Indoor wireless signal control method

Abstract

The embodiment of the invention discloses an indoor wireless signal control method, which comprises the following steps that: a system firstly calculates a signal coverage range according to information such as an installation position, transmitting power and a frequency parameter of a wireless signal transmitter; shadow effect areas are screened out according to the signal coverage range, and the areas are defined as target weak signal areas needing to be optimized. And the system adjusts the orientation of the camera, acquires an image covering the weak signal area and the surrounding environment thereof, and generates target image data. The system combines the coordinate position of the wireless signal transmitter and the position of the target weak signal area, and analyzes and extracts obstacle features causing signal attenuation from the target image. The system calculates the optimal reflection path of the signal which can efficiently reach the target weak signal area through reflection according to the obstacle characteristics and the camera position. And the system adjusts the transmitting angle of the wireless signal transmitter according to the optimal reflection path obtained by calculation, so that the signal is transmitted along the optimal path, and the communication quality of the area is improved.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to an indoor wireless signal control method. Background Art

[0002] In large shopping malls or supermarkets, due to their large area, when using wireless signals for communication, the propagation of signals will be affected by obstacles, resulting in large changes in signal strength, causing signal strength attenuation and obstruction, and thus leading to the generation of shadow effects.

[0003] The shadow effect is caused by obstacles (such as buildings, walls, and metal objects) that attenuate radio waves. When wireless signals encounter these obstacles during propagation, the signal strength is weakened by reflection, refraction, and scattering, forming an irregular shadow area.

[0004] The shadow effect can cause signal attenuation and irregular distribution, resulting in insufficient signal strength in some areas of the communication network, causing degraded communication quality or intermittent connections, affecting the signal in some areas and making it inconvenient for mobile devices to use.

[0005] The existing approach is to install a relay device at a corner, pointing it toward the shadowed area. The relay device then receives the wireless signal from the transmitter and retransmits it toward the shadowed area, effectively covering the shadowed area. This approach requires not only relay devices but also precise control over the angle at which they are installed. If the angle is not achieved, signal transmission will be weakened. Summary of the Invention

[0006] Based on this, it is necessary to propose an indoor wireless signal control method to address the above problems.

[0007] Provided is an indoor wireless signal control method, the indoor wireless signal control method comprising: Calculate the signal coverage of the wireless signal transmitter based on the installation location, transmission power and frequency data of the wireless signal transmitter; Obtaining shadow effect area location information based on the signal coverage range, and generating a target weak signal area; Acquire an image of a target camera near the target weak signal area to generate a target image; Screening obstacle features from the target image based on the location coordinates of the wireless signal transmitter and the target weak signal area; Calculating an optimal path for signal reflection based on the obstacle characteristics, the target camera, and the position coordinates of the wireless signal transmitter; The transmission angle of the wireless signal transmitter is adjusted according to the optimal path.

[0008] In at least one embodiment of the present application, the specific steps of calculating the signal coverage range of the wireless signal transmitter based on the installation location, transmission power, and frequency data of the wireless signal transmitter, obtaining the shadow effect area location information based on the signal coverage range, and generating the target weak signal area include: Acquire location information of the wireless signal transmitter to obtain first location information; Calculating the signal strength of the wireless signal transmitter based on the first location information and the signal frequency of the wireless signal transmitter to obtain signal strength data; Calculating the signal coverage range according to the signal strength data; Obtaining a weak signal strength threshold, comparing the signal strength data with the weak signal strength threshold, and if the signal strength is less than the weak signal strength threshold, marking the location of the shadow effect area within the signal coverage range; The position information of the shadow effect area is obtained to generate the target weak signal area.

[0009] In at least one embodiment of the present application, the specific steps of acquiring an image of a target camera near the target weak signal area and generating the target image include: Calculating a first direction based on the first position information and the target weak signal area; Adjusting a target camera near the target weak signal area according to the first direction; The target camera generates the target image based on the image captured in the first direction.

[0010] In at least one embodiment of the present application, the specific steps of screening obstacle features from the target image based on the position coordinates of the wireless signal transmitter and the target weak signal area, and calculating the optimal path for signal reflection based on the obstacle features, the target camera, and the position coordinates of the wireless signal transmitter include: Filtering the obstacle features from the target image according to the first direction using an edge detection algorithm; The geometric data of the obstacle features are calculated to generate obstacle data.

[0011] In at least one embodiment of the present application, the specific steps of screening obstacle features from the target image based on the position coordinates of the wireless signal transmitter and the target weak signal area, and calculating the optimal path for signal reflection based on the obstacle features, the target camera, and the position coordinates of the wireless signal transmitter include: Performing three-dimensional modeling based on the obstacle data, the location information of the target camera, and the location coordinates of the wireless signal transmitter; Calculate the optimal path for signal reflection in 3D modeling.

[0012] In at least one embodiment of the present application, the indoor wireless signal control method further includes: After the wireless signal transmitter adjusts its angle along the optimal path, when in use, it receives the return signal strength of the receiving device in the target weak signal area to obtain the return signal strength; Calculating a difference between the return signal strength and the transmission signal strength of the wireless signal transmitter to obtain a signal strength difference; The transmission signal frequency band of the wireless signal transmitter is adjusted according to the signal strength difference.

[0013] In at least one embodiment of the present application, the step of adjusting the transmission signal frequency band of the wireless signal transmitter according to the signal strength difference further includes: Calculating an actual signal attenuation value based on the signal strength, the location coordinates of the wireless signal transmitter, and the target weak signal area; The transmission signal frequency band of the wireless signal transmitter is adjusted according to the actual signal attenuation value.

[0014] In at least one embodiment of the present application, the indoor wireless signal control method further includes: Acquire feature data near the obstacle feature in the target image to generate nearby feature data; screening the reflection points in the target image according to the nearby feature data to generate a reflection point set; Selecting the best reflection point from the reflection point set; A corrected reflection path is calculated according to the optimal reflection point, and a transmission angle of the wireless signal transmitter is adjusted according to the corrected reflection path.

[0015] In at least one embodiment of the present application, the specific steps of acquiring feature data near the obstacle feature in the target image and generating nearby feature data include: Performing surface feature extraction on features near the obstacle features in the target image to obtain extracted image information; Performing brightness processing on the extracted image information to obtain data features with maximum brightness; Generate nearby feature data based on the data feature with the maximum brightness and the target image.

[0016] In at least one embodiment of the present application, the specific step of selecting the best reflection point from the set of reflection points includes: The reflection point with the greatest brightness is selected from the reflection point set as the optimal reflection point.

[0017] Implementing the indoor wireless signal control method of this embodiment will have at least the following beneficial effects: In the indoor wireless signal control method provided above, the system first calculates the signal coverage range of the wireless signal transmitter in the indoor environment according to the installation location, transmission power, frequency parameters and other information of the wireless signal transmitter, and draws the signal strength distribution.

[0018] Based on the calculated signal coverage, the system filters out shadow effect areas from the signal coverage and defines these areas as target weak signal areas that need to be optimized.

[0019] The system selects a surveillance camera near the target weak signal area, adjusts the camera direction, obtains images covering the weak signal area and its surrounding environment, and generates target image data for analyzing the cause of signal attenuation.

[0020] The system combines the coordinate position of the wireless signal transmitter with the location of the target weak signal area to analyze and extract the features of obstacles that cause signal attenuation (such as walls, shelves, metal partitions, etc.) from the target image.

[0021] The system establishes a propagation model based on the characteristics of obstacles, the location of the camera, and the location of the wireless signal transmitter, and calculates the optimal reflection path in the model so that the signal can efficiently reach the target weak signal area after reflection.

[0022] Based on the calculated optimal reflection path, the system adjusts the transmission angle of the wireless signal transmitter so that its signal propagates along the optimal path. After reflection, it effectively covers the original weak signal area, thereby improving the communication quality in the area.

[0023] By calculating the signal coverage and accurately identifying the shadow effect area, the optimization target can be concentrated on the weak signal area, improving the targeting and efficiency of signal improvement.

[0024] When the layout of shopping malls, supermarkets and other environments changes (such as shelf adjustments, partition additions and subtractions), the system can recalculate the coverage range and optimal reflection path, and adjust the transmission angle in real time to maintain signal coverage quality.

[0025] By analyzing the obstacle distribution and reflection conditions and calculating the optimal reflection path, the signal attenuation during propagation can be minimized and the signal energy utilization efficiency can be improved.

[0026] The transmitter signal after angle adjustment can cover weak signal areas more stably and evenly, reducing disconnection and communication quality fluctuations caused by shadow effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0028] in: Figure 1 is a flow chart of an indoor wireless signal control method according to an embodiment; Figure 2 is a partial flow chart of an indoor wireless signal control method according to an embodiment; Figure 3 is a flow chart of an indoor wireless signal control method according to another embodiment; Figure 4 The figure is a flowchart of an indoor wireless signal control method in another embodiment. DETAILED DESCRIPTION

[0029] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0030] Provided is an indoor wireless signal control method, the indoor wireless signal control method comprising: S101. Calculate the signal coverage of the wireless signal transmitter based on the installation location, transmission power, and frequency data of the wireless signal transmitter.

[0031] S102: Obtain shadow effect area location information according to the signal coverage range, and generate a target weak signal area.

[0032] S103: Acquire an image of a target camera near the target weak signal area to generate a target image.

[0033] S104: Filter out obstacle features from the target image based on the position coordinates of the wireless signal transmitter and the target weak signal area.

[0034] S105: Calculate an optimal path for signal reflection based on the obstacle features, the target camera, and the position coordinates of the wireless signal transmitter.

[0035] S106: Adjust the transmission angle of the wireless signal transmitter according to the optimal path.

[0036] Please refer to Figures 1-4 ,In this implementation, the system first calculates the signal coverage range of the ,wireless signal transmitter in an indoor environment based on the ,installation location, transmission power, frequency parameters and other information of the ,wireless signal transmitter, and draws the signal strength ,distribution.

[0037] Based on the calculated signal coverage, the system filters out shadow effect areas from the signal coverage and defines these areas as target weak signal areas that need to be optimized.

[0038] The system selects a surveillance camera near the target weak signal area, adjusts the camera direction, obtains images covering the weak signal area and its surrounding environment, and generates target image data for analyzing the cause of signal attenuation.

[0039] The system combines the coordinate position of the wireless signal transmitter with the location of the target weak signal area to analyze and extract the features of obstacles that cause signal attenuation (such as walls, shelves, metal partitions, etc.) from the target image.

[0040] The system establishes a propagation model based on the characteristics of obstacles, the location of the camera, and the location of the wireless signal transmitter, and calculates the optimal reflection path in the model so that the signal can efficiently reach the target weak signal area after reflection.

[0041] Based on the calculated optimal reflection path, the system adjusts the transmission angle of the wireless signal transmitter so that its signal propagates along the optimal path. After reflection, it effectively covers the original weak signal area, thereby improving the communication quality in the area.

[0042] By calculating the signal coverage and accurately identifying the shadow effect area, the optimization target can be concentrated on the weak signal area, improving the targeting and efficiency of signal improvement.

[0043] When the layout of shopping malls, supermarkets and other environments changes (such as shelf adjustments, partition additions and subtractions), the system can recalculate the coverage range and optimal reflection path, and adjust the transmission angle in real time to maintain signal coverage quality.

[0044] By analyzing the obstacle distribution and reflection conditions and calculating the optimal reflection path, the signal attenuation during propagation can be minimized and the signal energy utilization efficiency can be improved.

[0045] The transmitter signal after angle adjustment can cover weak signal areas more stably and evenly, reducing disconnection and communication quality fluctuations caused by shadow effects.

[0046] It should be noted that the wireless signal transmitter is equipped with motors for pitch and horizontal angle adjustment, and the angle of the wireless signal transmitter can be adjusted by the motors in two directions.

[0047] The signal coverage range of the wireless signal transmitter is calculated as follows: .

[0048] P is the path loss at the distance point, P1 is the path loss at the reference point, and P2 is the path loss at the receiving point; n is the path loss exponent; is the shadow fading correction term; is the distance from the signal transmitter to the receiving point; is the reference distance.

[0049] .

[0050] in, is the maximum range radius of the signal coverage; Pt is the transmission power of the wireless signal transmitter; Gt is the transmitting antenna gain; PLth is the path loss threshold for weak signal judgment.

[0051] In at least one embodiment of the present application, the specific steps of calculating the signal coverage range of the wireless signal transmitter based on the installation location, transmission power, and frequency data of the wireless signal transmitter, obtaining the shadow effect area location information based on the signal coverage range, and generating the target weak signal area include: S201: Acquire location information of a wireless signal transmitter to obtain first location information.

[0052] S202: Calculate the signal strength of the wireless signal transmitter based on the first location information and the signal frequency of the wireless signal transmitter to obtain signal strength data.

[0053] S203: Calculate the signal coverage range according to the signal strength data.

[0054] S204: Obtain a weak signal strength threshold, compare the signal strength data with the weak signal strength threshold, and if the signal strength data is less than the weak signal strength threshold, mark the position as a shadow effect area within the signal coverage range.

[0055] S205: Acquire the position information of the shadow effect area and generate the target weak signal area.

[0056] Please refer to Figures 1-4 In this embodiment, the system first determines the position coordinates of the wireless signal transmitter in the indoor environment and obtains the first position information of the position.

[0057] Based on the acquired first position information and in combination with the transmission parameters of the wireless signal transmitter (such as transmission power, signal frequency, etc.), the theoretical signal strength distribution at different spatial positions is calculated using a signal propagation model to obtain signal strength data.

[0058] The system draws the outline of the signal coverage area based on the signal strength data, that is, it calculates the area that the current transmitter can theoretically cover in an indoor environment.

[0059] The system pre-sets a weak signal strength threshold and compares the calculated signal strength data against this threshold. For locations where signal strength falls below this threshold, the system identifies them as areas significantly affected by obstacles and marks them as shadowed areas within the coverage area.

[0060] The system further integrates the location information of the shadow effect area to form the target weak signal area, which serves as the key area for subsequent optimization and adjustment (such as reflection path calculation, emission angle adjustment, etc.).

[0061] By calculating the signal strength based on the transmitter location, transmission frequency, and indoor propagation model, and comparing it with the preset threshold, the specific location where the signal is attenuated can be accurately identified, avoiding reliance on manual experience or blind testing and improving positioning accuracy.

[0062] After generating the target weak signal area, a clear area range can be provided for subsequent camera image acquisition, obstacle feature recognition and optimal reflection path calculation, greatly improving the pertinence and efficiency of optimization adjustment.

[0063] In scenarios such as shopping malls and supermarkets, the layout may change over time (such as shelf adjustments and temporary booth settings). This method can dynamically generate new weak signal areas through real-time calculation and comparison, achieving rapid response to environmental changes and adaptive optimization.

[0064] In at least one embodiment of the present application, the specific steps of acquiring an image of a target camera near the target weak signal area and generating the target image include: S206: Calculate a first direction according to the first position information and the target weak signal area.

[0065] S207: Adjust the target camera near the target weak signal area according to the first direction.

[0066] S208: Obtain an image captured by a target camera in the first direction to generate the target image.

[0067] Please refer to Figures 1-4 In this embodiment, the system first calculates the first direction from the camera to the target weak signal area based on the first position information of the wireless signal transmitter and the position of the target weak signal area identified in the previous step, ensuring that the camera's viewing angle can cover the target weak signal area and take into account its surrounding environment.

[0068] After obtaining the first direction, the system adjusts the camera installed near the target weak signal area so that the camera's shooting direction is consistent with the first direction, ensuring that the camera's shooting range covers the weak signal area and possible obstructions.

[0069] After the adjustment is completed, the camera shoots the target weak signal area and its surroundings in the set first direction, obtains an image containing complete environmental information, and generates a target image.

[0070] By calculating the first direction based on the target weak signal area and adjusting the camera, it is possible to ensure that the acquired image covers the weak signal area and possible obstacles that cause signal attenuation, and the pertinence and effectiveness of the image data are significantly improved.

[0071] Since the shooting direction is precisely aimed at the weak signal area, the target image can fully reflect the environmental characteristics on the signal propagation path, providing accurate visual information support for subsequent obstacle recognition, three-dimensional modeling and reflection path calculation.

[0072] This process can automatically adjust the camera direction through calculation, without the need for manual repeated debugging of the position and angle. It is especially suitable for environments with frequent layout changes such as shopping malls and supermarkets, and can achieve the ability to quickly adapt to new layouts.

[0073] Since the camera can automatically adjust the shooting direction according to changes in weak signal areas, the system can obtain the latest environmental images in real time, thereby quickly updating the signal optimization strategy, so that the adjustment of signal coverage has continuous dynamic optimization capabilities.

[0074] In at least one embodiment of the present application, the specific steps of screening obstacle features from the target image based on the position coordinates of the wireless signal transmitter and the target weak signal area, and calculating the optimal path for signal reflection based on the obstacle features, the target camera, and the position coordinates of the wireless signal transmitter include: S209 , filtering out the obstacle features from the target image according to the first direction using an edge detection algorithm.

[0075] S210: Calculate geometric data of the obstacle features to generate obstacle data.

[0076] Please refer to Figures 1-4,In this implementation, the system first uses the location coordinates of the wireless signal transmitter, the ,location of the target weak signal area, and the target image captured by the ,camera to determine the analysis range and direction.

[0077] Based on the first direction calculated in the previous step, the system uses an edge detection algorithm in the target image to analyze the image's outlines, edge changes, and other information, identifying obstacles that may cause wireless signal attenuation, such as shelves, partition walls, and columns. This step effectively extracts key obstacle information from complex backgrounds.

[0078] For the screened obstacle features, the system further calculates its geometric parameters, including the obstacle's height, width, location coordinates, orientation, and spatial relationship relative to the wireless signal transmitter and camera.

[0079] Through these geometric parameters, the corresponding obstacle data is generated, providing accurate spatial reference for the subsequent construction of three-dimensional environment models and calculation of signal reflection paths.

[0080] Through edge detection based on the first direction, obstacle features related to signal propagation can be quickly screened out from complex indoor images, reducing interference from irrelevant information and improving recognition accuracy.

[0081] Obstacle features are converted into structured obstacle data after geometric calculation, which can be directly used for 3D modeling and path calculation, avoiding the ambiguity problem when relying solely on image information.

[0082] The geometric data of obstacles enables the system to more accurately analyze the reflection, refraction and attenuation relationship between the signal and the obstacle, thereby deriving a more realistic optimal reflection path and improving the optimization effect of coverage in weak signal areas.

[0083] When the indoor layout changes (such as shelves moving or temporary partitions being built), the system can quickly adapt to the latest environment by re-acquiring images, re-extracting obstacle features and calculating geometric data, thereby maintaining the dynamic effectiveness of signal optimization.

[0084] The calculation method of reflection loss is: .

[0085] Where: Lref is the path length; is the location coordinate of the wireless signal transmitter; is the coordinate of the obstacle reflection point; The coordinates of the receiving point in the weak signal area.

[0086] Reflection loss: .

[0087] Where Lossref is the reflection path loss; is the wavelength; is the reflection coefficient loss.

[0088] In at least one embodiment of the present application, the specific steps of screening obstacle features from the target image based on the position coordinates of the wireless signal transmitter and the target weak signal area, and calculating the optimal path for signal reflection based on the obstacle features, the target camera, and the position coordinates of the wireless signal transmitter include: S211 , performing three-dimensional modeling based on the obstacle data, the position information of the target camera, and the position coordinates of the wireless signal transmitter.

[0089] S212. Calculate an optimal path for signal reflection in the three-dimensional modeling.

[0090] Please refer to Figures 1-4 ,In this implementation, the system first combines the obstacle data obtained in the ,previous step (including the obstacle’s geometric size, shape, position coordinates and ,orientation, etc.) with the location information of the ,target camera and the location coordinates of the wireless signal transmitter ,to construct a three-dimensional model of the indoor environment.

[0091] The three-dimensional model fully reflects the spatial relationship between the transmitter, camera, obstacles and weak signal areas, providing a real spatial scenario for the accurate calculation of the signal propagation path.

[0092] In the established three-dimensional model, the system simulates the path of the signal starting from the transmitter, reflecting on the surface of obstacles and finally reaching the weak signal area based on the propagation characteristics of radio waves.

[0093] The system analyzes and compares different reflection paths, comprehensively considering factors such as the number of reflections, path loss, incident angle and reflection angle, and selects the reflection path with the minimum signal attenuation and the highest arrival efficiency, that is, the optimal reflection path.

[0094] By combining obstacle data, camera and transmitter positions for three-dimensional modeling, the indoor space structure can be truly restored, so that path calculation no longer relies on two-dimensional approximate models, thereby improving the accuracy of path calculation.

[0095] By simulating and analyzing multiple possible reflection paths in a three-dimensional model, it is possible to find the reflection path with the least loss and the best coverage. Compared with the traditional method of adjusting the emission angle based on manual experience, the accuracy is significantly improved.

[0096] When the indoor layout (such as obstacles such as shelves and partitions) changes, the system can quickly update the three-dimensional model and recalculate the optimal path by re-acquiring obstacle data, thereby maintaining the effectiveness of optimization in weak signal areas.

[0097] Through precise three-dimensional modeling and path optimization, it is possible to compensate for signal coverage in weak signal areas, significantly reduce the problem of communication quality degradation caused by shadow effects, and improve signal uniformity and stability in the entire indoor space.

[0098] In at least one embodiment of the present application, the indoor wireless signal control method further includes: S301: After adjusting the angle of the wireless signal transmitter along the optimal path, the wireless signal transmitter receives the return signal strength of the receiving device in the target weak signal area when in use to obtain the return signal strength.

[0099] S302: Calculate the difference between the return signal strength and the transmission signal strength of the wireless signal transmitter to obtain a signal strength difference.

[0100] S303: Adjust the transmission signal frequency band of the wireless signal transmitter according to the signal strength difference.

[0101] Please refer to Figures 1-4 In this embodiment, after the wireless signal transmitter adjusts the transmission angle according to the optimal reflection path and is put into use, the receiving device located in the target weak signal area will return the received signal strength information to the transmitter.

[0102] The system compares the received return signal strength with the transmitter's own transmission signal strength and obtains the signal strength difference through difference calculation.

[0103] Based on the calculated signal strength difference and the characteristics of the propagation environment, the system dynamically adjusts the transmission frequency band of the wireless signal transmitter, so that the signal avoids the frequency band with greater attenuation as much as possible during indoor propagation, thereby further improving the coverage quality of the target weak signal area.

[0104] By receiving the return signal strength in weak signal areas in real time and dynamically adjusting the frequency band based on the difference, the transmitter can adaptively optimize the signal propagation effect according to environmental changes and improve the overall communication quality.

[0105] In environments with severe shadowing effects or high signal attenuation in specific frequency bands, frequency band adjustment can effectively avoid interfering frequencies, reduce signal attenuation, and improve coverage.

[0106] In at least one embodiment of the present application, the step of adjusting the transmission signal frequency band of the wireless signal transmitter according to the signal strength difference further includes: S304: Calculate an actual signal attenuation value according to the signal strength, the location coordinates of the wireless signal transmitter, and the target weak signal area.

[0107] S305: Adjust the transmission signal frequency band of the wireless signal transmitter according to the actual signal attenuation value.

[0108] Please refer to Figures 1-4 In this embodiment, the system calculates the actual attenuation value of the signal during the propagation process based on the transmission signal strength, location coordinates and location of the target weak signal area of ​​the wireless signal transmitter, combined with the signal propagation path (including direct path or reflection path).

[0109] This calculation takes into account factors such as propagation distance, obstacle reflection loss, and indoor environment absorption to obtain attenuation data that is close to the actual propagation situation.

[0110] After obtaining the actual signal attenuation value, the system will analyze the adaptability of the signal in different frequency bands under the current attenuation conditions and select the transmission frequency band that can achieve better propagation effect at this attenuation level.

[0111] By switching to a suitable frequency band, the signal loss in the shadow effect area can be effectively reduced, thereby improving the reception quality in the target weak signal area.

[0112] This embodiment combines the calculation with the actual attenuation value to more accurately select the frequency band that best suits the current environment, thereby avoiding the problem of unstable effects caused by blind frequency band switching.

[0113] In scenarios with large actual attenuation, selecting a frequency band that adapts to the attenuation value can significantly improve signal reception in weak signal areas and enhance communication stability.

[0114] Since the attenuation value calculation combines the transmitter position and the target area position in real time, even if the indoor layout changes (such as shelves moving, partitions being added, etc.), the system can quickly recalculate the attenuation value and adjust the frequency band to maintain the optimization effect.

[0115] In at least one embodiment of the present application, the indoor wireless signal control method further includes: S401: Acquire feature data near the obstacle feature in the target image to generate nearby feature data.

[0116] S402: Filter reflection points in the target image according to the nearby feature data to generate a reflection point set.

[0117] S403: Filter out the best reflection point from the reflection point set.

[0118] S404: Calculate a corrected reflection path according to the optimal reflection point, and adjust a transmission angle of the wireless signal transmitter according to the corrected reflection path.

[0119] Please refer to Figures 1-4,In this embodiment, the system extracts image data around the identified ,obstacle features from the target image, and analyzes the characteristics of these ,neighboring areas, including surface material, surface morphology, brightness and reflection ,properties, etc., thereby generating nearby feature data.

[0120] Based on the characteristic data near the obstacle and the reflection performance judgment criteria, the system identifies the specific locations in the target image where effective signal reflections may occur, and regards these locations as reflection points and compiles them into a reflection point set.

[0121] In the set of reflection points, the system analyzes the comprehensive performance of each reflection point in terms of reflection angle, reflection loss, and the efficiency of signals reaching weak signal areas, and selects the best reflection point that can achieve low-loss reflection and improve signal coverage.

[0122] The system recalculates the reflection path based on the optimal reflection point, generates a corrected reflection path, and adjusts the transmission angle of the wireless signal transmitter accordingly, making the signal propagation path more accurate, the loss lower, and the coverage effect further improved.

[0123] By finely screening the best reflection points near obstacles, we can avoid using large or blurred reflection surfaces, making signal reflection more concentrated and efficient, thereby improving path calculation accuracy.

[0124] The selection of the optimal reflection point is based on reflection efficiency and loss analysis, which can significantly reduce unnecessary reflections and energy loss, allowing more signal energy to be effectively transmitted to weak signal areas.

[0125] When changes in the indoor environment cause changes in the location of obstacles and reflection conditions, the system can re-acquire feature data and screen the best reflection points to achieve real-time correction of the reflection path and ensure that signal coverage is always in the best state.

[0126] By correcting the reflection path and adjusting the transmitter angle, the signal can more stably cover the original weak signal area, reducing communication interruptions and quality fluctuations.

[0127] In at least one embodiment of the present application, the specific steps of acquiring feature data near the obstacle feature in the target image and generating nearby feature data include: Surface feature extraction is performed on features near the obstacle features in the target image to obtain extracted image information.

[0128] Brightness processing is performed on the extracted image information to obtain data features with maximum brightness.

[0129] Generate nearby feature data based on the data feature with the maximum brightness and the target image.

[0130] Please refer to Figures 1-4In this implementation, the system first extracts surface features from the area near the obstacle in the target image. Using image analysis techniques (such as texture analysis and contour detection), it identifies the obstacle's surface structural features, material texture, and surface properties related to reflectivity, generating extracted image information.

[0131] The system performs brightness processing on the extracted image information, analyzing the brightness of different areas of the obstacle surface within the image. Brightness variations are often closely related to the reflective properties of the surface material; areas with higher brightness typically reflect stronger signals. Through brightness processing, data features with the highest brightness can be identified as candidates for potential high-reflectivity areas.

[0132] The system combines the data feature with the overall target image information to generate feature data near the obstacle. This feature data contains information about the area of ​​the obstacle that may form the best reflection point, and provides an accurate reference for subsequent reflection point set screening.

[0133] Through surface feature extraction and brightness analysis, local areas with better reflective performance can be identified from the obstacle surface, avoiding the use of the entire obstacle surface as a general reflective surface, thereby improving the accuracy of subsequent reflection path optimization.

[0134] The areas with the highest brightness usually represent surfaces with stronger reflective properties. By locking these areas as candidate reflection points, signal reflection loss can be reduced and signal transmission efficiency can be improved.

[0135] In at least one embodiment of the present application, the specific step of selecting the best reflection point from the set of reflection points includes: The reflection point with the greatest brightness is selected from the reflection point set as the optimal reflection point.

[0136] Please refer to Figures 1-4 In this embodiment, the brightness values ​​of different reflection points in the reflection point set reflect the potential reflection performance of the surface to wireless signals. Generally speaking, the higher the brightness of the area, the stronger the surface's ability to reflect radio waves and the smaller the reflection loss.

[0137] The system compares the brightness of all reflection points in the reflection point set and selects the one with the highest brightness, identifying it as the optimal reflection point. This optimal reflection point represents the specific location that provides the best reflection path in the current environment, providing the optimal benchmark for subsequent reflection path corrections.

[0138] By using brightness value, an indicator that directly represents the reflectivity, we can quickly locate the position with the best reflective effect among many candidate reflection points, simplifying calculations and improving efficiency.

[0139] Selecting the reflection point with the highest brightness can minimize the energy loss on the reflection path, thereby increasing the effective power of the wireless signal from the transmitter through the reflection point to the weak signal area, and improving signal coverage.

[0140] Path correction based on the optimal reflection point can significantly improve the accuracy of the corrected path, so that the adjusted emission angle of the transmitter best matches the path, thereby improving coverage stability in weak signal areas.

[0141] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0142] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A method for controlling indoor wireless signals, characterized in that: The indoor wireless signal control method includes: Calculate the signal coverage of the wireless signal transmitter based on the installation location, transmission power and frequency data of the wireless signal transmitter; Obtaining shadow effect area location information based on the signal coverage range, and generating a target weak signal area; Acquire an image of a target camera near the target weak signal area to generate a target image; Screening obstacle features from the target image based on the location coordinates of the wireless signal transmitter and the target weak signal area; Calculating an optimal path for signal reflection based on the obstacle characteristics, the target camera, and the position coordinates of the wireless signal transmitter; The transmission angle of the wireless signal transmitter is adjusted according to the optimal path.

2. The indoor wireless signal control method according to claim 1, characterized in that: The specific steps of calculating the signal coverage range of the wireless signal transmitter based on the installation location, transmission power and frequency data of the wireless signal transmitter, obtaining the position information of the shadow effect area based on the signal coverage range, and generating the target weak signal area include: Acquire location information of the wireless signal transmitter to obtain first location information; Calculating the signal strength of the wireless signal transmitter based on the first location information and the signal frequency of the wireless signal transmitter to obtain signal strength data; Calculating the signal coverage range according to the signal strength data; Obtaining a weak signal strength threshold, comparing the signal strength data with the weak signal strength threshold, and if the signal strength is less than the weak signal strength threshold, marking the location of the shadow effect area within the signal coverage range; The position information of the shadow effect area is obtained to generate the target weak signal area.

3. The indoor wireless signal control method according to claim 1, characterized in that: The specific steps of acquiring an image of a target camera near the target weak signal area and generating a target image include: Calculating a first direction based on the first position information and the target weak signal area; Adjusting a target camera near the target weak signal area according to the first direction; The target camera generates the target image based on the image captured in the first direction.

4. The indoor wireless signal control method according to claim 3, characterized in that: The specific steps of screening obstacle features from the target image based on the position coordinates of the wireless signal transmitter and the target weak signal area, and calculating the optimal path of signal reflection based on the obstacle features, the target camera, and the position coordinates of the wireless signal transmitter include: Filtering the obstacle features from the target image according to the first direction using an edge detection algorithm; The geometric data of the obstacle features are calculated to generate obstacle data.

5. The indoor wireless signal control method according to claim 4, characterized in that: The specific steps of screening obstacle features from the target image based on the position coordinates of the wireless signal transmitter and the target weak signal area, and calculating the optimal path of signal reflection based on the obstacle features, the target camera, and the position coordinates of the wireless signal transmitter include: Performing three-dimensional modeling based on the obstacle data, the location information of the target camera, and the location coordinates of the wireless signal transmitter; Calculate the optimal path for signal reflection in 3D modeling.

6. The indoor wireless signal control method according to claim 1, characterized in that: The indoor wireless signal control method further includes: After the wireless signal transmitter adjusts its angle along the optimal path, when in use, it receives the return signal strength of the receiving device in the target weak signal area to obtain the return signal strength; Calculating a difference between the return signal strength and the transmission signal strength of the wireless signal transmitter to obtain a signal strength difference; The transmission signal frequency band of the wireless signal transmitter is adjusted according to the signal strength difference.

7. The indoor wireless signal control method according to claim 6, characterized in that: The step of adjusting the transmission signal frequency band of the wireless signal transmitter according to the signal strength difference further includes: Calculating an actual signal attenuation value based on the signal strength, the location coordinates of the wireless signal transmitter, and the target weak signal area; The transmission signal frequency band of the wireless signal transmitter is adjusted according to the actual signal attenuation value.

8. The indoor wireless signal control method according to claim 1, characterized in that: The indoor wireless signal control method further includes: Acquire feature data near the obstacle feature in the target image to generate nearby feature data; screening the reflection points in the target image according to the nearby feature data to generate a reflection point set; Selecting the best reflection point from the reflection point set; A corrected reflection path is calculated according to the optimal reflection point, and a transmission angle of the wireless signal transmitter is adjusted according to the corrected reflection path.

9. The indoor wireless signal control method according to claim 8, characterized in that: The specific steps of obtaining feature data near the obstacle feature in the target image and generating nearby feature data include: Performing surface feature extraction on features near the obstacle features in the target image to obtain extracted image information; Performing brightness processing on the extracted image information to obtain data features with maximum brightness; Generate nearby feature data based on the data feature with the maximum brightness and the target image.

10. The indoor wireless signal control method according to claim 8, characterized in that: The specific step of selecting the best reflection point from the reflection point set includes: The reflection point with the greatest brightness is selected from the reflection point set as the optimal reflection point.

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