Dynamic environment adaptive high-rise building escape route optimization system and method

Abstract

The invention discloses a dynamic environment adaptive high-rise building escape route optimization system and method, and relates to the technical field of high-rise building safety. According to the invention, when fire alarm is triggered, selectable escape paths are dynamically planned according to the position of a person, the environmental evaluation index of each escape path is acquired and analyzed in real time, and environmental factors such as air temperature, harmful gas concentration and oxygen concentration are considered, so that the safety of the escape paths is evaluated. And analyzing in combination with the environment evaluation index and the path state data packet, and calculating a path evaluation index, thereby evaluating the safety and accessibility of the escape path more comprehensively, and ensuring that an optimal escape path is recommended for each person in an emergency.

Description

Technical Field

[0001] The present invention relates to the technical field of high-rise building safety, and in particular to a dynamic environment-adaptive high-rise building escape path optimization system and method. Background Art

[0002] With the acceleration of urbanization, the number and size of high-rise buildings are increasing. These buildings often have complex structures and dense population distribution. In the event of fire, earthquake, or other emergencies, evacuating people from high-rise buildings has become a major challenge. Traditional escape route planning methods often rely on static building layouts and preset evacuation routes, which have obvious limitations when facing emergencies.

[0003] However, the high-rise building escape path optimization system and method in the prior art still have the following deficiencies:

[0004] The dynamic changes in the building's internal environment during a fire are not taken into account. For example, a fire can cause a sharp rise in temperature, the rapid spread of harmful gases, and a decrease in oxygen concentration, all of which pose a serious threat to evacuation. However, existing technologies often lack the ability to monitor and assess these environmental parameters in real time, making it difficult to provide optimal escape routes.

[0005] Secondly, existing technologies rarely consider the real-time status of paths, such as the required walking distance, estimated evacuation time, and potential hazards along the path. In an emergency, these factors may affect the safe evacuation of personnel, causing them to choose suboptimal or even dangerous escape routes. For example, certain paths may become inaccessible due to fire or extremely dangerous due to the accumulation of smoke and heat.

[0006] To this end, a dynamic environment-adaptive high-rise building escape path optimization system and method is introduced. Summary of the Invention

[0007] In view of this, the present invention provides a dynamic environment-adaptive high-rise building escape route optimization system and method to solve the problems raised by the above background technology.

[0008] The purpose of the present invention can be achieved through the following technical solutions: A dynamic environment-adaptive high-rise building escape path optimization system, including a path planning module, an environment monitoring module, a data processing module, a path determination module and a user interaction module:

[0009] The path planning module is used to plan various optional escape paths based on the locations of various people in the high-rise building when a fire alarm is triggered in the high-rise building;

[0010] The environmental monitoring module is used to obtain the escape paths corresponding to each person in the high-rise building, analyze the environmental status of each escape path corresponding to each person, and thereby obtain the environmental assessment index Ygi of each escape path based on the location of each person when the fire alarm is currently triggered, where i represents the number corresponding to each escape path, i=1, 2, ..., k, and k is the total number of escape paths corresponding to the person;

[0011] The data processing module is used to receive the environmental assessment index Ygi of each person corresponding to each escape path, and analyze it in combination with the path status data packet of each escape path, thereby obtaining the path assessment index Lji of each person corresponding to each escape path, wherein the path status data packet includes the required walking distance, estimated time and path route of the path;

[0012] The path determination module is used to receive the path evaluation index Lji of each person corresponding to each escape path, and select the escape path of the corresponding person when the fire alarm is currently triggered based on the evaluation results of the path evaluation index Lji of each escape path;

[0013] The user interaction module is used to send the selected escape route to the mobile terminal of the corresponding person and generate a corresponding navigation voice data packet.

[0014] In some embodiments, the analysis of the environmental status of each escape path corresponding to each person is specifically as follows:

[0015] Divide each escape path of each person into sub-areas based on the preset division area, thereby obtaining the divided sub-areas corresponding to each escape path of each person;

[0016] Obtain the air temperature of each sub-region corresponding to each escape path. Record the air temperature of each sub-region at the current time as Wip, where p represents the sub-region number, p = 1, 2, ..., n, where n is the total number of sub-regions for each escape path.

[0017] Obtain the concentration values ​​of various types of harmful gases at the current time point in each divided sub-area, preset the maximum allowable concentration values ​​of each type of harmful gas, and calculate the ratios between the concentration values ​​of each type of harmful gas and the corresponding maximum allowable values. Set weight coefficients for each type of harmful gas, multiply each calculated ratio by the corresponding weight coefficient, and then sum them to obtain the harmful gas index of each divided sub-area, which is recorded as Nip;

[0018] Obtain the oxygen concentration of each divided sub-area at the current time point, recorded as Uip.

[0019] In some embodiments, the analyzing the environmental status of each escape path corresponding to each person further includes:

[0020] Substitute the air temperature Wip, harmful gas index Nip, and oxygen concentration Uip of each sub-area corresponding to each escape path into the formula: The state assessment index YXip of each divided sub-area of ​​the corresponding escape path is obtained, where Rip, Eip and Vip represent the maximum allowable air temperature, the highest allowable harmful gas index and the lowest allowable oxygen concentration, respectively; a1, a2 and a3 represent the influence weight factors of air temperature Wip, harmful gas index Nip and oxygen concentration Uip, respectively; Nip is visibility, Cip is minimum visibility, a4 is the influence weight factor of visibility Nip, and e is a natural constant.

[0021] In some embodiments, the environmental assessment index Ygi based on each escape path of each person's location when the fire alarm is currently triggered is specifically:

[0022] Extract the state evaluation index YXip of each divided sub-area of ​​the corresponding escape path at the current time point, and calculate the average of multiple state evaluation indexes YXip to obtain the state mean of the corresponding escape path. At the same time, extract the highest state evaluation index and the lowest state evaluation index among the state evaluation indexes YXip of each divided sub-area as the state peak value and state valley value of the corresponding escape path, respectively.

[0023] Preset the reference threshold index of the state evaluation index YXip of each sub-area of ​​the corresponding escape path, extract the state mean, state peak, and state valley of the corresponding escape path, and calculate the ratio with the reference threshold index respectively, that is, calculate by reference threshold index / state mean, reference threshold index / state peak, and reference threshold index / state valley;

[0024] The mean ratio, peak ratio, and valley ratio of the corresponding escape path are obtained, and the mean ratio, peak ratio, and valley ratio of the corresponding escape path are used as the length, width, and height of the three-dimensional rectangle, respectively, to construct a three-dimensional rectangular model of the corresponding escape path;

[0025] The surface area of ​​the three-dimensional rectangular model corresponding to the escape path is constructed as the environmental assessment index Ygi of the corresponding escape path.

[0026] In some embodiments, the receiving of the environmental assessment index Ygi corresponding to each escape path of each person and analyzing it in combination with the path status data packet of each escape path is specifically as follows:

[0027] Obtain the required walking distance and estimated time for each person corresponding to each escape path, recorded as Tai and Tbi respectively;

[0028] At the same time, the routes of each person corresponding to each escape route are analyzed, the position closest to the fire occurrence point in the route is selected, and the straight-line distance between the two is calculated as the hidden danger distance Tci;

[0029] Substitute the required walking distance Tai, estimated time Tbi and hidden danger distance Tci of each person corresponding to each escape path into the formula A weighted calculation is performed to obtain the path hidden danger value TGi of each escape path; where b1, b2 and b3 are the influence weight factors of the required walking distance Tai, the estimated time Tbi and the hidden danger distance Tci respectively.

[0030] In some embodiments, the path evaluation index Lji of each person corresponding to each escape path is obtained, specifically:

[0031] The environmental assessment index Ygi and path hidden danger value TGi of each escape path of each person are extracted and substituted into the formula Lji=tanh(1+Ygi×c1+TGi×c2) for weighted calculation to obtain the path assessment index Lji of each person corresponding to each escape path; where c1 and c2 are the influencing weight factors of the environmental assessment index Ygi and the path hidden danger value TGi, respectively.

[0032] In some embodiments, a dynamic environment-adaptive high-rise building escape route optimization system as described above includes:

[0033] Path generation: When a fire alarm is triggered in a high-rise building, optional escape routes are planned based on the locations of the people in the high-rise building;

[0034] Environmental assessment: Obtain the escape routes corresponding to each person in the high-rise building and analyze the environmental status of each escape route corresponding to each person. This will determine the environmental assessment index Ygi of each escape route based on the location of each person when the fire alarm is currently triggered. The environmental status includes the concentration of harmful gases, air temperature, and oxygen concentration.

[0035] Data processing: Receive the environmental assessment index Ygi of each person corresponding to each escape path, and analyze it in combination with the path status data packet of each escape path to obtain the path assessment index Lji of each person corresponding to each escape path;

[0036] Path selection: Receive the path evaluation index Lji of each person corresponding to each escape path, and select the corresponding escape path with the largest path evaluation index Lji as the escape path of the corresponding person when the fire alarm is currently triggered;

[0037] Sending user: Send the selected escape route to the corresponding person's mobile terminal and generate the corresponding navigation voice data packet.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] This invention divides high-rise building escape routes into multiple sub-areas and uses sensors to monitor the air temperature, hazardous gas concentration, and oxygen concentration in each sub-area in real time, achieving a refined assessment of the escape environment. This meticulous monitoring method can more accurately reflect the actual safety status of each area, providing a more precise quantitative indicator of escape route safety.

[0040] The present invention dynamically calculates the safety and accessibility of each escape route by analyzing environmental assessment indices and path status data packets in real time. This real-time dynamic path optimization method can quickly adapt to environmental changes in emergency situations such as fires and recommend the best escape route for building occupants, thereby improving evacuation efficiency and safety.

[0041] The present invention can provide personalized evacuation guidance based on each person's specific location and escape route. By sending optimized escape route information and navigation voice data packets to individual mobile terminals, each person can obtain the escape route that best suits them, thereby improving the efficiency and success rate of evacuation. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Further details, features and advantages of the present application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0043] Figure 1 It is a principle block diagram of the present invention;

[0044] Figure 2 Flowchart of the present invention. DETAILED DESCRIPTION

[0045] Several embodiments of the present application will be described in more detail below with reference to the accompanying drawings so that those skilled in the art can implement the present application. The present application can be embodied in many different forms and for many different purposes and should not be limited to the embodiments described herein. These embodiments are provided to make the present application comprehensive and complete and to fully convey the scope of the present application to those skilled in the art. The embodiments do not limit the present application.

[0046] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. It will be further understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the relevant art and / or the context of this specification, and will not be interpreted in an idealized or overly formal sense unless explicitly defined as such herein.

[0047] See also Figure 1 As shown, a dynamic environment-adaptive high-rise building escape path optimization system includes a path planning module, an environment monitoring module, a data processing module, a path determination module and a user interaction module;

[0048] The path planning module is used to plan optional escape routes based on the locations of people in a high-rise building when a fire alarm is triggered in the building;

[0049] Specifically:

[0050] When a fire alarm is triggered, a location acquisition signaling is sent to the mobile terminals of all personnel in the high-rise building. After each personnel confirms the location acquisition signaling, the location of each personnel in the high-rise building is obtained. The default confirmation is automatic after three seconds. Based on the location of each personnel in the high-rise building, combined with the building structure and the fire area, an algorithm is used to calculate the escape routes that are suitable for each personnel; the algorithm is such as the Dijkstra algorithm.

[0051] The Dijkstra algorithm is a graph search algorithm used to find the shortest path between two nodes in a graph. It considers building floors, stairways, elevator shafts, emergency exits, and other structures as nodes, and possible escape routes as edges. The Dijkstra algorithm can help calculate the shortest path from the fire point to each emergency exit, thereby planning the optimal escape route for everyone in the building. The following is the specific process by which the Dijkstra algorithm calculates each escape path:

[0052] initialization:

[0053] Mark all nodes as unvisited.

[0054] Set a distance value for each node, the distance of the starting point (near the fire point) is set to 0, and the distance of all other points is set to infinity.

[0055] Create a priority queue (or open list) to store all nodes to be visited and sort them from small to large according to their distance values.

[0056] Algorithm execution:

[0057] The node with the smallest distance is taken out from the priority queue and is called the current node.

[0058] Mark the current node as visited.

[0059] For each neighbor node of the current node, a relaxation operation is performed: the temporary distance from the starting point to the neighbor node is calculated, that is, the distance of the current node plus the weight (distance) of the edge from the current node to the neighbor node.

[0060] If the temporary distance is less than the current distance value of the neighbor node, the distance value of the neighbor node is updated to the temporary distance, and the path to the neighbor node is recorded (which can be achieved through a parent node array).

[0061] Repeat step 2:

[0062] Put the updated neighbor nodes back into the priority queue and reorder them according to the new distance values.

[0063] Repeat the above process until the priority queue is empty or all nodes have been visited.

[0064] Path backtracking:

[0065] Starting from the end node (safe exit), use the recorded parent node information to trace back to the starting point, so as to obtain the shortest path from the starting point to the end point.

[0066] Multipath computing:

[0067] In order to plan multiple optional escape paths for each person, the above algorithm can be repeatedly executed for each possible starting point.

[0068] You can set a condition, such as stopping the algorithm when the number of paths found reaches a preset value or when all possible paths have been calculated.

[0069] The environmental monitoring module is used to obtain the escape paths corresponding to each person in the high-rise building and analyze the environmental status of each escape path corresponding to each person. This module then obtains the environmental assessment index Ygi of each escape path based on the location of each person when the fire alarm is currently triggered, where i represents the number of the corresponding escape path, i=1, 2, ..., k, and k is the total number of escape paths corresponding to the person.

[0070] Specifically:

[0071] Divide each escape path of each person into sub-areas based on the preset division area, thereby obtaining the divided sub-areas corresponding to each escape path of each person;

[0072] The air temperature of each sub-area corresponding to each escape path is obtained through sensors pre-deployed in each sub-area. The air temperature of each sub-area at the current time is recorded as Wip, where p represents the sub-area number, and p = 1, 2, ..., n, where n is the total number of sub-areas for each escape path.

[0073] Obtain the concentration values ​​of various types of harmful gases at the current time point in each divided sub-area, preset the maximum allowable concentration values ​​of each type of harmful gas, and calculate the ratios between the concentration values ​​of each type of harmful gas and the corresponding maximum allowable values. Set weight coefficients for each type of harmful gas, multiply each calculated group of ratios by the corresponding weight coefficients, and then sum them to obtain the harmful gas index of each divided sub-area, which is recorded as Nip. Harmful gases include but are not limited to carbon monoxide and carbon dioxide.

[0074] Get the oxygen concentration value of each divided sub-area at the current time point, recorded as Uip;

[0075] Substitute the air temperature Wip, harmful gas index Nip and oxygen concentration Uip of each sub-area corresponding to the escape path into the formula A weighted calculation is performed to obtain the status assessment index YXip for each sub-area of ​​the corresponding escape path. YX represents the air environment impact index of the laboratory corresponding to the current monitoring period, where Rip, Eip, and Vip represent the maximum allowable air temperature, the highest allowable harmful gas index, and the lowest allowable oxygen concentration, respectively. a1, a2, and a3 represent the influence weight factors of air temperature Wip, harmful gas index Nip, and oxygen concentration Uip, respectively. Nip represents visibility, Cip represents minimum visibility, a4 represents the influence weight factor of visibility Nip, and e is a natural constant.

[0076] In addition, the danger of the escape route can be assessed based on the concentration change rate of each harmful gas, the visibility change rate, and the oxygen concentration change rate, specifically:

[0077] Obtaining the concentration parameter change rate, visibility parameter change rate, and oxygen concentration parameter change rate of each harmful gas stored in the database;

[0078] Analyze the concentration change rate of each harmful gas, the visibility change rate, and the oxygen concentration change rate and the concentration parameter change rate of each harmful gas, the visibility parameter change rate, and the oxygen concentration parameter change rate to obtain a dangerous situation coefficient;

[0079] If the danger situation coefficient is greater than the danger situation threshold stored in the database, it will prompt that the escape route is highly dangerous. If the danger situation coefficient is not greater than the danger situation threshold stored in the database, no prompt will be given.

[0080] The calculation formula of the dangerous situation coefficient is as follows:

[0081] Among them, Wx is the dangerous situation coefficient, SO is the oxygen concentration change rate, CO is the parameter change rate of oxygen concentration, a is the number of harmful gas, a=1, 2, 3, ..., A, A is the total number of harmful gas types, SBa is the concentration change rate of the a-th harmful gas, CBa is the parameter change rate of the concentration of the a-th harmful gas, SK is the visibility change rate, CK is the parameter change rate of visibility, Sm is the personnel density, Cm is the parameter personnel density, Sy is the actual air pressure in the escape area, and Cy is the parameter air pressure in the escape area.

[0082] The concentration change rates of various hazardous gases and oxygen concentrations are obtained from the database. This data is updated in real time to reflect actual conditions. It covers multiple key factors, including oxygen concentration, hazardous gases, visibility, crowd density, and air pressure, all of which are crucial parameters affecting escape safety. By comprehensively considering these factors, the assessment provides a more comprehensive picture of the actual danger level of the escape environment. Evaluating these change rates enables more timely responses, allowing for rapid identification of deteriorating environmental trends, enabling preventive measures or adjustments to escape strategies. A decrease in oxygen concentration may coincide with an increase in hazardous gas concentration, and these two factors are often correlated. The release of hazardous gases in a fire is often accompanied by oxygen depletion. Reduced visibility directly affects occupants' movement speed and direction of movement. High crowd density in low visibility conditions is particularly dangerous, as it can cause greater confusion and hinder effective evacuation. Changes in air pressure can affect the spread of flames and smoke, ultimately impacting the safety of the entire escape environment. The calculated danger coefficient is compared with a preset danger threshold. If the coefficient exceeds the threshold, the route presents a significant danger, and the system will issue a corresponding warning. If it does not, no warning is required.

[0083] Extract the state evaluation index YXip of each divided sub-area of ​​the corresponding escape path at the current time point, and calculate the mean to obtain the state mean of the corresponding escape path. At the same time, extract the highest state evaluation index and the lowest state evaluation index among the state evaluation index YXip of each divided sub-area as the state peak value and state valley value of the corresponding escape path respectively.

[0084] Preset the reference threshold index of the state evaluation index YXip of each sub-area of ​​the corresponding escape path, extract the state mean, state peak, and state valley of the corresponding escape path, and calculate the ratio with the reference threshold index respectively, that is, calculate by reference threshold index / state mean, reference threshold index / state peak, and reference threshold index / state valley;

[0085] The mean ratio, peak ratio, and valley ratio of the corresponding escape path are obtained, and the mean ratio, peak ratio, and valley ratio of the corresponding escape path are used as the length, width, and height of the three-dimensional rectangle, respectively, to construct a three-dimensional rectangular model of the corresponding escape path;

[0086] The surface area of ​​the three-dimensional rectangular model corresponding to the escape path is used as the environmental assessment index Ygi of the corresponding escape path;

[0087] It should be noted that by dividing the escape route into multiple sub-areas and monitoring the temperature, harmful gas concentration, and oxygen concentration in each sub-area, a refined assessment of the escape environment is achieved;

[0088] By calculating the status assessment index of each sub-area, the module can quantify the safety of each area and provide a scientific basis for the selection of escape routes;

[0089] In summary, this method achieves a refined assessment and dynamic optimization of the environmental conditions of each escape route within a high-rise building, ensuring that the safest and most accessible escape route is recommended to building occupants in an emergency. By real-time monitoring and analysis of key environmental parameters such as air temperature, hazardous gas concentration, and oxygen concentration, and combining weight coefficients and reference thresholds for comprehensive evaluation, this method quantifies the safety of each sub-area and constructs a three-dimensional rectangular model reflecting the environmental risk of the escape route. Using the model's surface area as an environmental assessment index, it provides an intuitive and quantitative safety assessment standard for each escape route. This effectively guides personnel in selecting the optimal escape route in emergencies such as fires, improving evacuation efficiency, reducing safety risks, and ensuring personnel safety.

[0090] By calculating the surface area of ​​the three-dimensional rectangular model as the environmental assessment index, a comprehensive safety assessment standard is provided for each escape route.

[0091] The data processing module is used to receive the environmental assessment index Ygi of each person corresponding to each escape path, and analyze it in combination with the path status data packet of each escape path to obtain the path assessment index Lji of each person corresponding to each escape path; the path status data packet includes the required walking distance, estimated time and path route of the path;

[0092] Specifically:

[0093] Obtain the required walking distance and estimated time for each person corresponding to each escape path, recorded as Tai and Tbi respectively;

[0094] At the same time, the routes of each person corresponding to each escape route are analyzed, the position closest to the fire occurrence point in the route is selected, and the straight-line distance between the two is calculated as the hidden danger distance Tci;

[0095] Substitute the required walking distance Tai, estimated time Tbi and hidden danger distance Tci of each person corresponding to each escape path into the formula Perform a weighted calculation to obtain the path hidden danger value TGi of each escape path; where b1, b2, and b3 are the influence weight factors of the required walking distance Tai, the estimated time Tbi, and the hidden danger distance Tci, respectively;

[0096] The environmental assessment index Ygi and path hidden danger value TGi of each escape path for each person are extracted and substituted into the formula Lji=tanh(1+Ygi×c1+TGi×c2) for weighted calculation, thereby obtaining the path assessment index Lji of each person corresponding to each escape path; where c1 and c2 are the influence weight factors of the environmental assessment index Ygi and the path hidden danger value TGi, respectively;

[0097] The calculation formula of the path evaluation index Lji of the escape path can also be Lji=tanh(1+e Ygi ×c1+TGi×c2+Wx×c3 ), where c3 is the impact weight factor of the dangerous situation coefficient.

[0098] By combining the environmental assessment index and the path hazard value, the calculation can comprehensively reflect the safety of the path. The environmental assessment index may take into account environmental factors such as gas concentration and oxygen content, while the path hazard value may include factors such as physical obstacles and the smoothness of the escape route. This comprehensive consideration can more accurately reflect the actual safety of the escape route. The introduction of nonlinear characteristics allows small changes in the environmental assessment to cause significant adjustments to the path assessment, emphasizing the severity of environmental conditions. For example, if the environment is extremely unsafe, even minor changes can significantly affect the escape path assessment, reflecting the nonlinear impact of environmental hazards. This formula can quantify the path assessment, provide a basis for decision-making, and enable a more standardized assessment of the safety of escape routes in emergency situations.

[0099] Comprehensive assessment of route safety: By considering travel distance, estimated time, and distance to potential hazards, the safety and feasibility of each escape route can be comprehensively assessed. This helps identify routes that may be too close to the fire or require too long a travel time, posing a higher risk.

[0100] Quantifying path risk: Through weighted calculation, the algorithm quantifies the hidden danger value (TGi) of each path, making the path risk assessment more accurate and objective.

[0101] Optimize escape route selection: Combining the environmental assessment index (Ygi) and the path hidden danger value (TGi), the algorithm further calculates the assessment index (Lji) of each path, providing a comprehensive decision-making basis for the final escape route selection.

[0102] Improve evacuation efficiency: By identifying the optimal escape route, people can be guided to evacuate quickly and safely, reducing confusion and congestion in emergency situations, thereby improving overall evacuation efficiency.

[0103] Personalized evacuation guidance: The algorithm provides each person with a personalized assessment based on their specific location and escape route, making evacuation guidance more accurate and helping to improve everyone's escape success rate.

[0104] Dynamically adapt to environmental changes: The algorithm can dynamically adjust path assessments based on real-time data, allowing escape routes to be updated in a timely manner to respond to environmental changes as emergencies such as fires develop.

[0105] The path determination module is used to receive the path evaluation index Lji of each person corresponding to each escape path, and select the corresponding escape path with the largest path evaluation index Lji as the escape path of the corresponding person when the fire alarm is currently triggered;

[0106] The user interaction module is used to send the selected escape route to the mobile terminal of the corresponding person and generate a corresponding navigation voice data packet.

[0107] Example 2

[0108] See also Figure 2 As shown, based on the dynamic environment-adaptive high-rise building escape path optimization system provided in Example 1 of this application, Example 2 of this application proposes a dynamic environment-adaptive high-rise building escape path optimization method. Example 2 is merely a preferred embodiment of Example 1, and the implementation of Example 2 will not affect the independent implementation of Example 1.

[0109] Specifically, the difference of the dynamic environment-adaptive high-rise building escape route optimization method provided in Example 2 of the present application is that it includes:

[0110] Path generation: When a fire alarm is triggered in a high-rise building, optional escape routes are planned based on the locations of the people in the high-rise building;

[0111] Environmental assessment: Obtain the escape routes corresponding to each person in the high-rise building and analyze the environmental status of each escape route corresponding to each person. This will determine the environmental assessment index Ygi of each escape route based on the location of each person when the fire alarm is currently triggered. The environmental status includes the concentration of harmful gases, air temperature, and oxygen concentration.

[0112] Data processing: Receive the environmental assessment index Ygi of each person corresponding to each escape path, and analyze it in combination with the path status data packet of each escape path to obtain the path assessment index Lji of each person corresponding to each escape path;

[0113] Path selection: receiving the path evaluation index Lji of each person corresponding to each escape path, and selecting the escape path of the corresponding person when the fire alarm is currently triggered based on the evaluation results of the path evaluation index Lji of each escape path;

[0114] Sending user: Send the selected escape route to the corresponding person's mobile terminal and generate the corresponding navigation voice data packet;

[0115] The above formulas are obtained by collecting a large amount of data and performing software simulation to select a formula that is close to the actual value. The influence weight factors and specific coefficient values ​​in the formulas are set by those skilled in the art based on actual conditions and can be adjusted and modified later;

[0116] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, an ATA hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state ATA hard disk.

[0117] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0118] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0119] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0120] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, and may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment based on actual needs.

[0121] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0122] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile ATA hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0123] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A dynamic environment-adaptive high-rise building escape route optimization system, characterized in that: Including path planning module, environment monitoring module, data processing module, path determination module and user interaction module: The path planning module is used to plan various optional escape paths based on the locations of various personnel in the high-rise building when a fire alarm is triggered in the high-rise building; The environmental monitoring module is used to obtain the escape paths corresponding to each person in the high-rise building, analyze the environmental status of each escape path corresponding to each person, and thereby obtain the environmental assessment index Ygi of each escape path based on the location of each person when the fire alarm is currently triggered, where i represents the number corresponding to each escape path, i=1, 2, ..., k, k is the total number of escape paths corresponding to the person; The data processing module is used to receive the environmental assessment index Ygi of each person corresponding to each escape path, and analyze it in combination with the path status data packet of each escape path, thereby obtaining the path assessment index Lji of each person corresponding to each escape path, wherein the path status data packet includes the required walking distance, estimated time and path route of the path; The path determination module is used to receive the path evaluation index Lji of each person corresponding to each escape path, and select the escape path of the corresponding person when the fire alarm is currently triggered based on the evaluation result of the path evaluation index Lji of each escape path; The user interaction module is used to send the selected escape route to the mobile terminal of the corresponding person and generate a corresponding navigation voice data packet.

2. A dynamic environment-adaptive high-rise building escape route optimization system according to claim 1, characterized in that: The environmental status of each escape path corresponding to each person is analyzed as follows: Divide each escape path of each person into sub-areas based on the preset division area, thereby obtaining the division sub-areas corresponding to each escape path of each person; Obtain the air temperature of each sub-area corresponding to each escape path, and record the air temperature of each sub-area corresponding to the current time point as Wip, where p represents the number of the sub-area, p=1, 2, .., n, and n is the total number of sub-areas divided by each escape path; Obtain the concentration values ​​of various types of harmful gases at the current time point in each divided sub-area, preset the maximum allowable values ​​of the concentrations of various types of harmful gases, and respectively calculate the ratios between the concentration values ​​of various types of harmful gases and the corresponding maximum allowable values, set the weight coefficients of various types of harmful gases, multiply the calculated ratios of each group by the corresponding weight coefficients, and then sum them up to obtain the harmful gas index of each divided sub-area, which is recorded as Nip; The oxygen concentration of each divided sub-area corresponding to the current time point is obtained, which is recorded as Uip.

3. A dynamic environment-adaptive high-rise building escape route optimization system according to claim 2, characterized in that: The analysis of the environmental status of each escape path corresponding to each person also includes: Substitute the air temperature Wip, harmful gas index Nip and oxygen concentration Uip of each sub-area corresponding to each escape path into the formula: The state assessment index YXip of each divided sub-area of ​​the corresponding escape path is obtained, where Rip, Eip and Vip represent the maximum allowable air temperature, the highest allowable harmful gas index and the minimum allowable oxygen concentration respectively; a1, a2 and a3 represent the influence weight factors of air temperature Wip, harmful gas index Nip and oxygen concentration Uip respectively, Nip is visibility, Cip is the minimum visibility, a4 is the influence weight factor of visibility Nip, and e is a natural constant.

4. A dynamic environment-adaptive high-rise building escape route optimization system according to claim 3, characterized in that: The environmental assessment index Ygi based on each escape path of each person's location when the fire alarm is currently triggered is specifically: Extract the state evaluation index YXip of each divided sub-area of ​​the corresponding escape path at the current time point, and calculate the mean of multiple state evaluation indexes YXip to obtain the state mean of the corresponding escape path, and at the same time extract the highest state evaluation index and the lowest state evaluation index among the state evaluation indexes YXip of each divided sub-area as the state peak value and state valley value of the corresponding escape path respectively; Preset the reference threshold index of the state evaluation index YXip of each divided sub-area of ​​the corresponding escape path, extract the state mean, state peak and state valley of the corresponding escape path, and calculate the ratio with the reference threshold index respectively, that is, calculate by reference threshold index / state mean, reference threshold index / state peak, reference threshold index / state valley; Thus, the mean ratio, peak ratio and valley ratio are obtained, and the mean ratio, peak ratio and valley ratio of the corresponding escape path are used as the length value, width value and height value of the three-dimensional rectangle respectively, to construct a three-dimensional rectangular model of the corresponding escape path; The surface area of ​​the three-dimensional rectangular model corresponding to the escape path is constructed as the environmental assessment index Ygi of the corresponding escape path.

5. The dynamic environment-adaptive high-rise building escape route optimization system according to claim 1, characterized in that: The receiving of the environmental assessment index Ygi corresponding to each escape path of each person and analyzing it in combination with the path status data packet of each escape path are specifically as follows: Obtain the required walking distance and estimated time for each person corresponding to each escape path, recorded as Tai and Tbi respectively; At the same time, the paths of each person corresponding to each escape path are analyzed, the position closest to the fire occurrence point in the route is selected, and the straight-line distance between the two is calculated as the hidden danger distance Tci; Substitute the required walking distance Tai, estimated time Tbi and hidden danger distance Tci of each person corresponding to each escape path into the formula Perform weighted calculation to obtain the path hidden danger value TGi of each escape path; Among them, b1, b2 and b3 are the influencing weight factors of the required walking distance Tai, the estimated time Tbi and the hidden danger distance Tci respectively.

6. A dynamic environment-adaptive high-rise building escape route optimization system according to claim 5, characterized in that: The path evaluation index Lji of each person corresponding to each escape path is obtained, specifically: The environmental assessment index Ygi and path hidden danger value TGi of each escape path of each person are extracted, and substituted into the formula Lji=tanh(1+Ygi×c1+TGi×c2) for weighted calculation, so as to obtain the path assessment index Lji of each person corresponding to each escape path; where c1 and c2 are the influencing weight factors of the environmental assessment index Ygi and the path hidden danger value TGi, respectively.

7. A dynamic environment-adaptive high-rise building escape path optimization method, applied to a dynamic environment-adaptive high-rise building escape path optimization system as described in any one of claims 1 to 6, characterized in that: include: Path generation: When a fire alarm is triggered in a high-rise building, optional escape paths are planned based on the locations of people in the high-rise building; Environmental assessment: Obtain the escape paths corresponding to each person in the high-rise building, analyze the environmental status of each escape path corresponding to each person, and thus obtain the environmental assessment index Ygi of each escape path based on the location of each person when the fire alarm is currently triggered, where the environmental status includes the concentration of harmful gases, air temperature and oxygen concentration; Data processing: receiving the environmental assessment index Ygi of each person corresponding to each escape path, and analyzing it in combination with the path status data packet of each escape path, thereby obtaining the path assessment index Lji of each person corresponding to each escape path; Path selection: receiving the path evaluation index Lji of each person corresponding to each escape path, and selecting the escape path of the corresponding person when the fire alarm is currently triggered based on the evaluation results of the path evaluation index Lji of each escape path; Sending user: Send the selected escape route to the mobile terminal of the corresponding person and generate the corresponding navigation voice data packet.

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