver, a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the transceiver, the memory and the processor are respectively connected through the bus, and when the computer program is executed by the processor, the processes of the method embodiment for controlling output data are realized, and the same technical effects can be achieved, so that repetition is avoided and redundant description is omitted.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that it will be apparent to those skilled in the art that modifications and variations can be made without departing from the technical principles of the present invention, and these modifications and variations should also be regarded as the scope of the invention.
Claims (7)
1. A smart building monitoring method based on BIM, the method comprising:
Based on BIM technology, respectively assigning index addresses to each smoke sensor and each safety outlet in a building;
acquiring an index address of a first smoke sensor triggering an alarm;
Traversing index addresses of all smoke sensors, screening out a second smoke sensor and a third smoke sensor which are closest to the first smoke sensor, wherein the second smoke sensor and the third smoke sensor are respectively positioned on two sides of the first smoke sensor;
Collecting the smoke concentration monitored by the second smoke sensor and the third smoke sensor in a set time, and carrying out trend analysis to obtain a smoke spreading trend;
acquiring image information of all safety exits; sequentially inputting the image information of all the safety exits into a pre-trained safety exit blockage recognition model to obtain the blockage degree of each safety exit;
traversing index addresses of all the safety exits, and calculating escape distances between all the safety exits and the first smoke sensor;
According to the smoke spreading trend and the blocking degree of the safety outlets, calculating a first decision parameter and a second decision parameter of each safety outlet; the first decision parameter is determined by the position relation between the safety outlet and the first smoke sensor and by combining the smoke spreading trend; the second decision parameter is determined by the degree of blockage of the safety exit;
Inputting the escape distance, the first decision parameter and the second decision parameter corresponding to the safety exit into an escape safety index calculation model to obtain an escape safety index of the safety exit;
traversing escape safety indexes of all safety exits, taking the safety exits with the escape safety indexes exceeding a preset safety threshold as preferred safety exits, and informing the preferred safety exits to masses around the ignition point;
The core calculation formula of the escape safety index calculation model is as follows:
K＝ω1×F(di)-1+ω2×G(pi1)+ω3×H(pi2)-1
Wherein K represents an escape safety index; d i denotes an escape distance between the ith safety vent and the first smoke sensor; p i1 denotes the first decision parameter of the ith secure exit; p i2 denotes a second decision parameter for the ith secure exit; omega 1 represents the influence weight of escape distance on the K value; omega 2 represents the impact weight of the first decision parameter on the K value; omega 3 represents the impact weight of the second decision parameter on the K value; f (d i) represents a function of normalizing the escape distance; g (p i1) represents a function normalizing the first decision parameter; h (p i2) represents a function that normalizes the second decision parameter;
The value of the first decision parameter is as follows: the first smoke sensor is taken as a vertex, the direction of the smoke spreading trend is taken as one side, the connecting line between the safety outlet and the first smoke sensor is taken as the other side, the formed included angle is a first decision parameter, the value range of the first decision parameter is 0-180 degrees, and the larger the first decision parameter is, the larger the calculated escape safety index is;
The value of the second decision parameter is as follows: the ratio between the blocking width of the safety outlet and the self width of the safety outlet is a second decision parameter, and the value range of the second decision parameter is 0-1; the larger the second decision parameter is, the smaller the escape safety index is obtained through calculation;
The escape distance calculating method between the safety outlet and the first smoke sensor comprises the following steps:
acquiring an index address of each safety outlet, and determining position information of each safety outlet;
Acquiring an index address of a first smoke sensor triggering an alarm, and determining the position of the first smoke sensor through the index address;
For each safety exit, calculating an escape distance by measuring a distance between its position and the position of the first smoke sensor;
and integrating the distances between all the safety outlets and the first smoke sensor to form an escape distance data set.
2. The BIM-based intelligent building monitoring method of claim 1, wherein the second and third smoke sensor screening methods include:
Acquiring index addresses of all smoke sensors, and traversing the index addresses of all smoke sensors;
For each smoke sensor, the system measures its distance from the first trigger smoke sensor;
The system screens out the two nearest sensors as second and third smoke sensors, respectively.
3. The BIM-based intelligent building monitoring method of claim 1, wherein the smoke propagation trend analysis method includes:
the system collects the smoke concentration data monitored by the second smoke sensor and the third smoke sensor in a set time period;
Preprocessing the collected smoke concentration data, including denoising, data smoothing and calibration;
comparing the monitoring data of the second smoke sensor with the monitoring data of the third smoke sensor, and calculating the smoke concentration difference between the two sensors;
Analyzing the time sequence of the data to determine the increasing and decreasing trend of the smoke concentration;
Estimating a propagation path and a velocity of smoke using a mathematical model;
Determining short-term and long-term trends of smoke spread;
visualizing the results of the trend analysis in the form of a graph;
based on the results of the trend analysis, the system predicts the spreading trend of the smoke, including the direction and speed of the spreading.
4. The BIM-based intelligent building monitoring method according to claim 1, wherein the blocking degree evaluation method includes:
Deploying an image capturing apparatus around each security exit within the building;
The image capturing device captures images in real time and transmits image data to the central server for processing;
carrying out data preprocessing on the image data, including image denoising, brightness and contrast adjustment and image enhancement;
Sequentially inputting the images of each safety outlet into a safety outlet blockage recognition model, analyzing the images by the model, recognizing an outlet area, and evaluating the blockage degree of the outlet;
based on the model output, each outlet is evaluated and assigned a blockage score.
5. A BIM-based intelligent building monitoring system for implementing the BIM-based intelligent building monitoring method of any one of claims 1 to 4, the system comprising:
And a data integration module: based on BIM technology, the system is used for assigning index addresses to each smoke sensor and each safety outlet in a building, integrating data in BIM and transmitting the data;
Fire trigger detection module: the system comprises a first smoke sensor, a second smoke sensor, a first alarm and a second alarm, wherein the first smoke sensor is used for receiving integrated index address data, detecting the triggering condition of a fire disaster or a smoke sensor, acquiring an index address of the first smoke sensor triggering an alarm and sending the index address;
Sensor cooperation module: the method comprises the steps of receiving index addresses of first smoke sensors, traversing the index addresses of all the smoke sensors, screening out second smoke sensors and third smoke sensors which are closest to the first smoke sensors, wherein the second smoke sensors and the third smoke sensors are respectively positioned on two sides of the first smoke sensors, and sending the second smoke sensors and the third smoke sensors;
And a spreading trend analysis module: the method comprises the steps of receiving information of a second smoke sensor and a third smoke sensor, collecting smoke concentrations monitored by the second smoke sensor and the third smoke sensor in a set time, carrying out trend analysis, obtaining a smoke spreading trend, and sending;
A safety exit state identification module: the method is used for acquiring image information of all safety exits; sequentially inputting image information of all safety exits into a pre-trained safety exit blockage recognition model, obtaining the blockage degree of each safety exit, and sending the blockage degree;
The escape distance calculation module: for receiving the integrated index address data and the index address of the first smoke sensor, and then traversing the index addresses of all the security exits, calculating escape distances between all the safety exits and the first smoke sensor, and sending the escape distances;
decision parameter calculation module: the method comprises the steps of receiving a smoke spreading trend and the blocking degree of each safety outlet, and calculating a first decision parameter and a second decision parameter of each safety outlet according to the smoke spreading trend and the blocking degree of the safety outlet, wherein the first decision parameter is determined by the position relation between the safety outlet and a first smoke sensor and by combining the smoke spreading trend; the second decision parameter is determined by the blockage degree of the safety outlet and is sent;
The escape safety index calculation module is used for receiving escape distances, first decision parameters and second decision parameters between the safety outlets and the first smoke sensor, inputting the escape distances, the first decision parameters and the second decision parameters corresponding to each group of safety outlets into the escape safety index calculation model, obtaining escape safety indexes of all the safety outlets, and sending the escape safety indexes;
a safety outlet selection module: the safety system comprises a safety exit, a safety point detection module and a safety point detection module, wherein the safety point detection module is used for detecting the safety point of a person, the safety point detection module is used for detecting the safety point of the person, and the safety point detection module is used for detecting the safety point of the person.
6. A BIM-based intelligent building monitoring electronic device comprising a bus, a transceiver, a memory, a processor and a computer program stored on the memory and executable on the processor, the transceiver, the memory and the processor being connected by the bus, characterized in that the computer program when executed by the processor implements the steps of the method according to any one of claims 1-4.
7. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any of claims 1-4.
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