Digital intelligence-driven existing building reconstruction design multi-dimensional data evaluation optimization method

Abstract

The invention relates to the technical field of building decoration design, in particular to a digital-intelligence-driven existing building reconstruction design multi-dimensional data evaluation optimization method, which comprises the following steps: acquiring multi-source monitoring data of an existing building, and determining a three-dimensional BIM model of the existing building according to the multi-source monitoring data, the multi-source monitoring data comprises structure monitoring data, environment sensing data and space use trajectory data; and according to the space limitation information in the three-dimensional BIM model, determining evaluation coverage areas corresponding to multiple groups of different function partition schemes and transformation strengths under a preset structure safety distance condition. Through the combination of the multi-source monitoring data and the three-dimensional BIM model, the structure, the safety, the environmental comfort and the use frequency of the existing building can be evaluated more accurately, and especially through detailed analysis of the function attenuation coefficient and the structure fluctuation amplitude of each space grid unit, the state change of the building in different time periods is reflected.

Description

Technical Field

[0001] This invention relates to the field of architectural decoration design technology, specifically to a digitally driven multi-dimensional data evaluation and optimization method for the renovation design of existing buildings. Background Technology

[0002] With the advancement of urbanization, more and more existing buildings need to be renovated and upgraded. However, the renovation of existing buildings often faces problems such as improper space utilization, structural safety hazards, and functional mismatch. How to improve the efficiency and effectiveness of renovation through scientific evaluation methods has become an important issue.

[0003] Currently, traditional building renovation often relies on human experience and intuitive judgment, neglecting the complex structure, usage, environmental comfort, and other multi-dimensional factors of the building itself. When renovating existing buildings, it is necessary to consider multiple aspects such as structural safety, functional requirements, and usage efficiency. The complex relationship between these factors often cannot be fully assessed by conventional means alone.

[0004] Furthermore, building renovation involves more than just changes in physical space; it also involves multiple dimensions such as structural safety, environmental comfort, and functional requirements. Traditional building assessment and renovation plans often fail to fully consider all relevant factors, resulting in failure to meet user needs or increased safety hazards. Therefore, there is an urgent need for an optimization method that can integrate multi-dimensional data and comprehensively consider spatial constraints and functional requirements. Summary of the Invention

[0005] To achieve the above objectives, the present invention provides the following technical solution: a multi-dimensional data evaluation and optimization method for the renovation design of existing buildings driven by digital intelligence, comprising: Acquire multi-source monitoring data of existing buildings, and determine a three-dimensional BIM model of the existing buildings based on the multi-source monitoring data, wherein the multi-source monitoring data includes structural monitoring data, environmental sensing data, and spatial usage trajectory data; Based on the spatial constraint information in the 3D BIM model, the assessment coverage areas corresponding to multiple different functional zoning schemes and renovation intensities are determined under the condition of preset structural safety distance; wherein, the spatial constraint information includes the location of load-bearing walls, pipeline distribution paths and evacuation passage ranges; The functional zoning scheme and renovation intensity corresponding to each of the assessment coverage areas are used as target renovation parameters; Based on the target transformation parameters and the three-dimensional BIM model, each of the assessment coverage areas is divided into multiple assessment sub-areas, and the key monitoring indicators corresponding to each assessment sub-area are determined. Obtain feedback information on problems in public spaces. When the feedback information points to any of the evaluation sub-areas, conduct an in-depth evaluation of the evaluation sub-area based on the corresponding key monitoring indicators to obtain a targeted renovation and optimization plan.

[0006] Preferably, determining the 3D BIM model of the existing building based on the multi-source monitoring data includes: The existing building is divided into at least one spatial grid unit of a preset size; Based on the multi-source monitoring data, the structural integrity, environmental comfort, and usage frequency values ​​within each spatial grid unit are calculated. Based on the structural integrity, environmental comfort, and usage frequency values ​​within each spatial grid unit, each spatial grid unit is divided into structurally safe units, environmentally unsuitable units, and inefficiently used units. Spatial correlation modeling is performed on the structural safety unit, environmentally unsuitable unit, and inefficient use unit to obtain the three-dimensional BIM model of the existing building.

[0007] Preferably, the calculation of structural integrity, environmental comfort, and usage frequency values ​​within each spatial grid unit based on the multi-source monitoring data includes: Based on the changes in structural and environmental parameters of each spatial grid cell between adjacent monitoring cycles, determine the functional attenuation coefficient of each spatial grid cell between adjacent monitoring cycles. The period is divided according to the functional attenuation coefficient of each spatial grid unit between all adjacent monitoring periods to obtain the evaluation time sequence corresponding to each spatial grid unit; Based on the structural fluctuation amplitude of each spatial grid unit in its corresponding assessment period sequence, and the functional attenuation coefficient between adjacent monitoring cycles in its corresponding assessment period sequence, the structural integrity value of each spatial grid unit in its corresponding assessment period sequence is determined. Based on the fluctuations in environmental parameters and changes in pedestrian density of each spatial grid unit in each corresponding assessment period sequence, the environmental comfort value and usage frequency value of each spatial grid unit in each corresponding assessment period sequence are determined.

[0008] Preferably, the structural integrity value of each spatial grid unit in each assessment period sequence is determined based on the structural fluctuation amplitude of each spatial grid unit in each corresponding assessment period sequence, and the functional attenuation coefficient between adjacent monitoring cycles in each corresponding assessment period sequence, including: Any spatial grid cell is defined as a marker grid, and any evaluation time period sequence corresponding to the marker grid is defined as a marker time period sequence; A preset number of spatial grid units with the highest correlation to the marked grid structure are selected from the first monitoring period in the marked time period sequence and used as a preset number of reference grids corresponding to the marked grid. Based on the structural fluctuation amplitude of each spatial grid unit in its corresponding evaluation time sequence, the maximum value of the functional attenuation coefficient of each spatial grid unit among all adjacent monitoring cycles in its corresponding evaluation time sequence, and the preset number of reference grids corresponding to each spatial grid unit, the structural integrity value of each spatial grid unit in its corresponding evaluation time sequence is determined.

[0009] Preferably, based on the fluctuations in environmental parameters and changes in pedestrian density of each spatial grid unit in its corresponding assessment time series, the environmental comfort value and usage frequency value of each spatial grid unit in its corresponding assessment time series are determined, including: Identify the target temperature point representing the temperature parameter, the target humidity point representing the humidity parameter, and the target pedestrian flow point representing the peak pedestrian flow for each spatial grid cell in each monitoring cycle. Any spatial grid cell is designated as the marker grid, and any monitoring cycle is designated as the marker cycle; The deviation between the target temperature point corresponding to the marked grid within the marking period and the preset comfortable temperature range is calculated to obtain the temperature deviation coefficient; The deviation between the target humidity point corresponding to the marked grid within the marking period and the preset comfortable humidity range is calculated to obtain the humidity deviation coefficient; The weighted result of the temperature deviation coefficient and the humidity deviation coefficient is determined as the environmental fluctuation factor corresponding to the marked grid within the marking period; The ratio of the cumulative value of the target pedestrian flow points in all monitoring periods of each spatial grid unit to the duration of the time period is used to determine the usage frequency value of each spatial grid unit in its corresponding evaluation time period. Based on the differences between the environmental fluctuation factors of each spatial grid unit in all adjacent monitoring periods in each assessment time sequence, the environmental comfort value of each spatial grid unit in each corresponding assessment time sequence is determined. The environmental comfort value of a spatial grid cell in its corresponding assessment period sequence is calculated based on the changing trend of the environmental fluctuation factor.

[0010] Preferably, based on the spatial constraint information in the 3D BIM model, the assessment coverage areas corresponding to multiple different functional zoning schemes and renovation intensities are determined under the condition of a preset structural safety distance, including: Extract the three-dimensional coordinates of each limiting element in the spatial constraint information, and establish a spatial constraint distribution map based on the three-dimensional coordinates of each limiting element. The limiting elements include load-bearing columns, main water pipelines, and fire lanes. In the spatial restriction distribution map, a restriction safety buffer zone is constructed with each restriction element as the center and according to the preset structural safety distance. Based on the preset maximum modification intensity and preset intensity gradient, multiple candidate modification intensities are generated; Within the restricted safety buffer, determine the feasible range of functional partitions corresponding to each of the candidate modification intensities; Within the feasible range of each functional partition, multiple functional partition schemes are generated according to preset functional compatibility rules, and the evaluation coverage area is determined based on each functional partition scheme and the intensity of modification.

[0011] Preferably, based on the target renovation parameters and the 3D BIM model, the target assessment coverage area is divided into multiple assessment sub-regions, including: Based on the functional zoning scheme and renovation intensity determined by the target renovation parameters, the scope of the renovation impact of the target assessment coverage area is calculated; Within the scope of the renovation impact, based on the spatial morphological characteristics in the three-dimensional BIM model, an effective assessment area that can be independently evaluated is determined, wherein the spatial morphological characteristics include bay size, lighting direction and floor height differences; According to the preset regional functional correlation, the effective evaluation area is divided into multiple evaluation sub-regions.

[0012] Preferably, the key monitoring indicators corresponding to each of the assessment sub-regions are determined, including: Obtain the core functional location of each of the evaluation sub-regions; For each of the aforementioned evaluation sub-regions, an indicator screening framework is constructed based on the core function positioning, and multi-dimensional candidate monitoring indicators are generated within the indicator screening framework. Obtain the historical data correlation and on-site monitoring feasibility of the candidate monitoring indicators; The historical data relevance and on-site monitoring feasibility of each candidate monitoring indicator are weighted and calculated to obtain the corresponding indicator importance score; The candidate monitoring indicator with the highest importance score will be selected as the key monitoring indicator for the corresponding evaluation sub-region.

[0013] Preferably, obtaining feedback information on issues in public spaces includes: Acquire space usage status data collected by IoT terminals and user feedback data. Based on a preset problem classification standard library, the space usage status data and experience feedback data are jointly identified to determine the problem areas with functional defects. Based on the spatial coordinate system of the 3D BIM model, the precise location information of the problem area is determined, and the precise location information and the corresponding functional defect description are used as problem feedback information.

[0014] Preferably, when the problem feedback information points to any of the evaluation sub-regions, an in-depth evaluation of the evaluation sub-region is performed based on the corresponding key monitoring indicators to obtain a targeted improvement and optimization plan, including: When the problem feedback information is located in the structural constraint occlusion area in the 3D BIM model, a local evaluation coordinate system is established with the location of the problem feedback information as the center. In the local evaluation coordinate system, multiple evaluation angles that avoid structural constraints are determined based on the spatial constraint information; Based on the target modification parameters and the evaluation perspective, several supplementary evaluation schemes are obtained; The optimal supplementary evaluation scheme is selected from the supplementary evaluation schemes, which meets the structural safety requirements and can completely cover the problem area. An in-depth evaluation is then conducted based on the optimal supplementary evaluation scheme to obtain a targeted modification and optimization scheme.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention, by combining multi-source monitoring data and 3D BIM models, can more accurately assess the structure, safety, environmental comfort, and usage frequency of existing buildings. In particular, detailed analysis of each spatial grid unit provides a deeper understanding of the building's actual usage, ensuring more realistic and reliable assessment results. Furthermore, by using multi-dimensional data, combined with spatial constraints and functional requirements, multiple sets of different functional zoning schemes and renovation intensities are generated, providing more diverse design options for building renovations. This effectively meets renovation requirements, enhances the building's usability, and reflects the building's state changes over different time periods through the functional attenuation coefficient and structural fluctuation amplitude of each spatial grid unit. The application of this change in renovation design is particularly crucial. Through this time-series assessment method, designers can more accurately predict the building's performance in future periods, enabling more effective adjustments. By combining spatial constraints, this invention can design a renovation plan that best meets usage needs and functional compatibility while ensuring structural safety, avoiding subsequent renovation failures or safety hazards caused by ignoring these constraints. It also uses weighted calculations based on the correlation of historical data and on-site monitoring data, and conducts targeted renovation optimization based on feedback on public space issues. For areas with problems, in-depth evaluation can be conducted to obtain the most suitable solution, thereby optimizing the renovation process and reducing unnecessary duplication of work and waste of resources. This invention, through precise 3D modeling and multi-dimensional spatial assessment, can effectively improve the utilization efficiency of building space. Especially during renovation, it can rationally partition the space based on data such as usage frequency and environmental comfort, avoiding excessive renovation or unnecessary functional waste. Furthermore, when problems are reported, the method can conduct local assessments based on the precise location information of the problem area, combined with information such as the 3D BIM model and structural constraints. By supplementing the assessment plan, it ensures that the renovation and optimization plan not only meets safety requirements but also solves functional defects to the greatest extent. Attached Figure Description

[0016] Figure 1 This is a schematic flowchart of the overall method in one embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1, please refer to Figure 1 This invention provides a technical solution: a multi-dimensional data evaluation and optimization method for the design of existing building renovation driven by digital intelligence, comprising: S1. Obtain multi-source monitoring data of existing buildings and determine the three-dimensional BIM model of existing buildings based on the multi-source monitoring data. The multi-source monitoring data includes structural monitoring data, environmental sensing data and space usage trajectory data. S2. Based on the spatial constraint information in the 3D BIM model, determine the assessment coverage area corresponding to multiple different functional zoning schemes and renovation intensities under the preset structural safety distance conditions; among which, the spatial constraint information includes the location of load-bearing walls, pipeline distribution paths, and evacuation passage ranges; S3. Use the functional zoning plan and renovation intensity corresponding to each assessment coverage area as the target renovation parameters; S4. Based on the target transformation parameters and the 3D BIM model, divide each assessment coverage area into multiple assessment sub-areas and determine the key monitoring indicators corresponding to each assessment sub-area. S5. Obtain feedback information on problems in public spaces. When the feedback information points to any evaluation sub-area, conduct an in-depth evaluation of the evaluation sub-area based on the corresponding key monitoring indicators to obtain a targeted renovation and optimization plan.

[0019] It's important to note that, firstly, multi-source monitoring data of existing buildings should be acquired. This data includes: structural monitoring data: recording the building's structural condition, such as foundation settlement, wall cracks, and beam / column deformation; environmental sensor data: acquiring information on changes in the building's internal and external environment, such as temperature, humidity, air quality, and noise; and space usage trajectory data: recording the usage of the building's internal spaces through smart devices or sensors, such as which areas are frequently used and which are infrequently used. For example, in the renovation of an old office building, sensors can be installed inside to collect real-time data on temperature, humidity, air quality, and personnel flow. This data helps determine which areas have poor air quality or which areas are frequently overcrowded. The design of the renovation plan is influenced by various factors. Based on the existing 3D BIM model, different functional zoning schemes and the assessment coverage area for renovation intensity are determined. The BIM model helps to accurately represent the building's spatial structure and constraints. Spatial constraints to consider include: the location of load-bearing walls (these walls cannot be arbitrarily demolished or altered); pipeline distribution paths (the renovation plan must avoid affecting the layout of water, electricity, and gas pipelines); and the scope of evacuation routes (evacuation routes in the building must be unobstructed and remain unobstructed). For example, in the renovation of an office building, if the original open-plan offices are to be converted into meeting rooms, it is necessary to ensure that load-bearing walls are not damaged and that the layout of electrical and air conditioning pipes within the building is not affected. Furthermore... The renovated space must still ensure unobstructed evacuation routes. After determining multiple functional zoning schemes, their specific schemes and renovation intensity (such as wall demolition, space reinforcement, etc.) are set as target renovation parameters as the basis for subsequent analysis. For example, assuming the goal of the above renovation project is to transform the office area into a multi-functional conference area, the target renovation parameters might include: demolition of conference room walls, structural reinforcement, equipment layout optimization, etc. The evaluation area is subdivided into several smaller sub-areas, and based on the specific conditions of these sub-areas, key monitoring indicators are determined, such as: building stability: changes in wall cracks, foundation settlement, etc.; environmental comfort: temperature, humidity, air quality, etc.; usage frequency: space usage frequency and personnel flow. Dynamic density, etc.; For example, during the functional zoning process, a floor may be divided into several small areas, each focusing on different indicators; for example, one area may focus on temperature, humidity, and air circulation, while another area may focus on the frequency of space use and personnel density; if feedback is received from public spaces, such as poor air quality or excessive noise in a certain area of ​​the building, the system will conduct in-depth evaluation of the specific indicators of the relevant sub-areas based on this feedback information and carry out targeted optimization; For example, suppose that during the use of a renovated meeting room, users report poor air quality in that area, the system will automatically analyze the temperature, humidity, and air circulation data of that area, find that the air circulation is not smooth, and finally propose a renovation and optimization plan to add a ventilation system.

[0020] In an optional embodiment, determining a 3D BIM model of an existing building based on multi-source monitoring data includes: Divide the existing building into at least one spatial grid unit of a preset size; Calculate the structural integrity, environmental comfort, and usage frequency values ​​within each spatial grid unit based on multi-source monitoring data; Based on the structural integrity, environmental comfort, and usage frequency values ​​within each spatial grid unit, each spatial grid unit is divided into structurally safe units, environmentally unsuitable units, and inefficiently used units. Spatial correlation modeling is performed on structural safety units, environmentally unsuitable units, and inefficiently used units to obtain a 3D BIM model of the existing building.

[0021] It's important to note that existing buildings are divided into multiple small grid units. The size of these grid units can be set according to actual needs (e.g., each unit might be 5 square meters, 10 square meters, etc.). These grid units will become the basic units for subsequent analysis and optimization. For example, suppose you have an office building with each floor having an area of ​​1000 square meters. When evaluating it, you can divide the floor into 100 grid units, each with an area of ​​10 square meters. This allows for a more refined analysis of the structure, environment, and usage of the entire floor. After gridding the building, the next step is to collect and calculate the data for each grid unit. The monitoring data is used to classify grid units based on their structural integrity, environmental comfort, and usage frequency. These classifications can be categorized as follows: Structurally safe units: units with intact structures and no safety hazards; Environmentally unsuitable units: units where environmental conditions do not meet comfort requirements (e.g., unsuitable temperature and humidity, poor air quality); Inefficiently used units: units with low usage frequency and inefficient function utilization. For example, in an office building, some grid units on the 20th floor are classified as "Environmentally unsuitable units" due to unsuitable temperature and humidity, while certain areas on the 15th floor, with low usage frequency, can be classified as "Inefficiently used units." This information will serve as the basis for subsequent renovations. The categorized units will be spatially correlated and modeled to further analyze the interrelationships and influences between spaces. This process helps establish a 3D BIM model of the building, which digitally models the building's spatial layout, structural features, environmental parameters, etc., thereby enabling precise renovation analysis. For example, suppose that in the grid units of a floor, some structurally safe units are too close to environmentally unsuitable units, or the number of structurally safe units is relatively dense. Through spatial correlation modeling, the spatial relationships between different units can be clearly displayed, providing a basis for building renovation and functional optimization. The above steps, combined with spatial grid division, structural, environmental, and usage data, ultimately yield a 3D BIM model of the building. This model not only depicts the building's external form but also includes the functional distribution of internal spaces, environmental parameters, and structural integrity. Based on this model, more refined evaluation, optimization, and renovation design schemes can be implemented. For example, after modeling, you can see detailed information about each floor of the entire building in the BIM system: which areas have environmental problems, which areas are underutilized, and which areas have structural integrity. This allows for targeted adjustments to the layout, environmental improvements, or optimized space utilization during renovations.

[0022] In an optional embodiment, calculating the structural integrity, environmental comfort, and usage frequency values ​​within each spatial grid cell based on multi-source monitoring data includes: Based on the changes in structural and environmental parameters of each spatial grid cell between adjacent monitoring cycles, determine the functional attenuation coefficient of each spatial grid cell between adjacent monitoring cycles. The period is divided according to the functional attenuation coefficient of each spatial grid unit between all adjacent monitoring periods to obtain the evaluation time sequence corresponding to each spatial grid unit; Based on the structural fluctuation amplitude of each spatial grid unit in its corresponding assessment period sequence, and the functional attenuation coefficient between adjacent monitoring cycles in its corresponding assessment period sequence, the structural integrity value of each spatial grid unit in its corresponding assessment period sequence is determined. Based on the fluctuations in environmental parameters and changes in pedestrian density of each spatial grid unit in each corresponding assessment period sequence, the environmental comfort value and usage frequency value of each spatial grid unit in each corresponding assessment period sequence are determined.

[0023] It should be noted that the functional degradation coefficient of each grid cell is calculated by monitoring changes in structural and environmental parameters between adjacent monitoring periods. The functional degradation coefficient describes the performance change of a spatial cell, such as the degree of structural deterioration or environmental quality decline. Structural parameter changes may include variations in structural problems such as cracks, deformation, and settlement. Environmental parameter changes include variations in temperature, humidity, air quality, and noise. The functional degradation coefficient is obtained by comparing the changes between adjacent monitoring periods. For example, if the temperature and humidity of a spatial cell fluctuate significantly between two monitoring periods, the functional degradation coefficient for environmental comfort will be higher, indicating a decline in comfort in that area. Example: Suppose the temperature in an office area fluctuates significantly over two months. The temperature fluctuates significantly (from 25°C to 30°C), while the air quality index rises from 60 to 80. These changes will lead to an increase in the environmental function degradation coefficient of the unit, reflecting a decline in the environmental quality of the area. Based on the function degradation coefficient between all adjacent monitoring periods, each spatial grid unit is divided into different assessment time periods. Each assessment time period represents a monitoring period segment, where the change in the function degradation coefficient reflects the structural and environmental status of the area during that period. If the function degradation coefficient is large during a certain period, it indicates that the spatial unit is in poor condition during that period. The assessment time period sequence helps to provide a clear assessment of structural and environmental performance for different time periods. Example: Suppose a region experiences significant temperature fluctuations, possibly from two... If the temperature gradually increases within a month, the assessment time series for that area will reflect a gradual deterioration process. During some periods, the structure may be intact and comfort levels may be good, while in other periods, high temperatures may lead to poor environmental comfort and decreased usage frequency. For each assessment time period, the structural integrity value of each spatial grid unit is determined based on the structural fluctuation amplitude (such as crack changes, settlement changes, etc.) and the functional decay coefficient between adjacent periods. The structural integrity value reflects the structural safety and stability of the spatial unit within that time period. If the structural fluctuation amplitude is large or the functional decay coefficient is high, the structural integrity value will be low, indicating that the structural health of the unit is poor during this period. Example: Suppose that during a monitoring period in a certain area... If cracks enlarge and the functional degradation coefficient is high during the period, the structural integrity value for that period may be low, indicating that the structure in that area may require repair or reinforcement. Based on fluctuations in environmental parameters (such as temperature, humidity, and noise) and changes in pedestrian density, the environmental comfort value and usage frequency value for each spatial grid unit are determined for each assessment period. Environmental comfort value: This can be assessed based on fluctuations in environmental parameters such as temperature, humidity, air quality, and noise. If these parameters exceed the comfortable range, the environmental comfort value will be low. Usage frequency value: This is assessed based on changes in pedestrian density. If an area is frequently used (e.g., with high pedestrian traffic), its usage frequency value is high; if the usage frequency of an area decreases due to environmental issues, the usage frequency value is low.Example: Suppose that employees feel uncomfortable in an office area due to excessively high temperature and low humidity, thus the environmental comfort value of that area is low. Simultaneously, if monitoring data shows that the area is used infrequently (e.g., employees are unwilling to stay in the area for extended periods due to environmental discomfort), then the usage frequency value of that area is also low.

[0024] In an optional embodiment, the structural integrity value of each spatial grid unit in each assessment time sequence is determined based on the structural fluctuation amplitude of each spatial grid unit in each corresponding assessment time sequence and the functional attenuation coefficient between adjacent monitoring periods in each corresponding assessment time sequence, including: Any spatial grid cell is defined as a marker grid, and any evaluation time period sequence corresponding to the marker grid is defined as a marker time period sequence. Within the first monitoring period of the marked time period sequence, a preset number of spatial grid units with the highest correlation to the marked grid structure are selected as the preset number of reference grids corresponding to the marked grid. Based on the structural fluctuation amplitude of each spatial grid unit in its corresponding evaluation time sequence, the maximum value of the functional attenuation coefficient of each spatial grid unit among all adjacent monitoring cycles in its corresponding evaluation time sequence, and the preset number of reference grids corresponding to each spatial grid unit, the structural integrity value of each spatial grid unit in its corresponding evaluation time sequence is determined.

[0025] It should be noted that, from all spatial grid cells, an arbitrary grid cell is selected as the marker grid, which will serve as the core of the analysis. For example, suppose we select a grid cell located in an office on the 3rd floor of a building (e.g., area A) as the marker grid; a specific evaluation time period sequence corresponding to the marker grid is selected as the marker time period sequence; the evaluation time period sequence consists of multiple time periods divided according to the monitoring cycle, where the environmental and structural characteristics of each time period may differ; suppose we select data from the marker grid between the 3rd and 5th monitoring cycles as the marker time period sequence; from the first monitoring cycle in the marker time period sequence, data corresponding to the marker grid are selected. The spatial grid cells with the highest structural correlation are selected as reference grids for the marker grid. The degree of structural correlation can be determined by calculating the similarity between spatial grid cells, possibly using the magnitude of changes in structural parameters (such as cracks, settlement, etc.). For example, suppose that in the first monitoring cycle of the marker grid, some structural changes (such as an increase in crack length) are detected in region A. By comparing the structural changes of adjacent grid cells, it may be found that the structural changes of the grid cells in the 4th and 6th layers have similar trends to those of the marker grid, and these grid cells are selected as reference grids. Assuming that we set the number of reference grids to 3, the 3 corresponding to the marker grids... The reference grid is the three grids whose structural changes are most similar. For each spatial grid cell, its structural integrity value is calculated for each corresponding evaluation period sequence. The following factors need to be considered in the calculation: Structural fluctuation amplitude: the structural changes of each grid cell during the monitoring period; the greater the fluctuation amplitude, the more unstable the structural state of the area, and the lower the integrity value; Maximum functional degradation coefficient: the maximum value of the functional degradation coefficient between all adjacent monitoring periods for each grid cell within its evaluation period; the functional degradation coefficient reflects the degree of deterioration of structural or environmental performance; the larger the maximum value, the more significant the performance degradation; Reference grid: considering the relationship between each grid cell and... The structural correlation between reference grids; that is, the impact of structural changes in the reference grids on the marker grids; reference grids with large structural changes may lead to a decrease in the structural integrity of the marker grids; for example, the structural fluctuation of the marker grid (region A) is 5 mm during a certain evaluation period, and the maximum functional decay coefficient is 0.4 (meaning that the structural condition deteriorates rapidly), and the reference grids of region A (such as the 4th, 6th, and 7th layers) all show similar structural problems (crack changes); by combining these factors, the structural integrity value of region A during this period can be calculated; for example, assuming the calculation result is 70%, it means that the structural integrity of the region is relatively moderate and still needs to be monitored.

[0026] In an optional embodiment, the environmental comfort value and usage frequency value of each spatial grid unit in each corresponding assessment time period sequence are determined based on the fluctuation of environmental parameters and changes in pedestrian density in each spatial grid unit in each corresponding assessment time period sequence, including: Identify the target temperature point representing the temperature parameter, the target humidity point representing the humidity parameter, and the target pedestrian flow point representing the peak pedestrian flow for each spatial grid cell in each monitoring cycle. Any spatial grid cell is designated as the marker grid, and any monitoring cycle is designated as the marker cycle; The deviation between the target temperature point corresponding to the marked grid within the marking period and the preset comfortable temperature range is calculated to obtain the temperature deviation coefficient; The deviation between the target humidity point corresponding to the marked grid within the marking period and the preset comfortable humidity range is calculated to obtain the humidity deviation coefficient; The weighted result of the temperature deviation coefficient and the humidity deviation coefficient is determined as the environmental fluctuation factor corresponding to the marked grid within the marking period; The ratio of the cumulative value of the target pedestrian flow points in all monitoring periods of each spatial grid unit to the duration of the time period is used to determine the usage frequency value of each spatial grid unit in its corresponding evaluation time period. Based on the differences between the environmental fluctuation factors of each spatial grid unit in all adjacent monitoring periods in each assessment time sequence, the environmental comfort value of each spatial grid unit in each corresponding assessment time sequence is determined. The environmental comfort value of a spatial grid cell in its corresponding assessment period sequence is calculated based on the changing trend of the environmental fluctuation factor.

[0027] It should be noted that: Target temperature point: For each spatial grid cell, a target temperature point characterizing the temperature parameter is identified within each monitoring cycle; for example, the temperature could be the average temperature or the highest / lowest temperature of the area. Target humidity point: Similarly, a target humidity point characterizing humidity is identified within each monitoring cycle; this could be the average humidity of the area or the humidity value at a specific time period. Target pedestrian flow point: A target pedestrian flow point is identified within each monitoring cycle; this could be the maximum pedestrian density in the area during a certain time period, typically used to represent the usage frequency of the area. Any monitoring cycle is selected as the marker cycle; within this cycle, all environmental parameters (temperature, humidity, etc.) are... Temperature (degrees of heat, humidity, etc.) will be used to calculate the corresponding deviation coefficients and comfort values; the deviation between the target temperature point and the preset comfort temperature range of the marked grid within the marking period will be calculated; for example, if the target temperature point of the marked grid is 28°C and the comfort temperature range is 22°C to 26°C, then the temperature deviation is |28°C - 26°C| = 2°C; the temperature deviation coefficient is the standardized or weighted result of this deviation value; the deviation between the target humidity point and the preset comfort humidity range of the marked grid within the marking period will be calculated; for example, if the target humidity point is 75% and the comfort humidity range is 40% to 60%, then the humidity deviation is |75% - 60%|=15%; The humidity deviation coefficient is the weighted result of this deviation value; Combining the weighted results of the temperature deviation coefficient and the humidity deviation coefficient, the environmental fluctuation factor of the marked grid within the marking period is obtained; For each spatial grid unit, in each evaluation time period sequence, the ratio of the cumulative value of the target population flow point to the time period duration is calculated to obtain the usage frequency value; For example, if the peak population flow of a spatial grid unit is 1000 people in a certain evaluation time period, and the duration of that time period is 1 hour, then the usage frequency value is 1000 / 1=1000 people / hour; Based on all adjacent monitoring weeks in the corresponding evaluation time period sequence for each spatial grid unit. The environmental comfort value of a grid cell is determined by the differences in environmental fluctuation factors within a given period. The environmental comfort value takes into account the changing trends of the fluctuation factors. If the fluctuation factors of a grid cell change little over multiple monitoring periods, the environmental comfort level of that area is high; conversely, if the fluctuation factors change significantly, the comfort level is low. The changing trends of environmental fluctuation factors within each period are considered comprehensively. For example, if the environmental fluctuation factor of a spatial grid cell remains at a high level (e.g., greater than 0.5) for a period of time and the changes are large, the environmental comfort value of that spatial grid cell is low; if the fluctuation factor is small and stable, the comfort value is high.

[0028] In an optional embodiment, based on spatial constraint information in the 3D BIM model, the assessment coverage areas corresponding to multiple different functional zoning schemes and renovation intensities are determined under preset structural safety distance conditions, including: Extract the three-dimensional coordinates of each limiting element in the spatial constraint information, and establish a spatial constraint distribution map based on the three-dimensional coordinates of each limiting element. The limiting elements include load-bearing columns, main water pipelines and fire lanes. In the spatial constraint distribution map, a constraint safety buffer is constructed with each constraint element as the center and according to the preset structural safety distance; Based on the preset maximum modification intensity and preset intensity gradient, multiple candidate modification intensities are generated; Determine the feasible range of functional partitions corresponding to each candidate modification intensity within the restricted safety buffer; Within the feasible range of each functional zone, multiple functional zone schemes are generated according to preset functional compatibility rules, and the assessment coverage area is determined based on each functional zone scheme and the intensity of the renovation.

[0029] It should be noted that during the architectural design and renovation process, the spatial location information of all limiting elements must first be extracted. These limiting elements include: load-bearing columns: load-bearing columns are key components supporting the building structure, and their three-dimensional coordinates can pinpoint the specific location of each column; the layout of main water pipes is also an important consideration in architectural renovation, as the three-dimensional coordinates of the main water pipes determine their spatial location; fire escape routes: the three-dimensional coordinates of fire escape routes determine the safe passage areas within the building, and they generally cannot be blocked or altered. By obtaining the three-dimensional coordinates of each limiting element, a spatial constraint distribution map can be drawn in three-dimensional space. This distribution map shows the location and distribution of each limiting element; for example, different colors can be used to mark them. The location of load-bearing columns, main water lines, and fire escape routes is indicated, along with their areas of influence. Based on structural safety distances in the building design, a safety buffer zone is constructed around each limiting element. This buffer zone is designed to prevent interference with these critical structural elements during renovations, ensuring the building's structural safety. Structural safety distances typically refer to the minimum inaccessible distance around load-bearing columns, main water lines, and fire escape routes. A restricted safety buffer zone is a safe area defined around these limiting elements, usually extending a certain distance in a circular or polygonal manner. Renovations or construction are not permitted within this buffer zone. For example, a 5-meter safety buffer zone might be set around load-bearing columns, and a 3-meter buffer zone might be set around fire escape routes. Conflict Zone; Based on the building's maximum modification intensity (i.e., allowable modification capacity) and a preset intensity gradient (different areas have different modification intensities), multiple candidate modification intensities are generated; the candidate modification intensities represent different degrees of modification that can be carried out in each area, and these intensities are usually set according to factors such as the structural stability and space usage requirements of the area; the maximum modification intensity refers to the maximum area or maximum load-bearing capacity that can be modified in a certain area; the intensity gradient can be set to multiple different levels of modification intensity, such as light, moderate, and heavy modification areas, or different intensity levels can be set according to the requirements of different building structures; after constructing the restricted safety buffer zone, it is necessary to determine the feasible scope of modification within these areas; each Each candidate modification intensity corresponds to a different functional zone. The feasibility of each functional zone is affected by: limiting factors (such as whether it is within a safety buffer zone) and the intensity of the modification required (i.e., whether it is suitable for a certain type of modification). For example, within the safety buffer zone around a load-bearing column, it is not suitable to make a large number of structural modifications, but it is possible to make minor non-structural modifications, such as the demolition of interior walls or light renovation. Within the feasible range of functional zones, multiple functional zone schemes are generated according to preset functional compatibility rules. Each functional zone scheme involves how to use these feasible areas for a reasonable functional layout. For example, in a certain area of ​​the building, there may be multiple feasible functional zones, such as offices, meeting rooms, and kitchens.The compatibility rules consider the usage requirements, space size, and compatibility with other functional areas for each function; based on each functional zoning scheme and the intensity of the renovation, the final evaluation coverage area is determined; this area represents the specific spatial renovations that can be carried out under a given renovation intensity and functional zoning scheme.

[0030] In an optional embodiment, the target assessment coverage area is divided into multiple assessment sub-regions based on the target modification parameters and the 3D BIM model, including: Based on the functional zoning scheme and renovation intensity determined by the target renovation parameters, calculate the scope of the renovation impact of the target assessment coverage area; Within the scope of the renovation impact, based on the spatial morphological characteristics in the 3D BIM model, determine the effective assessment areas that can be independently evaluated. Among them, the spatial morphological characteristics include bay size, lighting direction and floor height differences. Based on the pre-defined regional functional relationships, the effective assessment area is divided into multiple assessment sub-areas.

[0031] It should be noted that the scope of the renovation impact in the target assessment coverage area is calculated based on the renovation parameters (including functional zoning and renovation intensity) set according to the design objectives. The target assessment coverage area represents the area that can be renovated under a given renovation intensity, and these areas will be affected by the renovation intensity. The functional zoning scheme is the division of space, usually determined according to different functional needs (such as office area, meeting area, rest area, etc.). The renovation intensity of each area may be different. For example, the meeting area may require high-intensity renovation, while the rest area may only require light renovation. Depending on the needs of different areas, the renovation intensity may include structural renovations (such as wall demolition, increasing load, etc.) and non-structural renovations (such as decoration, equipment replacement, etc.). (etc.); Different intensities of renovation will affect the use and layout of space; when calculating the target assessment coverage area, the specific distribution of renovation intensity must be considered; for example, due to structural limitations, some areas of an office building cannot undergo heavy renovation, and can only undergo light renovation; this limitation will affect the calculation of the assessment coverage area; after determining the scope of the renovation impact, the next step is to determine the effective assessment area that can be independently assessed based on the spatial morphological characteristics in the 3D BIM model; BIM (Building Information Modeling) provides a digital 3D model of the building, which can help designers analyze space more accurately; spatial morphological characteristics: when conducting renovation assessment, the physical attributes of the space must be considered, mainly including: bay dimensions: representing the dimensions of rooms or areas in the building. Width typically influences the layout and use of space; for example, a larger bay may be suitable for large conference rooms or exhibition spaces, while a smaller bay is suitable for offices. Lighting direction affects the lighting conditions of a space; a proper lighting direction can make the space more comfortable and improve energy efficiency. Assessing the lighting direction can help designers determine whether window layout needs improvement or additional lighting fixtures need to be added. Ceiling height differences refer to the differences in ceiling height between different areas. Areas with significant ceiling height differences are usually suitable for different types of renovations or functional zoning; for example, higher ceilings are suitable for exhibition spaces or conference rooms, while lower ceilings may be suitable for storage spaces. Based on these spatial characteristics, determine which areas can be evaluated independently; for example, in an office... Within a floor, areas with lower ceilings may not be suitable for open-plan offices, while areas with higher ceilings may be suitable for meeting rooms or multi-functional areas. Finally, the effective assessment area is divided into multiple assessment sub-areas based on the functional relationships between the areas. Functional relationships refer to the relationships between different functional areas during the space renovation process; for example, there may be certain functional connections between office areas, rest areas, and meeting areas, and these connections determine their degree of dependence in spatial layout. Functional relationships take into account the usage needs of different areas; for example, meeting rooms are usually close to office areas and rest areas, while office areas and storage areas may be farther apart. Based on these relationships, the space can be divided into different sub-areas for more detailed assessment and renovation.Each assessment sub-area will have a specific renovation plan developed based on its functional requirements and spatial characteristics; the division of assessment sub-areas helps designers to rationally layout and optimize the space according to actual needs.

[0032] In an optional embodiment, the key monitoring indicators corresponding to each evaluation sub-region are determined, including: Obtain the core functional positioning of each evaluation sub-region; For each evaluation sub-region, an indicator screening framework is constructed based on the core functional positioning, and multi-dimensional candidate monitoring indicators are generated within the indicator screening framework. Obtain historical data correlation and on-site monitoring feasibility for candidate monitoring indicators; The historical data relevance and on-site monitoring feasibility of each candidate monitoring indicator are weighted and calculated to obtain the corresponding indicator importance score; The candidate monitoring indicator with the highest indicator importance score will be selected as the key monitoring indicator for the corresponding evaluation sub-region.

[0033] It's important to note that each evaluation sub-area has a clearly defined core function, which determines the area's purpose and importance. For example, in an office building renovation project: the core function of the office area might be to provide a comfortable working environment and improve employee productivity; the core function of the meeting room is to support various meetings and presentations, ensuring a good audiovisual experience; and the core function of the rest area is to provide relaxation and social space. Based on the core functional positioning of each sub-area, a screening framework is constructed to select relevant monitoring indicators. These indicators can include multiple dimensions, involving aspects such as spatial environment, comfort, and functionality. For example, for the office area, monitoring indicators might focus on the following dimensions: temperature: whether it is within a comfortable working temperature range; lighting: whether there is sufficient natural light or artificial lighting; noise level: whether it is below the noise standard that interferes with employee work. These indicators help quantify the quality of space use and further guide design and renovation. Candidate monitoring indicators need to undergo historical data analysis and on-site feasibility assessment. Here, historical data relevance refers to the degree of correlation between the indicator and the target function in past applications, while on-site monitoring feasibility is considered. The feasibility of monitoring refers to its effectiveness in a real-world environment. Historical data relevance is crucial, for example, analyzing past data to determine the relationship between temperature and employee productivity, or the correlation between light intensity and employee satisfaction. On-site monitoring feasibility is also important, such as whether suitable sensors can be installed on-site to monitor factors like temperature, noise, and light in real time. For each candidate indicator, a weighted calculation is performed based on its historical data relevance and on-site monitoring feasibility. This weighting process typically considers two aspects: historical data relevance (indicators with high relevance, such as the high correlation between light intensity and productivity) and on-site monitoring feasibility (indicators that are easy to monitor and technically feasible, such as temperature monitoring via thermometers and hygrometers). After weighted calculation, a comprehensive score is obtained to measure the importance of each monitoring indicator in practical applications. Based on the weighted indicator importance score, the candidate monitoring indicator with the highest score is identified as the key monitoring indicator for the corresponding sub-area. These indicators will be used as key monitoring targets for real-time data collection and analysis to optimize the functionality and performance of the area.

[0034] In an optional embodiment, obtaining feedback information on problems in public spaces includes: Acquire space usage status data collected by IoT terminals and user feedback data. Based on a pre-defined problem classification standard library, the space usage status data and experience feedback data are jointly identified to determine the problem areas with functional defects. Based on the spatial coordinate system of the 3D BIM model, the precise location information of the problem area is determined, and the precise location information and the corresponding functional defect description are used as problem feedback information.

[0035] It's important to note that real-time data on space usage, such as temperature, humidity, light intensity, and air quality, is collected via Internet of Things (IoT) terminals. Additionally, users provide personal feedback, potentially addressing issues related to comfort, noise levels, and air circulation. This combination provides comprehensive information on space usage and experience. A pre-defined standard library categorizes space usage data and feedback data, including common spatial problems and their corresponding classifications. For example, excessively high or low temperatures might be categorized as "comfort issues," excessive noise as "environmental disturbance issues," and insufficient lighting as "work efficiency issues." The purpose of this data-driven identification is to quickly identify functional defects in specific areas through intelligent analysis. A 3D BIM model provides a three-dimensional coordinate system for the building space, allowing for precise location of problem areas. For instance, when an issue of excessively high temperature in an office area is identified, the specific location of the problem can be pinpointed in the BIM model, such as near the left wall of an office. The BIM model's coordinate system ensures highly accurate problem location.

[0036] In an optional embodiment, when the problem feedback information points to any evaluation sub-region, an in-depth evaluation of the evaluation sub-region is performed based on the corresponding key monitoring indicators to obtain a targeted improvement and optimization plan, including: When the problem feedback information is located in the structural constraint occlusion area in the 3D BIM model, a local evaluation coordinate system is established with the location of the problem feedback information as the center. In the local evaluation coordinate system, multiple evaluation angles that avoid structural constraints are determined based on spatial constraint information; Based on the target modification parameters and evaluation perspectives, several supplementary evaluation schemes were obtained; The optimal supplementary assessment scheme is selected from the supplementary assessment schemes, which meets the structural safety requirements and can fully cover the problem area. An in-depth assessment is then conducted based on the optimal supplementary assessment scheme to obtain a targeted modification and optimization scheme.

[0037] It should be noted that combining the precise location information of the problem area with the corresponding functional defect description (such as "excessive temperature") forms detailed problem feedback information. This feedback information will be used for subsequent evaluation and modification decisions. If the problem feedback points to a specific evaluation sub-area, an in-depth evaluation will be conducted based on the core functional positioning and monitoring indicators of that area. For example, if the problem occurs in a meeting room and the feedback is "excessive noise," noise control may be selected as a key monitoring indicator for in-depth evaluation. If the problem is located in a structurally constrained area in the 3D BIM model (such as walls or other building structures), limitations on monitoring angles or equipment installation will be encountered. In this case, a local evaluation coordinate system needs to be established around the problem area, that is, the coordinate system is redefined in the space around the problem point to avoid structural obstacles. Based on the structural constraints of the space, multiple methods to avoid these constraints are designed. The assessment process involves several angles to ensure a comprehensive evaluation of the problem area. For example, monitoring equipment may need to be installed from multiple directions to obtain complete data. Based on spatial constraints and target modification parameters (such as noise control equipment and temperature control systems), multiple feasible assessment plans are generated. Each plan may differ, for example, by adjusting air conditioning, adding sound insulation, or changing the spatial layout. From these supplementary plans, a plan that meets structural safety requirements and fully covers the problem area is selected. This means that the selected plan must not only solve the problem but also ensure that the modification does not affect the safety of the building structure. Finally, based on the optimal supplementary assessment plan, an in-depth assessment of the problem area is conducted to derive a specific modification and optimization plan. This may include changes to the spatial structure, the addition or adjustment of equipment, or other plans to improve the functionality of the space and the user experience.

[0038] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.

Claims

1. A multi-dimensional data evaluation and optimization method for the renovation design of existing buildings driven by digital intelligence, characterized in that, include: Acquire multi-source monitoring data of existing buildings, and determine a three-dimensional BIM model of the existing buildings based on the multi-source monitoring data, wherein the multi-source monitoring data includes structural monitoring data, environmental sensing data, and spatial usage trajectory data; Based on the spatial constraint information in the 3D BIM model, the assessment coverage areas corresponding to multiple different functional zoning schemes and renovation intensities are determined under the condition of preset structural safety distance; wherein, the spatial constraint information includes the location of load-bearing walls, pipeline distribution paths and evacuation passage ranges; The functional zoning scheme and renovation intensity corresponding to each of the assessment coverage areas are used as target renovation parameters; Based on the target transformation parameters and the three-dimensional BIM model, each of the assessment coverage areas is divided into multiple assessment sub-areas, and the key monitoring indicators corresponding to each assessment sub-area are determined. Obtain feedback information on problems in public spaces. When the feedback information points to any of the evaluation sub-areas, conduct an in-depth evaluation of the evaluation sub-area based on the corresponding key monitoring indicators to obtain a targeted renovation and optimization plan.

2. The method for multi-dimensional data evaluation and optimization of existing building renovation design driven by digital intelligence as described in claim 1, characterized in that, The existing building's 3D BIM model is determined based on the multi-source monitoring data, including: The existing building is divided into at least one spatial grid unit of a preset size; The structural integrity, environmental comfort, and usage frequency values ​​within each spatial grid unit are calculated based on the multi-source monitoring data. Based on the structural integrity, environmental comfort, and usage frequency values ​​within each spatial grid unit, each spatial grid unit is divided into structurally safe units, environmentally unsuitable units, and inefficiently used units. Spatial correlation modeling is performed on the structural safety unit, environmentally unsuitable unit, and inefficient use unit to obtain the three-dimensional BIM model of the existing building.

3. The method for multi-dimensional data evaluation and optimization of existing building renovation design driven by digital intelligence as described in claim 2, characterized in that, Based on the multi-source monitoring data, the structural integrity, environmental comfort, and usage frequency values ​​within each spatial grid cell are calculated, including: Based on the changes in structural and environmental parameters of each spatial grid cell between adjacent monitoring cycles, determine the functional attenuation coefficient of each spatial grid cell between adjacent monitoring cycles. The period is divided according to the functional attenuation coefficient of each spatial grid unit between all adjacent monitoring periods to obtain the evaluation time sequence corresponding to each spatial grid unit; Based on the structural fluctuation amplitude of each spatial grid unit in its corresponding assessment period sequence, and the functional attenuation coefficient between adjacent monitoring cycles in its corresponding assessment period sequence, the structural integrity value of each spatial grid unit in its corresponding assessment period sequence is determined. Based on the fluctuations in environmental parameters and changes in pedestrian density of each spatial grid unit in each corresponding assessment period sequence, the environmental comfort value and usage frequency value of each spatial grid unit in each corresponding assessment period sequence are determined.

4. The method for multi-dimensional data evaluation and optimization of existing building renovation design driven by digital intelligence as described in claim 3, characterized in that, Based on the structural fluctuation amplitude of each spatial grid unit in its corresponding assessment time series, and the functional attenuation coefficient between adjacent monitoring periods in its corresponding assessment time series, the structural integrity value of each spatial grid unit in its corresponding assessment time series is determined, including: Any spatial grid cell is defined as a marker grid, and any evaluation time period sequence corresponding to the marker grid is defined as a marker time period sequence; A preset number of spatial grid units with the highest correlation to the marked grid structure are selected from the first monitoring period in the marked time period sequence and used as a preset number of reference grids corresponding to the marked grid. Based on the structural fluctuation amplitude of each spatial grid unit in its corresponding evaluation time sequence, the maximum value of the functional attenuation coefficient of each spatial grid unit among all adjacent monitoring cycles in its corresponding evaluation time sequence, and the preset number of reference grids corresponding to each spatial grid unit, the structural integrity value of each spatial grid unit in its corresponding evaluation time sequence is determined.

5. The method for multi-dimensional data evaluation and optimization of existing building renovation design driven by digital intelligence as described in claim 4, characterized in that, Based on the fluctuations in environmental parameters and changes in pedestrian density of each spatial grid unit in its corresponding assessment time series, the environmental comfort value and usage frequency value of each spatial grid unit in its corresponding assessment time series are determined, including: Identify the target temperature point representing the temperature parameter, the target humidity point representing the humidity parameter, and the target pedestrian flow point representing the peak pedestrian flow for each spatial grid cell in each monitoring cycle. Any spatial grid cell is designated as the marker grid, and any monitoring cycle is designated as the marker cycle; The deviation between the target temperature point corresponding to the marked grid within the marking period and the preset comfortable temperature range is calculated to obtain the temperature deviation coefficient; The deviation between the target humidity point corresponding to the marked grid within the marking period and the preset comfortable humidity range is calculated to obtain the humidity deviation coefficient; The weighted result of the temperature deviation coefficient and the humidity deviation coefficient is determined as the environmental fluctuation factor corresponding to the marked grid within the marking period; The ratio of the cumulative value of the target pedestrian flow points in all monitoring periods of each spatial grid unit to the duration of the time period is used to determine the usage frequency value of each spatial grid unit in its corresponding evaluation time period. Based on the differences between the environmental fluctuation factors of each spatial grid unit in all adjacent monitoring periods in each assessment time sequence, the environmental comfort value of each spatial grid unit in each corresponding assessment time sequence is determined. The environmental comfort value of a spatial grid cell in its corresponding assessment period sequence is calculated based on the changing trend of the environmental fluctuation factor.

6. The method for multi-dimensional data evaluation and optimization of existing building renovation design driven by digital intelligence as described in claim 5, characterized in that, Based on the spatial constraint information in the 3D BIM model, the assessment coverage areas corresponding to multiple different functional zoning schemes and renovation intensities are determined under the preset structural safety distance conditions, including: Extract the three-dimensional coordinates of each limiting element in the spatial constraint information, and establish a spatial constraint distribution map based on the three-dimensional coordinates of each limiting element. The limiting elements include load-bearing columns, main water pipelines, and fire lanes. In the spatial restriction distribution map, a restriction safety buffer zone is constructed with each restriction element as the center and according to the preset structural safety distance. Based on the preset maximum modification intensity and preset intensity gradient, multiple candidate modification intensities are generated; Within the restricted safety buffer, determine the feasible range of functional partitions corresponding to each of the candidate modification intensities; Within the feasible range of each functional partition, multiple functional partition schemes are generated according to preset functional compatibility rules, and the evaluation coverage area is determined based on each functional partition scheme and the intensity of modification.

7. The method for multi-dimensional data evaluation and optimization of existing building renovation design driven by digital intelligence as described in claim 6, characterized in that, Based on the target renovation parameters and the 3D BIM model, the target assessment coverage area is divided into multiple assessment sub-regions, including: Based on the functional zoning scheme and renovation intensity determined by the target renovation parameters, the scope of the renovation impact of the target assessment coverage area is calculated; Within the scope of the renovation impact, based on the spatial morphological characteristics in the three-dimensional BIM model, an effective assessment area that can be independently evaluated is determined, wherein the spatial morphological characteristics include bay size, lighting direction and floor height differences; According to the preset regional functional correlation, the effective evaluation area is divided into multiple evaluation sub-regions.

8. The method for multi-dimensional data evaluation and optimization of existing building renovation design driven by digital intelligence as described in claim 7, characterized in that, The key monitoring indicators for each of the aforementioned assessment sub-regions were determined, including: Obtain the core functional location of each of the evaluation sub-regions; For each of the aforementioned evaluation sub-regions, an indicator screening framework is constructed based on the core function positioning, and multi-dimensional candidate monitoring indicators are generated within the indicator screening framework. Obtain the historical data correlation and on-site monitoring feasibility of the candidate monitoring indicators; The historical data relevance and on-site monitoring feasibility of each candidate monitoring indicator are weighted and calculated to obtain the corresponding indicator importance score; The candidate monitoring indicator with the highest importance score will be selected as the key monitoring indicator for the corresponding evaluation sub-region.

9. The method for multi-dimensional data evaluation and optimization of existing building renovation design driven by digital intelligence as described in claim 8, characterized in that, Obtain feedback information on issues related to public spaces, including: Acquire space usage status data collected by IoT terminals and user feedback data. Based on a preset problem classification standard library, the space usage status data and experience feedback data are jointly identified to determine the problem areas with functional defects. Based on the spatial coordinate system of the 3D BIM model, the precise location information of the problem area is determined, and the precise location information and the corresponding functional defect description are used as problem feedback information.

10. The method for multi-dimensional data evaluation and optimization of existing building renovation design driven by digital intelligence as described in claim 9, characterized in that, When the feedback information points to any of the evaluation sub-regions, an in-depth evaluation of the evaluation sub-region is conducted based on the corresponding key monitoring indicators to obtain a targeted improvement and optimization plan, including: When the problem feedback information is located in the structural constraint occlusion area in the 3D BIM model, a local evaluation coordinate system is established with the location of the problem feedback information as the center. In the local evaluation coordinate system, multiple evaluation angles that avoid structural constraints are determined based on the spatial constraint information; Based on the target modification parameters and the evaluation perspective, several supplementary evaluation schemes are obtained; The optimal supplementary evaluation scheme is selected from the supplementary evaluation schemes, which meets the structural safety requirements and can completely cover the problem area. An in-depth evaluation is then conducted based on the optimal supplementary evaluation scheme to obtain a targeted modification and optimization scheme.

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