Design data digital supervision system and method applied to intelligent building

Abstract

The invention discloses a design data digital supervision system and method applied to an intelligent building, and relates to the technical field of building area supervision, and the system comprises a design data processing unit, a data analysis module, and an intelligent building area supervision module. The design data processing unit is used for collecting a design drawing adopted by the intelligent building, extracting information of all areas in the building and information of connecting channels among all the areas in the design drawing, and constructing a building area connected graph; the data analysis module calculates the regional congestion degree of each regional node and the passing cost of reaching a building exit in real time, and determines the number of crowds transferred among the regional nodes; and the intelligent building area supervision module is used for monitoring personnel distribution of each area node in real time, judging whether each area node can accommodate crowd transfer or not, and guiding crowds of each area node in a building according to an iterative calculation result of a crowd transfer quantity which can be absorbed by each area node.

Description

Technical Field

[0001] The present invention relates to the technical field of building area supervision, and in particular to a digital supervision system and method for design data applied to intelligent buildings. Background Art

[0002] In modern intelligent buildings, evacuation management of high-density crowds at the end of large-scale gatherings and sudden disasters is an essential function;

[0003] In today's building crowd evacuation management, it is common to place fixed safety channel guide signs or set up guides at the key road forks inside the building. Most of them are based on fixed evacuation paths for crowd distribution, and lack consideration of the congestion of different areas in the intelligent building and the evacuation cost of the distance to the exit. Therefore, in actual operation, due to the different traffic efficiency of different channels, crowds often get stuck in some small channels and small areas, resulting in uneven crowd evacuation, greatly increasing the probability of dangerous events such as trampling, while reducing the actual evacuation efficiency of the crowd;

[0004] Therefore, a digital supervision system and method for design data applied to intelligent buildings is needed to achieve real-time supervision of evacuated people, optimize evacuation efficiency, and improve evacuation safety. Summary of the invention

[0005] The purpose of the present invention is to provide a digital supervision system and method for design data applied to intelligent buildings to solve the problems raised in the prior art.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A digital supervision method for design data applied to intelligent buildings, the method comprising the following steps:

[0008] Step S100: Acquire intelligent building design data, divide and mark each area in the building and the channels between each area, and construct a building area connectivity map; the intelligent building design data refers to the marked data in the spatial design drawings of each area in the intelligent building;

[0009] Step S200: obtaining a personnel distribution image of each area in the intelligent building, identifying the number of personnel in each area, and calculating the regional congestion degree of each regional node according to the building area connectivity graph;

[0010] Step S300: Calculate the travel cost of each regional node according to the building area connectivity graph, and analyze the comprehensive travel cost of each regional node to reach the building exit through each path;

[0011] Step S400: According to the congestion degree of nodes in each area and the comprehensive travel cost to the exit of the intelligent building, the number of people transferred between adjacent areas is determined, and the people in each area of ​​the intelligent building are iteratively guided.

[0012] In the above technical solution, step S100 is divided into the following steps:

[0013] Step S101: obtaining the design drawings used by the intelligent building, and extracting the information of each area in the building and the information of the connection channels between the areas in the design drawings;

[0014] Step S102: taking each area as a regional node of the current intelligent building, taking the connecting channels between each area as the connecting lines between the regional nodes of the current intelligent building, and constructing a building area connectivity map;

[0015] When constructing a building area connectivity map, the area of ​​each area in the area information is used as the corresponding area node weight, and the maximum traffic rate of each area connection channel in the area connection channel information is used as the connection line weight between area nodes; by analyzing the intelligent building design data to construct a building area connectivity map, the rationality of the transfer strategy can be effectively improved when supervising the transfer of people in various areas of the building.

[0016] In the above technical solution, step S200 includes the following contents:

[0017] Install image sensors in each area of ​​the intelligent building, obtain the distribution image of people in each area node, count the real-time number of people in each area node, and calculate the regional congestion of each area node; for any area node a, according to the formula:

[0018]

[0019] Among them, C a is the regional congestion degree of regional node a, N a is the real-time number of people in regional node a, S a is the weight of regional node a;

[0020] Set the upper threshold of regional congestion C′ and normalize the regional congestion of each regional node. The normalization formula is as follows:

[0021]

[0022] Among them, C′ a is the normalized congestion degree of regional node a; when C′ a >1, C′ a The value is corrected to 1;

[0023] By calculating and analyzing the congestion degree of each area, the distribution status of the crowd in each area of ​​the building is reflected, and a scientific data basis is provided for the crowd transfer strategy between areas, ensuring the spatial rationality and safety of the crowd during actual evacuation and transfer, and reducing the safety risks during crowd evacuation.

[0024] In the above technical solution, step S300 includes the following contents:

[0025] Obtain the plane map of each regional node in the building area connectivity map, measure the travel distance through each regional node according to the orientation of the connecting channel between each regional node and the adjacent regional node, and calculate the comprehensive travel cost of each path from regional node a to the exit of the intelligent building in combination with the weight of the connecting line between the regional nodes;

[0026] For any path p, according to the formula:

[0027]

[0028] Cost(a, p) is the comprehensive cost of regional node a to reach the exit of the intelligent building through path p, i is the number of regional nodes along path p, N p is the number of regional nodes that path p passes through, Cost(i) is the cost of passing regional node i, l i is the travel distance of path p through regional node i, k v is the inter-regional traffic coefficient, v i is the weight of the connection line between regional node i and the next regional node, c 1 and c 2 is a positive constant parameter, C′ i is the normalized congestion degree of regional node i; by combining the distance to the exit of each area, regional congestion, and channel traffic rate to analyze the travel costs of different paths, it reflects the additional impact of high congestion, narrow channels, and distance to the exit on the actual evacuation efficiency during the evacuation of high-density crowds, providing a more reliable data basis for subsequent crowd transfer and evacuation strategies.

[0029] In the above technical solution, step S400 is divided into the following steps:

[0030] Step S401: using a path planning algorithm to analyze the path with the minimum comprehensive travel cost from each regional node to the exit of the intelligent building;

[0031] Step S402: Traverse forward along each path in sequence from the regional node adjacent to the exit, calculate the crowd transfer weight between adjacent regional nodes in each path and the crowd transfer capacity of each regional node, and determine the number of people transferred between each regional node;

[0032] Step S403: according to the change in the number of people in each area of ​​the intelligent building, iteratively guide the travel routes of people in each area.

[0033] In the above technical solution, the method for calculating the number of people transferred between adjacent regional nodes in each path in step S402 is as follows:

[0034] Extract the path information with the minimum comprehensive travel cost from all regional nodes to the exit of the intelligent building, and obtain, for any regional node n, screen out all the paths passing through regional node n, and for any screened path, calculate the population transfer weight of the previous adjacent regional node of the current path regional node n to regional node n, according to the formula:

[0035]

[0036] Among them, w n-1 is the population transfer weight of the population from the previous adjacent regional node of the current path regional node n to regional node n, n-1 is the previous adjacent regional node of the current path regional node n, Cost(n-1, p n-1 ) is the path p of the regional node n-1 through which the node belongs n-1 The comprehensive cost of reaching the exit of the smart building;

[0037] Traverse forward along each path from the regional node adjacent to the exit. For any regional node n, screen all paths involving regional node n, and obtain the population transfer weights of all previous adjacent regional nodes of regional node n in the screened path. According to the formula: Perform weighted scaling on the population transfer weights of each node;

[0038] Get the preset upper limit threshold C' of regional congestion, according to the formula: Calculate the population transfer capacity N′ of regional node n n ; where C′ n is the normalized congestion degree of regional node n, N n is the real-time number of personnel in regional node n; when C′ n >C′, change N′ n Corrected to 0;

[0039] Then, the population transfer weights of each previous adjacent regional node of regional node n are multiplied by the population transfer capacity of regional node n to obtain the number of people transferred from each previous adjacent regional node to regional node n;

[0040] The population in each area is weighted and allocated to ensure the balance of population in different areas during evacuation. At the same time, the real-time traffic costs of each area are combined to ensure the traffic stability when the population in each area is transferred and allocated, thereby improving the actual efficiency of population transfer.

[0041] In the above technical solution, the method for iteratively guiding the travel routes of people in each area in step S403 is as follows:

[0042] Set a threshold for the proportion of people transferring, and inversely deduce the threshold for the number of people transferring in each area based on the regional congestion calculation method;

[0043] When the crowd begins to move, the regional congestion and crowd transfer capacity of each regional node are calculated, the number of people to be transferred between regional nodes is determined, and the crowd close to the inter-regional connection channel is guided to transfer;

[0044] During the crowd transfer process, if the regional congestion of any regional node reaches the upper threshold of the regional congestion, the regional node is monitored. If the crowd transfer capacity of the regional node is greater than the crowd transfer quantity threshold, it is determined that the regional node can accommodate crowd transfer, and the above method is used to iteratively calculate the number of crowd transfers that can be absorbed by the regional node to guide the crowd;

[0045] If the population transfer capacity of the region is greater than the number of people that the regional node can absorb from all previous regional nodes in the path involved, all people in the previous regional nodes will be transferred;

[0046] By monitoring the crowd in real time and triggering the iterative calculation of crowd transfer allocation according to the crowd transfer ratio threshold judgment result, the real-time nature of the actual operation is ensured while avoiding frequent algorithm calculations, thereby improving the overall efficiency of the system and ensuring the timeliness of crowd evacuation guidance.

[0047] A digital design data supervision system for intelligent buildings using the digital design data supervision method for intelligent buildings described in the above technical solution, the system comprising: a design data processing unit, a data analysis module, and an intelligent building area supervision module;

[0048] The design data processing unit is used to collect the design drawings used in the intelligent building, extract the information of each area in the building and the connection channel information between the areas in the design drawings, and construct a building area connectivity map; the data analysis module calculates the regional congestion of each regional node and the travel cost to reach the building exit in real time, and determines the number of people transferring between regional nodes; the intelligent building regional supervision module is used to monitor the distribution of personnel in each regional node in real time, determine whether each regional node can accommodate the transfer of people, and iterate the calculation results according to the number of people transfer that each regional node can absorb, and guide the people in each regional node in the building.

[0049] In the above technical solution, the data analysis module includes: a regional congestion calculation unit, a traffic cost analysis unit, and a transfer path planning unit;

[0050] The regional congestion calculation unit calculates the regional congestion data of each regional node according to the number of people in each area; the traffic cost analysis unit is used to analyze the traffic cost of each regional node in the intelligent building where people transfer; the transfer path planning unit is used to calculate the comprehensive traffic cost of people in each area transferring to the exit of the intelligent building, and plan the path with the minimum comprehensive traffic cost for people transfer in each area.

[0051] In the above technical solution, the intelligent building area supervision module includes: an area monitoring unit, a crowd transfer decision unit, and a crowd transfer guidance unit;

[0052] The regional monitoring unit is used to monitor the distribution of personnel in each area of ​​the intelligent building and identify the number of personnel in each area; the crowd transfer decision unit is used to analyze the crowd transfer weight of each regional node to transfer people to the next regional node along the personnel transfer path, synchronously calculate the crowd transfer capacity in each regional node, determine the number of people transferred in each regional node, and judge whether each regional node can accommodate crowd transfer; when determining that the regional node can accommodate crowd transfer, the crowd transfer guiding unit sends a regional transfer signal to the personnel who are closer to the inter-regional connection channel, and synchronously sends the travel direction information of the target regional node.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] The present invention analyzes the intelligent building design data, constructs a building area connectivity map, monitors the distribution of people in each area of ​​the intelligent building in real time, calculates the real-time distribution of people in each area of ​​the intelligent building, calculates the congestion of each area, the travel cost to the exit and other data, takes into account the regional congestion and the efficiency of crowd transfer and evacuation, achieves more accurate crowd transfer allocation, and improves the efficiency and safety of crowd transfer and evacuation; the present invention identifies the change in the number of people in each area based on real-time monitoring, controls the iterative calculation of crowd transfer, reduces the redundant calculation of the algorithm, and ensures the applicability in actual high-timeliness scenarios; the present invention determines the number of people to be transferred based on the congestion of each area, ensures the balance of congestion between areas, avoids local high congestion, and avoids safety risks during evacuation and transfer. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A flow chart of a method for digitally supervising design data applied to intelligent buildings according to the present invention;

[0056] Figure 2 The present invention discloses an organizational structure diagram of a design data digital supervision system applied to intelligent buildings. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] Example: See Figure 1-Figure 2 , the present invention provides a technical solution,

[0059] like Figure 1 As shown, the present invention provides a digital supervision method for design data applied to intelligent buildings, and the method is divided into the following steps:

[0060] Step S100: Acquire intelligent building design data, divide and mark each area in the building and the channels between each area, and construct a building area connectivity map; the intelligent building design data refers to the marked data in the spatial design drawings of each area in the intelligent building;

[0061] Step S200: obtaining a personnel distribution image of each area in the intelligent building, identifying the number of personnel in each area, and calculating the regional congestion degree of each regional node according to the building area connectivity graph;

[0062] Step S300: Calculate the travel cost of each regional node according to the building area connectivity graph, and analyze the comprehensive travel cost of each regional node to reach the building exit through each path;

[0063] Step S400: According to the congestion degree of nodes in each area and the comprehensive travel cost to the exit of the intelligent building, the number of people transferred between adjacent areas is determined, and the people in each area of ​​the intelligent building are iteratively guided.

[0064] In the above technical solution, step S100 is divided into the following steps:

[0065] Step S101: obtaining the design drawings used by the intelligent building, and extracting the information of each area in the building and the information of the connection channels between the areas in the design drawings;

[0066] Step S102: taking each area as a regional node of the current intelligent building, taking the connecting channels between each area as the connecting lines between the regional nodes of the current intelligent building, and constructing a building area connectivity map;

[0067] When constructing the building area connectivity map, the area of ​​each area in the area information is used as the corresponding area node weight, and the maximum traffic rate of each area connection channel in the area connection channel information is used as the connection line weight between area nodes;

[0068] In the specific implementation, according to the internal construction drawings of the building, analyze the connection relationship between the various areas inside the building, and calculate the scale of each area and the maximum number of pedestrians per unit time between the areas based on the data in the construction drawings and the specifications of the connecting passages; in addition, if complex calculations need to be avoided, the corridors can be divided into regional nodes, and the regional boundaries can be used as the connecting lines between the areas;

[0069] When actually analyzing the traffic efficiency of connecting channels, if there are periodic traffic tools such as elevators, the average calculation can be made based on the time it takes for the elevator to pass through different floors and the maximum number of people the elevator can carry, and then the maximum traffic rate of the elevator can be analyzed.

[0070] In the above technical solution, step S200 includes the following contents:

[0071] Install image sensors in each area of ​​the intelligent building, obtain the distribution image of people in each area node, count the real-time number of people in each area node, and calculate the regional congestion of each area node; for any area node a, according to the formula:

[0072]

[0073] Among them, C a is the regional congestion degree of regional node a, N a is the real-time number of people in regional node a, S a is the weight of regional node a;

[0074] Set the upper threshold of regional congestion C′ and normalize the regional congestion of each regional node. The normalization formula is as follows:

[0075]

[0076] Among them, C′ a is the normalized congestion degree of regional node a; when C′ a >1, C′ a The value is corrected to 1.

[0077] In the above technical solution, step S300 includes the following contents:

[0078] Obtain the plane map of each regional node in the building area connectivity map, measure the travel distance through each regional node according to the orientation of the connecting channel between each regional node and the adjacent regional node, and calculate the comprehensive travel cost of each path from regional node a to the exit of the intelligent building in combination with the weight of the connecting line between the regional nodes;

[0079] For any path p, according to the formula:

[0080]

[0081] Cost(a, p) is the comprehensive cost of regional node a to reach the exit of the intelligent building through path p, i is the number of regional nodes along path p, N p is the number of regional nodes that path p passes through, Cost(i) is the cost of passing regional node i, l i is the travel distance of path p through regional node i, k v is the inter-regional traffic coefficient, v i is the weight of the connection line between regional node i and the next regional node, c 1 and c 2 is a positive constant parameter, C′ i is the normalized congestion degree of regional node i;

[0082] In the specific implementation, it is taken into consideration that when people are evacuated and transferred, the farther they are from the building exit, the more congested the route area is, and the lower the efficiency of the connecting channels between the route areas is, the longer the actual evacuation time will be. Therefore, the travel cost of each area and path is calculated based on a comprehensive consideration of various parameters.

[0083] In the above technical solution, step S400 is divided into the following steps:

[0084] Step S401: using a path planning algorithm to analyze the path with the minimum comprehensive travel cost from each regional node to the exit of the intelligent building;

[0085] Step S402: Traverse forward along each path in sequence from the regional node adjacent to the exit, calculate the crowd transfer weight between adjacent regional nodes in each path and the crowd transfer capacity of each regional node, and determine the number of people transferred between each regional node;

[0086] Step S403: according to the change in the number of people in each area of ​​the intelligent building, iteratively guide the travel routes of people in each area.

[0087] In the above technical solution, the method for calculating the number of people transferred between adjacent regional nodes in each path in step S402 is as follows:

[0088] Extract the path information with the minimum comprehensive travel cost from all regional nodes to the exit of the intelligent building, and obtain, for any regional node n, screen out all the paths passing through regional node n, and for any screened path, calculate the population transfer weight of the previous adjacent regional node of the current path regional node n to regional node n, according to the formula:

[0089]

[0090] Among them, w n-1is the population transfer weight of the population from the previous adjacent regional node of the current path regional node n to regional node n, n-1 is the previous adjacent regional node of the current path regional node n, Cost(n-1, p n-1 ) is the path p of the regional node n-1 through which the node belongs n-1 The comprehensive cost of reaching the exit of the smart building;

[0091] Traverse forward along each path from the regional node adjacent to the exit. For any regional node n, screen all paths involving regional node n, and obtain the population transfer weights of all previous adjacent regional nodes of regional node n in the screened path. According to the formula: Perform weighted scaling on the population transfer weights of each node;

[0092] Get the preset upper limit threshold C' of regional congestion, according to the formula: Calculate the population transfer capacity N′ of regional node n n ; where C′ n is the normalized congestion degree of regional node n, N n is the real-time number of personnel in regional node n; when C′ n >C′, change N′ n Corrected to 0;

[0093] Then, the population transfer weights of each previous adjacent regional node of regional node n are multiplied by the population transfer capacity of regional node n to obtain the number of people transferred from each previous adjacent regional node to regional node n;

[0094] In the specific implementation, after selecting the regional node, analyze whether the path with the minimum comprehensive travel cost of the remaining regional nodes passes through the current regional node. If so, screen all the previous regional nodes of the current regional node in each path to calculate the population transfer weight.

[0095] In the above technical solution, the method for iteratively guiding the travel routes of people in each area in step S403 is as follows:

[0096] Set a threshold for the proportion of people transferring, and inversely deduce the threshold for the number of people transferring in each area based on the regional congestion calculation method;

[0097] When the crowd begins to move, the regional congestion and crowd transfer capacity of each regional node are calculated, the number of people to be transferred between regional nodes is determined, and the crowd close to the inter-regional connection channel is guided to transfer;

[0098] During the crowd transfer process, if the regional congestion of any regional node reaches the upper threshold of the regional congestion, the regional node is monitored. If the crowd transfer capacity of the regional node is greater than the crowd transfer quantity threshold, it is determined that the regional node can accommodate crowd transfer, and the above method is used to iteratively calculate the number of crowd transfers that can be absorbed by the regional node to guide the crowd;

[0099] If the population transfer capacity of the region is greater than the number of people that the regional node can absorb from all previous regional nodes in the path involved, all people in the previous regional nodes will be transferred;

[0100] In the specific implementation, in a single iterative calculation, since the collected data is single data at the same time, the transfer distribution flow of the crowd in each area will show a trend of converging to the exit, and if different paths do not separate after the initial intersection, there is no need to consider the scenario of divergent distribution from a single regional node to multiple regional nodes; in addition, due to the real-time change in the number of people at the nodes in each area, the regional congestion also changes accordingly, so the real-time analysis of the minimum comprehensive travel cost path of each area is adaptive, and then the crowd in the area far from the exit is guided to converge to the exit, avoiding a small number of people being allocated to the area far from the exit due to the proportional distribution calculation method; after guiding the people in each area of ​​the building to converge to the exit, the number of people further transferred to the exit in each area is calculated according to the crowd transfer weight, among which the crowd transfer weight is calculated according to the travel cost to ensure that the time spent on the transfer of people in each area is relatively similar, further improving the efficiency of the overall crowd transfer and evacuation supervision.

[0101] like Figure 2 The present invention also provides a digital supervision system for design data applied to intelligent buildings, the system comprising: a design data processing unit, a data analysis module, and an intelligent building area supervision module;

[0102] The design data processing unit is used to collect the design drawings used in the intelligent building, extract the information of each area in the building and the connection channel information between the areas in the design drawings, and construct a building area connectivity map; the data analysis module calculates the regional congestion of each regional node and the travel cost to reach the building exit in real time, and determines the number of people transferring between regional nodes; the intelligent building regional supervision module is used to monitor the distribution of personnel in each regional node in real time, determine whether each regional node can accommodate the transfer of people, and iterate the calculation results according to the number of people transfer that each regional node can absorb, and guide the people in each regional node in the building.

[0103] In the above technical solution, the data analysis module includes: a regional congestion calculation unit, a traffic cost analysis unit, and a transfer path planning unit;

[0104] The regional congestion calculation unit calculates the regional congestion data of each regional node according to the number of people in each area; the traffic cost analysis unit is used to analyze the traffic cost of each regional node in the intelligent building where people transfer; the transfer path planning unit is used to calculate the comprehensive traffic cost of people in each area transferring to the exit of the intelligent building, and plan the path with the minimum comprehensive traffic cost for people transfer in each area.

[0105] In the above technical solution, the intelligent building area supervision module includes: an area monitoring unit, a crowd transfer decision unit, and a crowd transfer guidance unit;

[0106] The regional monitoring unit is used to monitor the distribution of personnel in each area of ​​the intelligent building and identify the number of personnel in each area; the crowd transfer decision unit is used to analyze the crowd transfer weight of each regional node to transfer people to the next regional node along the personnel transfer path, synchronously calculate the crowd transfer capacity in each regional node, determine the number of people transferred in each regional node, and judge whether each regional node can accommodate crowd transfer; when determining that the regional node can accommodate crowd transfer, the crowd transfer guiding unit sends a regional transfer signal to the personnel who are closer to the inter-regional connection channel, and synchronously sends the travel direction information of the target regional node.

[0107] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A digital supervision method for design data applied to intelligent buildings, characterized in that , the method is divided into the following steps: Step S100: Acquire intelligent building design data, divide and mark the areas in the building and the passages between the areas, and construct a building area connectivity map; The intelligent building design data refers to the data marked in the spatial design drawings of each area in the intelligent building; Step S200: obtaining a personnel distribution image of each area in the intelligent building, identifying the number of personnel in each area, and calculating the regional congestion degree of each regional node according to the building area connectivity graph; Step S300: Calculate the travel cost of each regional node according to the building area connectivity graph, and analyze the comprehensive travel cost of each regional node to reach the building exit through each path; Step S400: According to the congestion degree of nodes in each area and the comprehensive travel cost to the exit of the intelligent building, the number of people transferred between adjacent areas is determined, and the people in each area of ​​the intelligent building are iteratively guided.

2. A digital supervision method for design data applied to intelligent buildings according to claim 1, characterized in that: The step S100 is divided into the following steps: Step S101: obtaining the design drawings used by the intelligent building, and extracting the information of each area in the building and the information of the connection channels between the areas in the design drawings; Step S102: taking each area as a regional node of the current intelligent building, taking the connecting channels between each area as the connecting lines between the regional nodes of the current intelligent building, and constructing a building area connectivity map; When constructing the building area connectivity map, the area of ​​each area in the area information is used as the corresponding area node weight, and the maximum traffic rate of each inter-area connection channel in the inter-area connection channel information is used as the connection line weight between area nodes.

3. A digital supervision method for design data applied to intelligent buildings according to claim 2, characterized in that: The step S200 includes the following contents: Install image sensors in each area of ​​the intelligent building, obtain the distribution image of people in each area node, count the real-time number of people in each area node, and calculate the regional congestion of each area node; for any area node a, according to the formula: Among them, C a is the regional congestion degree of regional node a, N a is the real-time number of people in regional node a, S a is the weight of regional node a; Set the upper threshold of regional congestion C′ and normalize the regional congestion of each regional node. The normalization formula is as follows: Among them, C′ a is the normalized congestion degree of regional node a; when C′ a >1, C′ a The value is corrected to 1.

4. The method for digital supervision of design data applied to intelligent buildings according to claim 2 is characterized in that: The step S300 includes the following contents: Obtain the plane map of each regional node in the building area connectivity map, measure the travel distance through each regional node according to the orientation of the connecting channel between each regional node and the adjacent regional node, and calculate the comprehensive travel cost of each path from regional node a to the exit of the intelligent building in combination with the weight of the connecting line between the regional nodes; For any path p, according to the formula: Cost(a, p) is the comprehensive cost of regional node a to reach the exit of the intelligent building through path p, i is the number of regional nodes along path p, N p is the number of regional nodes that path p passes through, Cost(i) is the cost of passing regional node i, l i is the travel distance of path p through regional node i, k v is the inter-regional traffic coefficient, v i is the weight of the connection line between regional node i and the next regional node, c1 and c2 are positive constant parameters, C′ i is the normalized congestion degree of regional node i.

5. The method for digital supervision of design data applied to intelligent buildings according to claim 2 is characterized in that: The step S400 is divided into the following steps: Step S401: using a path planning algorithm to analyze the path with the minimum comprehensive travel cost from each regional node to the exit of the intelligent building; Step S402: Traverse forward along each path in sequence from the regional node adjacent to the exit, calculate the crowd transfer weight between adjacent regional nodes in each path and the crowd transfer capacity of each regional node, and determine the number of people transferred between each regional node; Step S403: according to the change in the number of people in each area of ​​the intelligent building, iteratively guide the travel routes of people in each area.

6. A digital supervision method for design data applied to intelligent buildings according to claim 5, characterized in that: The method for calculating the number of people transferred between adjacent regional nodes in each path in step S402 is as follows: Extract the path information with the minimum comprehensive travel cost from all regional nodes to the exit of the intelligent building, and obtain, for any regional node n, screen out all the paths passing through regional node n, and for any screened path, calculate the population transfer weight of the previous adjacent regional node of the current path regional node n to regional node n, according to the formula: Among them, w n-1 is the population transfer weight of the population from the previous adjacent regional node of the current path regional node n to regional node n, n-1 is the previous adjacent regional node of the current path regional node n, Cost(n-1, p n-1 ) is the path p of the regional node n-1 through which the node belongs n-1 The comprehensive cost of reaching the exit of the smart building; Traverse forward along each path from the regional node adjacent to the exit. For any regional node n, screen all paths involving regional node n, and obtain the population transfer weights of all previous adjacent regional nodes of regional node n in the screened path. According to the formula: Perform weighted scaling on the population transfer weights of each node; Get the preset upper limit threshold C' of regional congestion, according to the formula: Calculate the population transfer capacity N′ of regional node n n ; where C′ n is the normalized congestion degree of regional node n, N n is the real-time number of personnel in regional node n; when C′ n >C′, change N′ n Corrected to 0; Then, the population transfer weights of each previous adjacent regional node of regional node n are multiplied by the population transfer capacity of regional node n to obtain the number of people transferred from each previous adjacent regional node to regional node n.

7. The method for digital supervision of design data applied to intelligent buildings according to claim 5 is characterized in that: The method for iteratively guiding the travel routes of people in each area in step S403 is as follows: Set a threshold for the proportion of people transferring, and inversely deduce the threshold for the number of people transferring in each area based on the regional congestion calculation method; When the crowd begins to move, the regional congestion and crowd transfer capacity of each regional node are calculated, the number of people to be transferred between regional nodes is determined, and the crowd close to the inter-regional connection channel is guided to transfer; During the crowd transfer process, if the regional congestion of any regional node reaches the upper threshold of the regional congestion, the regional node is monitored. If the crowd transfer capacity of the regional node is greater than the crowd transfer quantity threshold, it is determined that the regional node can accommodate crowd transfer, and the above method is used to iteratively calculate the number of crowd transfers that can be absorbed by the regional node to guide the crowd; If the population transfer capacity of the area is greater than the number of people that the regional node can absorb from all the previous regional nodes in the path involved, all the people in the previous regional nodes will be transferred.

8. A digital design data supervision system for intelligent buildings using the digital design data supervision method for intelligent buildings according to any one of claims 1 to 7, characterized in that: The system includes: a design data processing unit, a data analysis module, and an intelligent building area supervision module; The design data processing unit is used to collect the design drawings used in the intelligent building, extract the information of each area in the building and the connection channel information between the areas in the design drawings, and construct a building area connectivity map; the data analysis module calculates the regional congestion of each regional node and the travel cost to reach the building exit in real time, and determines the number of people transferring between regional nodes; the intelligent building regional supervision module is used to monitor the distribution of personnel in each regional node in real time, determine whether each regional node can accommodate the transfer of people, and iterate the calculation results according to the number of people transfer that each regional node can absorb, and guide the people in each regional node in the building.

9. A digital design data supervision system for intelligent buildings according to claim 8, characterized in that: The data analysis module includes: a regional congestion calculation unit, a traffic cost analysis unit, and a transfer path planning unit; The regional congestion calculation unit calculates the regional congestion data of each regional node according to the number of people in each area; the traffic cost analysis unit is used to analyze the traffic cost of each regional node in the intelligent building where people transfer; the transfer path planning unit is used to calculate the comprehensive traffic cost of people in each area transferring to the exit of the intelligent building, and plan the path with the minimum comprehensive traffic cost for people transfer in each area.

10. A digital design data supervision system for intelligent buildings according to claim 8, characterized in that: The intelligent building area supervision module includes: an area monitoring unit, a crowd transfer decision unit, and a crowd transfer guidance unit; The regional monitoring unit is used to monitor the distribution of personnel in each area of ​​the intelligent building and identify the number of personnel in each area; the crowd transfer decision unit is used to analyze the crowd transfer weight of each regional node to transfer people to the next regional node along the personnel transfer path, synchronously calculate the crowd transfer capacity in each regional node, determine the number of people transferred in each regional node, and judge whether each regional node can accommodate crowd transfer; when determining that the regional node can accommodate crowd transfer, the crowd transfer guiding unit sends a regional transfer signal to the personnel who are closer to the inter-regional connection channel, and synchronously sends the travel direction information of the target regional node.

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