Office building design method and system based on big data collection

Abstract

The application discloses an office building design method and system based on big data collection, relates to the technical field of building informatization and intelligent design, and comprises the following steps: S100, a test pulse is emitted point by point in a building corridor area, positioning signals and reflected echo data are collected, a reflected response sequence corresponding to a point is formed, and a reflected suspicious fragment list is constructed according to a response amplitude and a time delay difference; S200, static marker points are arranged in the area corresponding to the reflected suspicious fragment list, a picture sequence without personnel movement is continuously recorded, and a stable and unchanged static anchor point list is extracted and used as a baseline for subsequent personnel positioning track authenticity comparison. The application realizes whole-process suppression of pseudo displacement signals, accurately strips non-real personnel tracks, avoids space design and energy consumption decision deviation caused by misjudgment, improves the scientificity and efficiency of building design, and is suitable for positioning data cleaning and optimization in various complex indoor environments.

Description

Technical Field

[0001] This invention relates to the field of building information technology and intelligent design, specifically to a method and system for office building design based on big data collection. Background Technology

[0002] Office building design based on big data collection refers to a design method that comprehensively utilizes multi-source data collection, data analysis, 3D modeling, and intelligent optimization during the planning and design process of office buildings to conduct scientific and quantitative research on building functional layout, space utilization, energy consumption distribution, and personnel behavior patterns. This method continuously collects data related to office buildings, such as environmental parameters, energy consumption indicators, personnel activity trajectories, lighting utilization rates, and air quality, through sensor networks, IoT platforms, building management systems, and external databases. This data is then cleaned, classified, and feature extracted on a big data platform. Based on this analyzed multi-dimensional data, combined with the spatial structure expression obtained from 3D modeling, designers can accurately grasp the real needs and operational patterns of office buildings at different stages of use, thereby achieving dynamic optimization of spatial layout, lighting and ventilation, equipment configuration, and energy-saving strategies during the design phase. Compared to traditional experience-based design methods, this data-driven approach makes the decision-making process for building schemes more objective, quantifiable, and verifiable, significantly improving the scientific rigor, comfort, and sustainability of the design, and realizing the transformation of office building design from experience-based design to data-intelligent design.

[0003] Existing technologies have the following shortcomings: In current technologies, office building design typically relies on personnel location data based on wireless positioning, Bluetooth beacons, or infrared sensors to statistically analyze space usage frequency and personnel flow. However, in complex building environments, positioning signals are easily interfered with by metal components, glass curtain walls, and reflective surfaces, creating a multipath propagation effect. This causes the system to mistakenly identify false displacements caused by signal reflections as real personnel movement trajectories. These pseudo-displacement trajectories are statistically classified as high-frequency flow paths during big data aggregation and analysis, leading to the design-stage algorithm model misjudging the area as a high-traffic area, resulting in unnecessary expansions of corridor widths, air conditioning vents, and ventilation duct layouts. This causes a severe imbalance in spatial resource allocation, low actual utilization rates, and abnormal energy distribution within the building, undermining the rationality of spatial planning and increasing energy consumption burden and maintenance costs during later operation.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide an office building design method and system based on big data collection, so as to solve the problems in the background art mentioned above.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an office building design method based on big data collection, comprising the following steps: S100 transmits test pulses point by point in the building corridor area, collects positioning signals and reflected echo data, forms a reflection response sequence for the corresponding point, and constructs a list of suspected reflection segments based on the difference in response amplitude and time delay. S200: Set up stationary markers in the area corresponding to the list of suspected reflection fragments, continuously record the sequence of images without personnel movement, and extract a stable and unchanging list of stationary anchor points from them, which will be used as the baseline for subsequent comparison of the authenticity of personnel positioning trajectories. S300 performs time-segmented analysis on the collected personnel positioning trajectories, identifies abrupt trajectory segments that are inconsistent with the anchor point positions based on the static anchor point column, and merges all abrupt trajectory segments to form a pseudo displacement pulse band. S400, along the path corresponding to the pseudo-displacement pulse zone, sequentially inspects the building environment, and sets up temporary extinction plates in the high reflection direction of each path segment. By recording the changes in reflection intensity, a reflection source pointing map is drawn. The S500, based on the reflection source pointing pattern, drives the coordinated operation of the time-slot alternating polarization antenna and the directional absorbing curtain. It dynamically adjusts the antenna polarization angle and the position of the absorbing curtain according to the reflection direction, so that the reflected signal cancels out in time and space, and constructs a dynamic interference closed loop to suppress pseudo displacement signals.

[0007] Preferably, step S100 includes: Test locations were set up at equal intervals in the corridor area of ​​the office building. Each location emitted a pulse signal with a clear structure and stable frequency in sequence, and the positioning signal and reflected echo data were collected to form a reflection response sequence. Extract the time delay point where the energy peak is located from the reflection response sequence at each location point, calculate the delay difference relative to the direct wave, and determine the reflector properties by combining the signal amplitude. For data regions with similar delay differences and high-amplitude reflection peaks in continuous test points, coordinate positioning and numbering are performed, and a priority classification of reflection interference is established. In the numbered areas, the original signal data is traced back, and the echo difference between the strong reflection area and the non-reflection area is compared. Based on the reflection characteristics, a list of suspected reflection segments is constructed, including the point number, the range of delay difference, the percentage of peak reflection intensity, the interference priority, and the range of location coordinates.

[0008] Preferably, when constructing the list of suspected reflection fragments, the high-amplitude reflected waves appearing in the delay interval after the main peak signal are used as the judgment criterion by comparing the echo data of strong reflection areas and non-reflection areas, and the interference priority classification criteria are based on the decrease in reflection peak intensity and the stability of delay difference distribution, thereby ensuring the accuracy of reflection source location and the reliability of list data.

[0009] Preferably, step S200 includes: In the suspected reflection area identified by the reflection response data, stationary markers are set up at equal intervals. Each marker is equipped with a fixed high-definition camera and the imaging angle is calibrated by a level. A continuous video shooting task is initiated at a stationary marker point to capture a sequence of images with no personnel moving, and the shadow lines of wall corners, the intersections of floor tile seams, and the edge lines of fixed light fixtures are identified in the images as spatial feature points; The identified image feature points are converted into corresponding actual spatial coordinates through linear mapping, and the anchor point sequence is selected based on the frequency of occurrence and positional stability. The anchor point sequence extracted from all stationary markers is connected in physical order to form a stationary anchor point column, and the spatial distance between each anchor point is recorded to construct a trajectory comparison baseline.

[0010] Preferably, each anchor point in the static anchor point column is obtained by dual determination of the contour boundary change rate and gray-level gradient change rate in consecutive image frames. The contour position offset does not exceed the pixel-level error range, the gray-level gradient change rate is lower than the set threshold, and the spatial coordinate accuracy of each anchor point is maintained within the centimeter range to ensure the stability and repeatability of the trajectory comparison baseline.

[0011] Preferably, step S300 includes: The personnel trajectory data collected in office buildings is processed by time segmentation, and the location points are extracted in each time segment and the trajectory path is constructed based on the continuity of the points; Based on the comparison of trajectory paths with static anchor points, identify abrupt trajectory segments that jump across multiple sets of anchor points without passing through intermediate transition anchor points at fixed time intervals. Spatial consistency verification is performed on the jump trajectory segment. The spatial distance between the trajectory sampling point and the adjacent anchor point is calculated, and the start and end times, start coordinates, end coordinates and number of trajectory points are recorded. The time-continuous and direction-consistent abrupt trajectory segments are sequentially merged into extended abnormal trajectory segments, and then integrated into pseudo-displacement pulse bands based on path direction, time continuity, and spatial overlap.

[0012] Preferably, during the identification of abrupt trajectory segments, when the spatial deviation between the trajectory sampling point and the stationary anchor point column remains constant within a continuous time period and the deviation distance exceeds a preset threshold, it is determined to be an abnormal trajectory, and the trajectory is included in the formation range of the pseudo-displacement pulse band for subsequent reflection source localization and path intervention analysis.

[0013] Preferably, step S400 includes: Based on the spatial coordinate sequence of the pseudo-displacement pulse band, the path is reconstructed segment by segment on the building plan, and each segment is numbered according to its length. Measurement reference points are set up at the center point of each test segment and positioning pulse signals are emitted. Conduct inspections in the high-reflection direction corresponding to the measurement benchmark point to identify areas with metal components, glass curtain walls, mirrored decorative materials, or reflective stone, and attach temporary matting sheets to the high-reflection surfaces. After attaching the extinction film, repeat the signal emission test, record the main peak intensity and waveform attenuation changes of the reflected signal, and form an extinction data set for each test segment; A reflection direction vector is constructed based on the line connecting the center point of the test section and the reflection source. The direction angle, material type of the reflection source, distance length, and signal attenuation rate are marked on the building floor plan to form a reflection pointing diagram.

[0014] Preferably, step S500 includes: Based on the reflection source pointing map, the direction angle of the reflection vector, the distance to the reflection source, the reflection intensity attenuation information and the building material properties are extracted, and a transmitting device with adjustable polarization direction is deployed at the center of each test segment; An absorption device made of flexible absorbing material is set up in the reflection direction corresponding to the transmitting device, and its position is finely adjusted according to the deviation angle and distance of the reflection source position to cooperate with the transmitting device to complete spatial intervention. The energy of the reflected signal after each round of polarization angle adjustment and absorption device movement is compared, and the main peak intensity and tail wave intensity are recorded to evaluate the phase cancellation effect. The polarization angles and absorption device location data that effectively attenuate reflection interference in all test segments are summarized to form a dynamic intervention strategy for pseudo-displacement pulse bands and to establish a dynamic matching table for synchronous control of reflection direction and time.

[0015] The office building design system based on big data collection includes a reflection detection module, a stationary anchor point extraction module, a trajectory anomaly identification module, a reflection source localization module, and an electromagnetic interference control module. The reflection detection module emits test pulses point by point in the building corridor area, collects positioning signals and reflection echo data, forms a reflection response sequence for the corresponding point, and constructs a list of suspected reflection fragments based on the difference in response amplitude and time delay. The stationary anchor point extraction module sets up stationary markers in the area corresponding to the list of suspected reflection fragments, continuously records the sequence of images without personnel movement, and extracts a stable and unchanging column of stationary anchor points from them, which is used as the baseline for subsequent comparison of the authenticity of personnel positioning trajectories. The trajectory anomaly identification module analyzes the collected personnel positioning trajectory in different time periods, identifies abrupt trajectory segments that are inconsistent with the anchor point position based on the static anchor point column, and merges all abrupt trajectory segments to form a pseudo displacement pulse band. The reflection source positioning module sequentially inspects the building environment along the path corresponding to the pseudo-displacement pulse band, and sets up temporary extinction plates in the high reflection direction of each path segment. It draws a reflection source pointing map by recording the changes in reflection intensity. The electromagnetic interference control module, based on the reflection source pointing diagram, drives the coordinated operation of the time-slot alternating polarization antenna and the directional absorbing curtain. It dynamically adjusts the antenna polarization angle and the position of the absorbing curtain according to the reflection direction, so that the reflected signal cancels out in time and space, and constructs a dynamic interference closed loop to suppress pseudo displacement signals.

[0016] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention achieves end-to-end control of pseudo-displacement signals, from perception to source suppression, through reflection response acquisition, static anchor point comparison, sudden jump trajectory identification, reflection direction mapping, and coordinated control of the polarization antenna and absorption device. Its significant advantages include: effectively separating non-real personnel movement trajectories within buildings, preventing erroneous judgments regarding spatial layout, passageways, equipment placement, and energy consumption strategies due to pseudo-displacement aggregation during big data analysis, fundamentally avoiding design misguidance and resource waste. Furthermore, this method features high accuracy, strong adaptability, and dynamic adjustment, making it suitable for location data cleaning and design assistance in various high-density office buildings, intelligent buildings, and complex indoor environments, providing reliable support for data-driven building design. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0018] Figure 1 This is a flowchart of the office building design method based on big data collection according to the present invention.

[0019] Figure 2 This is a schematic diagram of the modules of the office building design system based on big data collection according to the present invention. Detailed Implementation

[0020] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0021] This invention provides, for example Figure 1 The office building design method based on big data collection shown includes the following steps: S100 transmits test pulses point by point in the building corridor area, collects positioning signals and reflected echo data, forms a reflection response sequence for the corresponding point, and constructs a list of suspected reflection segments based on the difference in response amplitude and time delay. In the corridor areas of office buildings, to accurately identify reflection interference in positioning signals and provide a foundation for subsequent trajectory data screening and suppression, it is necessary to first actively collect and finely model positioning signal and reflection echo data point by point in the physical space. Through the analysis of signal response characteristics, a complete list of suspected reflection segments is constructed. The specific implementation method is as follows: In the corridor area of ​​the office building, test points were set up at equal intervals of one meter. At each point, a set of clearly structured and frequency-stable pulse signals was sequentially transmitted. These pulse signals used an RF signal with a center frequency of 2.4 GHz, a pulse width of 1 microsecond, and a transmit power of 20 dBm. After each signal transmission, a dedicated receiving device was used to synchronously receive the return signal and record the original time-domain waveform. This waveform contained a mixed response of various propagation paths, including direct waves, single-reflection waves, and multiple-reflection waves. At least 10 rounds of signal transmission and reception were performed at each point to ensure sufficient stability and statistical reliability of the echo data. All waveform data were then uniformly converted into a time delay distribution map. By observing high-amplitude echo signals with delays between 50 and 500 nanoseconds, non-direct reflective response components could be identified.

[0022] Based on the signal response sequence recorded at each location point, the time delay points of the main energy peaks are extracted, and the corresponding delay difference relative to the direct wave is calculated. For example, at a certain location point, the direct wave signal delay is 30 nanoseconds, and the second peak appears at 115 nanoseconds, with a delay difference of 85 nanoseconds. This difference is marked as a physical response indicator of a possible mid-to-long-distance reflecting surface. Combined with signal strength analysis, if the amplitude of the second peak exceeds 20% of the amplitude of the first main wave, it is determined that the reflecting surface area is large or the reflecting material is highly reflective metal or glass. When multiple test points show similar delay differences and strong reflection peaks consecutively, it is preliminarily determined that there may be structural reflection sources in the area, such as metal door frames, glass walls, or aluminum panels in air conditioning ceilings. Based on this, the area is recorded as a high-risk segment for reflection interference.

[0023] The above areas are numbered segment by segment, and each suspected reflection area is located according to its start and end coordinates. For example, the starting point is 3 meters from the entrance of the corridor, and the ending point is 7.5 meters. Intervention priorities for reflection interference are established within the numbered areas, categorized based on the dispersion of the delay difference distribution and the trend of peak intensity variation. If the reflection peak position of a segment is stable and the intensity is consistent, it indicates that the reflection source is fixed and the direction is clear, and the priority is set to high. If multiple sets of reflection peak positions change significantly and the shape jumps frequently, it indicates the existence of multipath superposition effects or irregular reflector surfaces, and the priority is set to medium. If the response fluctuates greatly but does not form continuous high-amplitude peaks, the priority is set to low. All numbered reflection interference areas are archived according to high, medium, and low priorities, and a coordinate index table for the three categories of suspected reflection segments is established.

[0024] Based on the location and classification of suspected reflection areas, the original data of test pulses at each point were reviewed, and representative areas were selected for error amplification analysis. Specifically, within the 12-meter-long experimental section of the corridor, the 3rd to 6th meters were selected as strong reflection areas, and the echo data differences between this area and adjacent non-reflection areas were compared. For example, in the non-reflection section, there was no obvious secondary peak within 90 nanoseconds after the main peak signal delay, while in the strong reflection section, the peak rebound appeared 20 nanoseconds after the main peak, and this rebound lasted until 70 nanoseconds, with an amplitude of more than 45% of the main peak, showing significant reflection characteristics. Based on this difference, a complete list of suspected reflection segments was constructed for the entire corridor space. Each item in the list includes five key parameters: point number, time delay difference range, percentage of reflection peak intensity, interference priority, and location coordinate range, providing basic data support for subsequent static anchor point screening and abnormal trajectory analysis.

[0025] S200: Set up stationary markers in the area corresponding to the list of suspected reflection fragments, continuously record the sequence of images without personnel movement, and extract a stable and unchanging list of stationary anchor points from them, which will be used as the baseline for subsequent comparison of the authenticity of personnel positioning trajectories. Based on the identified physical area containing the suspected reflection fragment, to obtain stable spatial reference points in the real static scene, stationary markers need to be deployed in the corresponding area and observed for a long period of time. Anchor point sequences with fixed spatial positions and stable images are extracted from these markers and used as the benchmark for subsequent comparison of the positioning trajectory data. The specific implementation method is as follows: Within the suspected reflection area identified by the reflection response data, observation points were selected based on spatial geometric characteristics. Each observation point should be located in an unobstructed, uniformly lit area within the corridor, where there is low frequency of daily pedestrian traffic, to avoid unnecessary interference during data collection. Following the principle of placing one point every 2 meters, a total of 6 observation points were established within a 12-meter-long corridor, with an interval error of no more than ±5 centimeters between each point. A laser rangefinder was used to measure the linear distance between each point and the starting point of the corridor, and the precise value was recorded. All distance information was retained to one decimal place as the basis for converting image coordinates to physical coordinates. A fixed high-definition camera was installed above each marker point at a height of 2.5 meters, with a 45-degree downward tilt angle and a lens focal length of 4 millimeters, providing a complete field of view covering a 2-meter-long and 1.5-meter-wide ground area. During installation, a level was used to calibrate the camera's orientation to ensure consistent imaging angles.

[0026] The video recording task was initiated at the observation point. The recording period was 48 consecutive hours, covering two full workdays and one weekend. The frame rate was set to 10 frames per second, and the resolution was 1920×1080 pixels. The video files were stored in hourly segments. During the recording process, no personnel were allowed to move within the recording area to ensure that the scene composition in the image remained completely static. After the video data was recorded, images were extracted frame by frame and time-axis aligned. During image analysis, the shadow lines of wall corners, the intersections of floor tile seams, and the edges of fixed light fixtures in consecutive image frames were selected as target recognition areas for edge detection and contour recognition. If, in 1000 consecutive frames, the contour boundary position of a certain image area changed by no more than 2 pixels, and the boundary grayscale gradient change rate was less than 0.5%, the image of that area was considered stable and met the static observation conditions. Each observation point needed to identify at least two spatial feature points in the video data that were fixed in position, had clear boundaries, and whose contours did not show significant shifts. Taking a certain marker point as an example, the intersection of the cross joint of the floor tiles, the intersection of the wall socket frame and the skirting board are selected in the image. They appear 726 times, 742 times and 753 times respectively in a 48-hour video sequence, and the maximum positional deviation is less than 1.8 pixels. Therefore, it is determined to be a stable static feature point.

[0027] The identified static feature points in the image are mapped to their actual spatial coordinates. The pixel coordinates of each feature point in the image frame should be converted to measured coordinates through linear mapping. During the conversion, a proportional mapping relationship is constructed based on the camera installation height, lens tilt angle, and field of view parameters. The position of a point in the image located at row 320 and column 540 is converted to a position on the corridor floor 1.2 meters directly below the camera and offset to the right by 0.9 meters. After the conversion, the positions of the static feature points extracted from all 6 observation points are recorded in the global spatial coordinate system with centimeter-level accuracy. For example, the first anchor point of marker point 3 is located 7.2 meters from the starting point of the corridor and offset to the right by 0.85 meters. The three anchor points with the highest recurrence frequency and the best positional stability are selected from each observation point to form the anchor point sequence for that point. All anchor points must meet the following conditions: the number of successful image recognitions within 48 hours is no less than 700, the maximum pixel position offset is less than 2 pixels, and the error of repeated calculation of the corresponding spatial coordinates does not exceed 2 centimeters.

[0028] The anchor point sequence extracted from the six observation points is numbered using the format A1-1, A1-2, A1-3 to A6-3, representing the anchor point at a specific location. These anchor points are arranged in physical spatial order to form a static anchor point column, and the spatial distance between any two adjacent anchor points is recorded. For example, the distance between A1-1 and A1-2 is 62 cm, and the distance between A1-2 and A1-3 is 59 cm. All distance information is retained to the millimeter level and used as a threshold benchmark in subsequent trajectory analysis. All anchor point columns are connected to form a continuous trajectory baseline, and its coverage area in the entire corridor is marked, forming a static reference skeleton for areas suspected of reflection. This static reference skeleton will be used as a comparison reference in subsequent trajectory data authenticity analysis. If the personnel positioning trajectory deviates significantly from the skeleton position at a certain time period, or if the trajectory crosses multiple anchor points but lacks continuity, it can be preliminarily determined that the trajectory contains non-real jump segments and is included in the warning range for false displacement identification.

[0029] S300 performs time-segmented analysis on the collected personnel positioning trajectories, identifies abrupt trajectory segments that are inconsistent with the anchor point positions based on the static anchor point column, and merges all abrupt trajectory segments to form a pseudo displacement pulse band. To identify non-realistic movement trajectories in the positioning data of office buildings, based on the obtained static anchor point sequence, the entire personnel trajectory data should be processed by time segmentation. Combined with anchor point location information, all jump trajectory segments inconsistent with the anchor point sequence should be gradually analyzed and systematically integrated into a continuous pseudo-displacement pulse band. Specific implementation method: The collected personnel trajectory data within the office building were standardized. All trajectory data were represented using two-dimensional plane coordinates and matched with the collection timestamp of each location point. The trajectory data was divided into fixed-length time periods, each lasting 60 seconds, with no overlap between periods. Taking a data collection period of 4 hours as an example, the data was divided into 240 consecutive time periods. Within each time period, all location points were extracted, and trajectory paths were constructed based on the continuity of the points. By analyzing the spatial jump amplitude between points, changes in movement direction, and the spatial areas traversed by the path, abnormal fluctuations in the trajectory were identified. If a trajectory segment instantly jumps from one set of anchor points in a static anchor point column to another set of anchor points in a very short time, without passing through the transition area anchor points between the two sets, the trajectory segment is considered to have a sudden jump phenomenon. For example, during the time period from 1320 to 1380 seconds, a trajectory jumps abruptly from anchor point A2-1, which is 4.2 meters away from the entrance, to anchor point A5-3, which is 9.1 meters away from the entrance. The actual measured distance between the two points is 4.9 meters. This trajectory only contains two anchor points and no other points appear in between. Furthermore, no rapid crossing behavior is observed by the personnel in the corresponding video footage during this time period. Therefore, this segment is marked as a jump trajectory.

[0030] Further spatial consistency verification is performed on each jump trajectory segment. Using all anchor points within the corresponding time period as references, the spatial distance from each sampling point in the jump trajectory to adjacent anchor points is calculated, with the error unit measured in centimeters. If a trajectory sampling point is more than 30 centimeters away from an anchor point its theoretical path should pass through, and three consecutive sampling points are not within 3 meters of any anchor point, then the trajectory is considered to have a significant spatial offset. For example, the jump trajectory numbered TJS-07 contains 7 sampling points, all distributed outside the A3 anchor point column, and the nearest point is 84 centimeters from A3-2, far exceeding the error threshold for normal human walking trajectories. Therefore, this trajectory can be confirmed as a spatially structurally abnormal jump. After each jump trajectory segment is verified, it is marked as an abnormal segment, and parameters such as start and end times, start coordinates, end coordinates, number of trajectory points, and maximum jump amplitude are recorded to construct a structured abnormal trajectory information unit.

[0031] All abrupt trajectory segments marked as abnormal are organized chronologically to construct a continuously identifiable abnormal trajectory path. If two abrupt trajectory segments are less than 120 seconds apart in time, and their start and end coordinates are located on the same side boundary within the coverage area of ​​the stationary anchor point column, and the directional angle between the two trajectories is less than 15 degrees, then the two trajectories are merged into a single continuous extended abnormal trajectory segment. For example, the interval between abrupt trajectories TJS-08 and TJS-09 is 95 seconds, both their start and end points are located on the north boundary of the corridor, and their directional angle deviation is 12.7 degrees, satisfying the merging condition. Therefore, they are merged to generate the extended trajectory segment EXTJ-02. After forming the extended trajectory segment, its total length, total number of trajectory points, start and end time range, and spatial span are calculated, and its directional axis is marked. For example, EXTJ-02 has a total length of 6.3 meters, 18 trajectory points, a coverage time from 10:12 AM to 10:36 AM, a starting point 3.4 meters from the corridor entrance, an ending point 9.7 meters from the entrance, and the entire path extends along the north wall.

[0032] All extended trajectory segments are integrated into pseudo-displacement pulse zones according to path direction, temporal continuity, and spatial overlap, and each pulse zone is numbered. Each pseudo-displacement pulse zone must include seven parameters: starting point coordinates, ending point coordinates, coverage time period, number of jump segments, average path offset angle, total path length, displacement direction relative to the stationary anchor point column, and spatial overlap. On the two-dimensional architectural plan, the pseudo-displacement pulse zones are marked as broken lines with high-contrast colors to facilitate subsequent manual verification and correspondence with reflection sources. Taking pseudo-displacement pulse zone PVPB-05 as an example, its path starts at the 2.8-meter position of the corridor and ends at the 9.3-meter position, with a total path length of 6.5 meters. It contains 13 jump segments, spans from 9:18 AM to 9:47 AM, has an average path offset angle of 10.1 degrees, overlaps with the stationary anchor point column A1 to A6, and the entire path trajectory is distributed within a range of 50 centimeters to 1.2 meters to the right of the anchor point column. Once generated, this pseudo-displacement pulse band will serve as the initial spatial basis for determining the interference path of the reflection source, providing precise reference coordinates for the next stage of high-reflection direction positioning and intervention deployment.

[0033] S400, along the path corresponding to the pseudo-displacement pulse zone, sequentially inspects the building environment, and sets up temporary extinction plates in the high reflection direction of each path segment. By recording the changes in reflection intensity, a reflection source pointing map is drawn. After identifying and labeling the pseudo-displacement pulse bands, to further confirm the location of the spatial reflection source causing the abnormal trajectory, a segmented inspection of the area along the line within the building should be conducted based on the pulse band's direction. The reflection attenuation response should be tested through local intervention to create a precise radiation pattern of the reflection source. The specific implementation method is as follows: Based on the spatial coordinate sequence of the pseudo-displacement pulse band, its path was reconstructed segment by segment on the building floor plan. Each segment was numbered according to a length not exceeding 2 meters, with the numbering order consistent with the personnel movement trajectory to ensure the correlation between intervention testing and trajectory changes. Taking a pseudo-displacement pulse band with a total length of 7.6 meters as an example, the path was divided into four test segments, numbered PVPB-03-S1 to PVPB-03-S4. A measurement reference point was set at the center of each test segment. The reference point positioning method used laser ranging combined with ground reflective markers, with ranging accuracy controlled within 1 cm. Each reference point was set as a transmission test point, transmitting a continuous positioning pulse signal at a frequency of 2.4 GHz with a pulse interval of 200 milliseconds. Each transmission segment lasted 5 minutes. The receiving end was set 1.5 meters away from the reference point, at a 90-degree angle to the corridor direction. The intensity curve of the received signal was initially measured, and the direction of strongest signal was used as the predicted high reflection direction.

[0034] At the measurement reference point of each test section, a field inspection was conducted along the predicted high-reflection direction to observe whether there were any architectural elements with high reflective properties, such as large-area metal components, glass curtain walls, mirrored decorative materials, or reflective stone. Taking test section PVPB-03-S2 as an example, its high-reflection direction pointed to the north wall of the corridor. The inspection revealed a 1.8-meter-long stainless steel locker with a mirrored stainless steel surface. Its surface was highly flat and located 2.3 meters from the test point, meeting the characteristics of a reflection source. After confirmation, a temporary matting sheet measuring 50 cm by 50 cm was affixed to the metal surface. The matting sheet was made of dark gray anti-reflective resin fiber with a surface roughness controlled at 80 micrometers, possessing high scattering and low reflection performance. After affixing the sheet, the signal transmission test in the first step was repeated, and new reflection response data were collected under the same test conditions.

[0035] By comparing the received signal intensity curves before and after the temporary extinction sheet was applied, the decrease in peak reflection intensity and the overall waveform attenuation characteristics were calculated. If the decrease in the main peak intensity of the reflected signal within the coverage area of ​​the extinction sheet exceeded 20%, and a significant energy reduction appeared at the tail of the subsequent waveform, then the extinction location was confirmed to have a primary reflection contribution. The high-reflection directions of each test segment were then located and extincted in the same manner, forming a test data set of multiple extinction points. Taking the PVPB-03 path as an example, three significant reflective surfaces were located in the four test segments: the storage cabinet on the north wall, the glass partition on the west side, and the ceiling reflector. After application at each location, the average attenuation of the reflected signal was between 22% and 37%, forming a relatively stable reflection intervention response curve.

[0036] The direction of the maximum change in reflected signal in each test segment is comprehensively compared with the actual distribution of building materials. Based on the line connecting the center point of each test segment to the main reflection source, a set of reflection direction vectors is constructed. All vectors are marked on the building plan to form a continuous reflection pointing map. Each vector contains five pieces of information: starting point coordinates, direction angle, reflection source material type, distance length, and signal attenuation rate. Taking PVPB-03 as an example, its reflection pointing map contains 6 vectors with an average direction angle of 48 degrees, an average reflection source distance of 2.1 meters, and the main reflecting materials are stainless steel and tempered glass, with reflection energy attenuation rates all exceeding 25%. The final generated reflection source pointing map is used to guide subsequent electromagnetic intervention operations and serves as a visual data basis for pseudo-displacement root cause analysis.

[0037] The S500 is based on the coordinated operation of a time-slot rotating polarization antenna and a directional absorbing curtain driven by a reflection source pointing pattern. It dynamically adjusts the antenna polarization angle and the position of the absorbing curtain according to the reflection direction, so that the reflected signal cancels out in time and space, and constructs a dynamic interference closed loop to suppress pseudo displacement signals. After calibrating the main reflection path in space using the reflection source pointing map, a signal intervention device with directional control capability is needed to dynamically electromagnetically intervene in the identified reflection path. This cancels the reflected signals in both time and space, thus suppressing the formation of spurious displacement signals. The specific implementation method is as follows: Based on the completed reflection source pointing map, the spatial parameters of each reflection vector are extracted, including direction angle, distance to the reflection source, reflection intensity attenuation information, and building material properties, and these parameters are mapped one-to-one with the center point of each test segment. A set of polarization-adjustable transmitting devices is deployed at the center point of each test segment. This device consists of a rotation control mechanism and a polarization signal source, and its core task is to emit pulse signals with different polarization directions in different time intervals. In practice, the transmitting device is installed at a height of 2.2 meters, and the polarization control unit can mechanically rotate in 10-degree increments between 0 and 180 degrees, with each rotation cycle lasting 500 milliseconds. Each round of signal transmission lasts for 3 seconds, the signal frequency is 2.4 GHz, and the power is controlled at 18 dB / mW to ensure sufficient signal strength without interfering with actual wireless communication equipment. Taking the test section S2 of PVPB-03 as an example, its reflection direction angle is 45 degrees. The initial polarization direction of the transmitting device is set to 135 degrees, which is perpendicular to it. After entering the rotation, the polarization direction is gradually adjusted to 120 degrees, 105 degrees, 90 degrees, etc., to cover the small deviations in the physical structure of the reflective surface.

[0038] A movable absorbing device is installed in the direction corresponding to the reflection of the transmitting device. This device is made of flexible absorbing material and works by converting reflected energy into heat energy through directional arrangement, thereby reducing the intensity of the reflected wave. The absorbing device is supported by two sets of guide rails and can move horizontally along the wall, with a maximum movement distance of 2 meters and a minimum movement step of 5 centimeters. In each test segment, the initial position of the absorbing device is set to the area directly opposite the reflection source, and its position is finely adjusted sequentially according to the deviation angle and distance of the reflection source pointing to the position of the reflection source in the diagram. For example, in test segment S2, the reflection source is a metal storage cabinet, 2.3 meters away from the test point, and its direction deviates from the center line by 20 degrees. Therefore, the initial placement angle of the absorbing device is 20 degrees, and its position is set at 2.3 meters from the test point. During each antenna rotation cycle, the absorbing device adjusts its position accordingly, making fine adjustments of 5 to 10 centimeters each time, and staying at each position for no less than 5 seconds to ensure that it cooperates with the transmitting device to complete periodic spatial intervention.

[0039] The working cycle of each transmitting and absorbing device is monitored in real time, and the changes in the reflected signal are recorded. The phase cancellation effect is evaluated by energy comparison. During the test, a receiving device is placed at the center point of the test section to receive the intensity of the reflected signal and record the complete waveform structure. After each round of polarization angle adjustment and absorption device movement, the intensity of the main peak and the intensity of the wake wave under that combination are recorded. If a combination has a main peak attenuation of more than 30%, a wake wave decrease of more than 20%, and a waveform stability duration of more than 10 seconds, it is considered that the intervention has achieved effective phase cancellation. Multiple rounds of rotation and coordination adjustments are continued to gradually find the angle and position combination that achieves the maximum reflection attenuation effect. Taking PVPB-03-S2 as an example, when the polarization angle is set to 125 degrees and the absorption device position is set to 2.1 meters from the test point and offset from the wall by 15 degrees, the intensity of the main peak of the received reflected signal decreases by 34% compared to the uninterrupted state, and the wake wave energy decreases by 28%, providing the optimal intervention combination for this reflection path.

[0040] The polarization angles and absorption device position data that effectively attenuate reflection interference in all test segments are summarized to form a dynamic intervention strategy for specific pseudo-displacement pulse bands. In this strategy, each pair of angle and position combinations is defined as an intervention parameter unit and bound to the corresponding test segment number, forming a dynamic matching table for synchronous control of reflection direction and time. All parameter units are executed sequentially and repeated periodically, with each round of intervention lasting no less than 30 minutes. This control process triggers the transmission of signals and the rotation of absorption devices through manually set time segments, causing the reflected signals on the entire pseudo-displacement path to undergo phase cancellation effects at different time points through spatial misalignment and polarization shift, thereby eliminating the root cause of reflection interference before the actual personnel trajectory appears. After completing the above operations, the personnel trajectory data collected on the pseudo-displacement pulse band is retested to verify the trajectory continuity and the disappearance of abrupt jumps. Taking the PVPB-03 path as an example, within 48 hours after the intervention was initiated, the areas in the trajectory data that previously showed an average of more than 6 abrupt jump segments per hour all disappeared, the trajectory changes were highly consistent with the actual stationary anchor point column, the intervention effect was clear, and the dynamic interference closed loop was completed.

[0041] This invention achieves end-to-end control of pseudo-displacement signals, from perception to source suppression, through reflection response acquisition, static anchor point comparison, sudden jump trajectory identification, reflection direction mapping, and coordinated control of the polarization antenna and absorption device. Its significant advantages include: effectively separating non-real personnel movement trajectories within buildings, preventing erroneous judgments regarding spatial layout, passageways, equipment placement, and energy consumption strategies due to pseudo-displacement aggregation during big data analysis, fundamentally avoiding design misguidance and resource waste. Furthermore, this method features high accuracy, strong adaptability, and dynamic adjustment, making it suitable for location data cleaning and design assistance in various high-density office buildings, intelligent buildings, and complex indoor environments, providing reliable support for data-driven building design.

[0042] This invention provides, for example Figure 2 The office building design system based on big data collection shown includes a reflection detection module, a stationary anchor point extraction module, a trajectory anomaly identification module, a reflection source localization module, and an electromagnetic interference control module. The reflection detection module emits test pulses point by point in the building corridor area, collects positioning signals and reflection echo data, forms a reflection response sequence for the corresponding point, and constructs a list of suspected reflection fragments based on the difference in response amplitude and time delay. The stationary anchor point extraction module sets up stationary markers in the area corresponding to the list of suspected reflection fragments, continuously records the sequence of images without personnel movement, and extracts a stable and unchanging column of stationary anchor points from them, which is used as the baseline for subsequent comparison of the authenticity of personnel positioning trajectories. The trajectory anomaly identification module analyzes the collected personnel positioning trajectory in different time periods, identifies abrupt trajectory segments that are inconsistent with the anchor point position based on the static anchor point column, and merges all abrupt trajectory segments to form a pseudo displacement pulse band. The reflection source positioning module sequentially inspects the building environment along the path corresponding to the pseudo-displacement pulse band, and sets up temporary extinction plates in the high reflection direction of each path segment. It draws a reflection source pointing map by recording the changes in reflection intensity. The electromagnetic interference control module, based on the reflection source pointing diagram, drives the coordinated operation of the time-slot alternating polarization antenna and the directional absorbing curtain. It dynamically adjusts the antenna polarization angle and the position of the absorbing curtain according to the reflection direction, so that the reflected signal cancels out in time and space, and constructs a dynamic interference closed loop to suppress pseudo displacement signals.

[0043] The office building design method based on big data collection provided in this embodiment of the invention is implemented through the above-mentioned office building design system based on big data collection. For details of the specific methods and processes of the office building design system based on big data collection, please refer to the embodiments of the office building design method based on big data collection described above, which will not be repeated here.

[0044] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. An office building design method based on big data collection, characterized in that, Includes the following steps: S100 transmits test pulses point by point in the building corridor area, collects positioning signals and reflected echo data, forms a reflection response sequence for the corresponding point, and constructs a list of suspected reflection segments based on the difference in response amplitude and time delay. S200: Set up stationary markers in the area corresponding to the list of suspected reflection fragments, continuously record the sequence of images without personnel movement, and extract a stable and unchanging list of stationary anchor points from them, which will be used as the baseline for subsequent comparison of the authenticity of personnel positioning trajectories. S300 performs time-segmented analysis on the collected personnel positioning trajectories, identifies abrupt trajectory segments that are inconsistent with the anchor point positions based on the static anchor point column, and merges all abrupt trajectory segments to form a pseudo displacement pulse band. S400, along the path corresponding to the pseudo-displacement pulse zone, sequentially inspects the building environment, and sets up temporary extinction plates in the high reflection direction of each path segment. By recording the changes in reflection intensity, a reflection source pointing map is drawn. The S500, based on the reflection source pointing pattern, drives the coordinated operation of the time-slot alternating polarization antenna and the directional absorbing curtain. It dynamically adjusts the antenna polarization angle and the position of the absorbing curtain according to the reflection direction, so that the reflected signal cancels out in time and space, and constructs a dynamic interference closed loop to suppress pseudo displacement signals.

2. The office building design method based on big data collection according to claim 1, characterized in that, Step S100 includes: Test locations were set up at equal intervals in the corridor area of ​​the office building. Each location emitted a pulse signal with a clear structure and stable frequency in sequence, and the positioning signal and reflected echo data were collected to form a reflection response sequence. Extract the time delay point where the energy peak is located from the reflection response sequence at each location point, calculate the delay difference relative to the direct wave, and determine the reflector properties by combining the signal amplitude. For data regions with similar delay differences and high-amplitude reflection peaks in continuous test points, coordinate positioning and numbering are performed, and a priority classification of reflection interference is established. In the numbered areas, the original signal data is traced back, and the echo difference between the strong reflection area and the non-reflection area is compared. Based on the reflection characteristics, a list of suspected reflection segments is constructed.

3. The office building design method based on big data collection according to claim 2, characterized in that, When constructing the list of suspected reflection fragments, the echo data of strong reflection areas and non-reflection areas are compared. The high-amplitude reflected waves that appear in the delay interval after the main peak signal are used as the judgment criteria. The decrease in reflection peak intensity and the stability of delay difference distribution are used as the criteria for interference priority classification, thereby ensuring the accuracy of reflection source location and the reliability of list data.

4. The office building design method based on big data collection according to claim 2, characterized in that, Step S200 includes: In the suspected reflection area identified by the reflection response data, stationary markers are set up at equal intervals. Each marker is equipped with a fixed high-definition camera and the imaging angle is calibrated by a level. A continuous video shooting task is initiated at a stationary marker point to capture a sequence of images with no personnel moving, and the shadow lines of wall corners, the intersections of floor tile seams, and the edge lines of fixed light fixtures are identified in the images as spatial feature points; The identified image feature points are converted into corresponding actual spatial coordinates through linear mapping, and the anchor point sequence is selected based on the frequency of occurrence and positional stability. The anchor point sequence extracted from all stationary markers is connected in physical order to form a stationary anchor point column, and the spatial distance between each anchor point is recorded to construct a trajectory comparison baseline.

5. The office building design method based on big data collection according to claim 4, characterized in that, Each anchor point in the static anchor point column is obtained by dual determination of the contour boundary change rate and gray-level gradient change rate in consecutive image frames. The contour position offset does not exceed the pixel-level error range, the gray-level gradient change rate is lower than the set threshold, and the spatial coordinate accuracy of each anchor point is kept within the centimeter range to ensure the stability and repeatability of the trajectory comparison baseline.

6. The office building design method based on big data collection according to claim 4, characterized in that, Step S300 includes: The personnel trajectory data collected in office buildings is processed by time segmentation, and the location points are extracted in each time segment and the trajectory path is constructed based on the continuity of the points; Based on the comparison of trajectory paths with static anchor points, identify abrupt trajectory segments that jump across multiple sets of anchor points without passing through intermediate transition anchor points at fixed time intervals. Spatial consistency verification is performed on the jump trajectory segment. The spatial distance between the trajectory sampling point and the adjacent anchor point is calculated, and the start and end times, start coordinates, end coordinates and number of trajectory points are recorded. The time-continuous and direction-consistent abrupt trajectory segments are sequentially merged into extended abnormal trajectory segments, and then integrated into pseudo-displacement pulse bands based on path direction, time continuity, and spatial overlap.

7. The office building design method based on big data collection according to claim 6, characterized in that, During the identification of sudden jump trajectory segments, if the spatial deviation between the trajectory sampling point and the stationary anchor point column remains constant within a continuous time period and the deviation distance exceeds a preset threshold, it is determined to be an abnormal trajectory. This trajectory is then included in the formation range of the pseudo-displacement pulse band for subsequent reflection source localization and path intervention analysis.

8. The office building design method based on big data collection according to claim 6, characterized in that, Step S400 includes: Based on the spatial coordinate sequence of the pseudo-displacement pulse band, the path is reconstructed segment by segment on the building plan, and each segment is numbered according to its length. Measurement reference points are set up at the center point of each test segment and positioning pulse signals are emitted. Conduct inspections in the high-reflection direction corresponding to the measurement benchmark point to identify areas with metal components, glass curtain walls, mirrored decorative materials, or reflective stone, and attach temporary matting sheets to the high-reflection surfaces. After attaching the extinction film, repeat the signal emission test, record the main peak intensity and waveform attenuation changes of the reflected signal, and form an extinction data set for each test segment; A reflection direction vector is constructed based on the line connecting the center point of the test section and the reflection source. The direction angle, material type of the reflection source, distance length, and signal attenuation rate are marked on the building floor plan to form a reflection pointing diagram.

9. The office building design method based on big data collection according to claim 8, characterized in that, Step S500 includes: Based on the reflection source pointing map, the direction angle of the reflection vector, the distance to the reflection source, the reflection intensity attenuation information and the building material properties are extracted, and a transmitting device with adjustable polarization direction is deployed at the center of each test segment; An absorption device made of flexible absorbing material is set up in the reflection direction corresponding to the transmitting device, and its position is finely adjusted according to the deviation angle and distance of the reflection source position to cooperate with the transmitting device to complete spatial intervention. The energy of the reflected signal after each round of polarization angle adjustment and absorption device movement is compared, and the main peak intensity and tail wave intensity are recorded to evaluate the phase cancellation effect. The polarization angles and absorption device location data that effectively attenuate reflection interference in all test segments are summarized to form a dynamic intervention strategy for pseudo-displacement pulse bands and to establish a dynamic matching table for synchronous control of reflection direction and time.

10. An office building design system based on big data collection, used to implement the office building design method based on big data collection as described in any one of claims 1-9, characterized in that, It includes a reflection detection module, a stationary anchor point extraction module, a trajectory anomaly identification module, a reflection source localization module, and an electromagnetic interference control module. The reflection detection module emits test pulses point by point in the building corridor area, collects positioning signals and reflection echo data, forms a reflection response sequence for the corresponding point, and constructs a list of suspected reflection fragments based on the difference in response amplitude and time delay. The stationary anchor point extraction module sets up stationary markers in the area corresponding to the list of suspected reflection fragments, continuously records the sequence of images without personnel movement, and extracts a stable and unchanging column of stationary anchor points from them, which is used as the baseline for subsequent comparison of the authenticity of personnel positioning trajectories. The trajectory anomaly identification module analyzes the collected personnel positioning trajectory in different time periods, identifies abrupt trajectory segments that are inconsistent with the anchor point position based on the static anchor point column, and merges all abrupt trajectory segments to form a pseudo displacement pulse band. The reflection source positioning module sequentially inspects the building environment along the path corresponding to the pseudo-displacement pulse band, and sets up temporary extinction plates in the high reflection direction of each path segment. It draws a reflection source pointing map by recording the changes in reflection intensity. The electromagnetic interference control module, based on the reflection source pointing diagram, drives the coordinated operation of the time-slot alternating polarization antenna and the directional absorbing curtain. It dynamically adjusts the antenna polarization angle and the position of the absorbing curtain according to the reflection direction, so that the reflected signal cancels out in time and space, and constructs a dynamic interference closed loop to suppress pseudo displacement signals.

Images