Indoor-based wireless signal control method

Abstract

The embodiment of the application discloses a kind of based on indoor wireless signal control method, system first according to the installation position of wireless signal transmitter, transmission power, frequency parameter etc., signal coverage is calculated.According to signal coverage, shadow effect area is filtered out, and these areas are defined as target weak signal area needing optimization.System adjusts camera orientation, obtains the image of covering the weak signal area and its surrounding environment, generates target image data.System combines the coordinate position of wireless signal transmitter with the position of target weak signal area, analyzes and extracts the obstacle feature causing signal attenuation from target image.The system calculates the optimal reflection path of signal through reflection that can efficiently reach the target weak signal area according to the obstacle feature and camera position.System adjusts the transmission angle of wireless signal transmitter according to the optimal reflection path calculated, so that its signal propagates along the best path, thereby improving the communication quality of the area.

Description

Technical Field

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

[0002] In large shopping malls or supermarkets, due to their large area, the propagation of wireless signals can be affected by obstacles, causing significant changes in signal strength. This can lead to signal attenuation and blockage, resulting in a shadow effect.

[0003] The shadow effect occurs because obstacles (such as buildings, walls, and metal objects) attenuate radio waves. When a wireless signal encounters these obstacles during propagation, the signal strength weakens due to reflection, refraction, and scattering, forming an irregular signal shadow area.

[0004] The shadowing effect can cause signal attenuation and irregular distribution, resulting in insufficient signal strength in some areas of the communication network, causing a decline in communication quality or intermittent connection. This affects the signal in some areas and makes it inconvenient for mobile devices to use.

[0005] The current approach involves placing a repeater at a corner, oriented towards the area affected by the shadow effect. The repeater receives the wireless signal transmitted by the transmitter and retransmits it towards the shadow area to cover it. However, this method requires not only the repeater but also precise control over its installation angle. If the angle is not controlled correctly, signal transmission will be weakened. Summary of the Invention

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

[0007] An indoor-based wireless signal control method is provided, the method comprising:

[0008] Calculate the signal coverage range of the wireless signal transmitter based on its installation location, transmission power, and frequency data.

[0009] Based on the signal coverage area, obtain the location information of the shadow effect area and generate the target weak signal area;

[0010] Acquire images of the target camera near the target weak signal area and generate a target image;

[0011] Based on the location coordinates of the wireless signal transmitter and the weak signal area of ​​the target, obstacle features are selected from the target image;

[0012] The optimal path for signal reflection is calculated based on the obstacle features, the position coordinates of the target camera and the wireless signal transmitter;

[0013] Adjust the transmission angle of the wireless signal transmitter according to the optimal path.

[0014] In at least one embodiment of this application, the specific steps of calculating the signal coverage range of the wireless signal transmitter based on its installation location, transmission power, and frequency data, obtaining the location information of the shadow effect area based on the signal coverage range, and generating the target weak signal area include:

[0015] Obtain the location information of the wireless signal transmitter to obtain the first location information;

[0016] Based on the first location information and the signal frequency of the wireless signal transmitter, the signal strength of the wireless signal transmitter is calculated to obtain signal strength data;

[0017] The signal coverage area is calculated based on the signal strength data;

[0018] Obtain a weak signal strength threshold, compare the signal strength data with the weak signal strength threshold, and if it is less than the weak signal strength threshold, mark the location of the shadow effect area within the signal coverage area;

[0019] The location information of the shadow effect region is obtained, and the target weak signal region is generated.

[0020] In at least one embodiment of this application, the specific steps of acquiring images of the target camera near the target weak signal area and generating the target image include:

[0021] Calculate the first direction based on the first location information and the target weak signal region;

[0022] Adjust the target camera near the target weak signal area according to the first direction;

[0023] The target image is generated by acquiring an image captured by the target camera in the first direction.

[0024] In at least one embodiment of this application, the specific steps of filtering obstacle features from the target image based on the location 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 location coordinates of the wireless signal transmitter include:

[0025] Based on the first direction, the obstacle features are selected from the target image using an edge detection algorithm;

[0026] Calculate the geometric data of the obstacle features to generate obstacle data.

[0027] In at least one embodiment of this application, the specific steps of filtering obstacle features from the target image based on the location 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 location coordinates of the wireless signal transmitter include:

[0028] A 3D model is created based on the obstacle data, the location information of the target camera, and the location coordinates of the wireless signal transmitter.

[0029] Calculate the optimal path for signal reflection in 3D modeling.

[0030] In at least one embodiment of this application, the indoor-based wireless signal control method further includes:

[0031] After the wireless signal transmitter adjusts its angle along the optimal path, and when in use, it receives the return signal strength from the receiving device in the target weak signal area to obtain the return signal strength.

[0032] The signal strength difference is obtained by calculating the difference between the returned signal strength and the transmitted signal strength of the wireless signal transmitter;

[0033] The frequency band of the wireless signal transmitter is adjusted based on the signal strength difference.

[0034] In at least one embodiment of this application, the step of adjusting the transmission signal frequency band of the wireless signal transmitter based on the signal strength difference further includes:

[0035] The actual signal attenuation value is calculated based on the signal strength, the location coordinates of the wireless signal transmitter, and the target weak signal area;

[0036] Adjust the transmission frequency band of the wireless signal transmitter based on the actual signal attenuation value.

[0037] In at least one embodiment of this application, the indoor-based wireless signal control method further includes:

[0038] Obtain feature data near the obstacle features in the target image, and generate nearby feature data;

[0039] Based on the nearby feature data, reflection points in the target image are filtered to generate a set of reflection points;

[0040] The best reflection point is selected from the set of reflection points;

[0041] The corrected reflection path is calculated based on the optimal reflection point, and the transmission angle of the wireless signal transmitter is adjusted based on the corrected reflection path.

[0042] In at least one embodiment of this application, the specific steps of obtaining feature data near the obstacle features in the target image and generating nearby feature data include:

[0043] Surface feature extraction is performed on the features near the obstacle features in the target image to obtain the extracted image information;

[0044] The extracted image information is subjected to brightness processing to obtain the data feature with the highest brightness.

[0045] Based on the data feature with the highest brightness and the target image, nearby feature data is generated.

[0046] In at least one embodiment of this application, the specific steps of selecting the optimal reflection point from the set of reflection points include:

[0047] The brightest reflection point is selected from the set of reflection points as the optimal reflection point.

[0048] The indoor wireless signal control method of this embodiment will have at least the following beneficial effects:

[0049] The above-mentioned indoor wireless signal control method first calculates the signal coverage range of the wireless signal transmitter in the indoor environment based on information such as the installation location, transmission power, and frequency parameters, and then plots the signal strength distribution.

[0050] Based on the calculated signal coverage area, the system filters out shadow effect areas from the signal coverage area and defines these areas as target weak signal areas that need to be optimized.

[0051] The system selects surveillance cameras near the target weak signal area, adjusts the camera orientation to acquire images covering the weak signal area and its surrounding environment, and generates target image data for analyzing the cause of signal attenuation.

[0052] The system combines the coordinates of the wireless signal transmitter with the location of the target weak signal area to analyze and extract obstacle features (such as walls, shelves, metal partitions, etc.) that cause signal attenuation from the target image.

[0053] The system establishes a propagation model based on obstacle characteristics, camera location, and wireless signal transmitter location, and calculates the optimal reflection path in the model so that the signal can efficiently reach the target weak signal area after reflection.

[0054] 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 and effectively covers the original weak signal area after reflection, thereby improving the communication quality of the area.

[0055] By calculating the signal coverage area and accurately identifying shadow effect areas, the optimization target can be focused on weak signal areas, improving the targeting and efficiency of signal improvement.

[0056] When the layout of environments such as shopping malls and supermarkets changes (e.g., shelf adjustments, additions or removals of partitions), the system can recalculate the coverage area and optimal reflection path, and adjust the transmission angle in real time to maintain signal coverage quality.

[0057] By analyzing the distribution of obstacles and reflection conditions, and calculating the optimal reflection path, signal attenuation during propagation can be minimized, thereby improving signal energy utilization efficiency.

[0058] The transmitter signal, after angle adjustment, can more stably and evenly cover weak signal areas, reducing dropped calls and communication quality fluctuations caused by shadowing effects. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0060] in:

[0061] Figure 1 This is a flowchart of an indoor wireless signal control method in one embodiment;

[0062] Figure 2 This is a partial flowchart of an indoor-based wireless signal control method in one embodiment;

[0063] Figure 3 This is a flowchart of an indoor-based wireless signal control method in another embodiment;

[0064] Figure 4 This is a flowchart of an indoor-based wireless signal control method in another embodiment. Detailed Implementation

[0065] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0066] An indoor-based wireless signal control method is provided, the method comprising:

[0067] S101. Calculate the signal coverage range of the wireless signal transmitter based on its installation location, transmission power, and frequency data.

[0068] S102. Obtain the location information of the shadow effect area based on the signal coverage range, and generate the target weak signal area.

[0069] S103. Acquire images of the target camera near the target weak signal area and generate a target image.

[0070] S104. Based on the location coordinates of the wireless signal transmitter and the weak signal area of ​​the target, obstacle features are selected from the target image.

[0071] S105. Calculate the optimal path for signal reflection based on the obstacle characteristics, the position coordinates of the target camera and the wireless signal transmitter.

[0072] S106. Adjust the transmission angle of the wireless signal transmitter according to the optimal path.

[0073] Please refer to Figures 1-4 In this embodiment, the system first calculates the signal coverage range of the wireless signal transmitter in an indoor environment based on information such as the installation location, transmission power, and frequency parameters, and then plots the signal strength distribution.

[0074] Based on the calculated signal coverage area, the system filters out shadow effect areas from the signal coverage area and defines these areas as target weak signal areas that need to be optimized.

[0075] The system selects surveillance cameras near the target weak signal area, adjusts the camera orientation to acquire images covering the weak signal area and its surrounding environment, and generates target image data for analyzing the cause of signal attenuation.

[0076] The system combines the coordinates of the wireless signal transmitter with the location of the target weak signal area to analyze and extract obstacle features (such as walls, shelves, metal partitions, etc.) that cause signal attenuation from the target image.

[0077] The system establishes a propagation model based on obstacle characteristics, camera location, and wireless signal transmitter location, and calculates the optimal reflection path in the model so that the signal can efficiently reach the target weak signal area after reflection.

[0078] 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 and effectively covers the original weak signal area after reflection, thereby improving the communication quality of the area.

[0079] By calculating the signal coverage area and accurately identifying shadow effect areas, the optimization target can be focused on weak signal areas, improving the targeting and efficiency of signal improvement.

[0080] When the layout of environments such as shopping malls and supermarkets changes (e.g., shelf adjustments, additions or removals of partitions), the system can recalculate the coverage area and optimal reflection path, and adjust the transmission angle in real time to maintain signal coverage quality.

[0081] By analyzing the distribution of obstacles and reflection conditions, and calculating the optimal reflection path, signal attenuation during propagation can be minimized, thereby improving signal energy utilization efficiency.

[0082] The transmitter signal, after angle adjustment, can more stably and evenly cover weak signal areas, reducing dropped calls and communication quality fluctuations caused by shadowing effects.

[0083] It should be noted that the wireless signal transmitter is equipped with motors for pitch and horizontal angle adjustment, which can be used to adjust the angle of the wireless signal transmitter.

[0084] The method for calculating the signal coverage of the wireless signal transmitter is as follows:

[0085] .

[0086] P is the path loss at the distance point, P1 is the path loss at the reference point, P2 is the path loss at the receiving point; n is the path loss exponent. This is a shadow fading correction term; The distance from the signal transmitter to the receiver; For reference distance.

[0087] .

[0088] in, denoted as the maximum radius of signal coverage; Pt is the transmit power of the wireless transmitter; Gt is the transmit antenna gain; PLth is the path loss threshold for weak signal detection.

[0089] In at least one embodiment of this application, the specific steps of calculating the signal coverage range of the wireless signal transmitter based on its installation location, transmission power, and frequency data, obtaining the location information of the shadow effect area based on the signal coverage range, and generating the target weak signal area include:

[0090] S201. Obtain the location information of the wireless signal transmitter to obtain the first location information.

[0091] 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.

[0092] S203. Calculate the signal coverage area based on the signal strength data.

[0093] S204. Obtain a weak signal strength threshold, compare the signal strength data with the weak signal strength threshold, and if it is less than the weak signal strength threshold, mark the location of the shadow effect area within the signal coverage area.

[0094] S205. Obtain the location information of the shadow effect area and generate the target weak signal area.

[0095] Please refer to Figures 1-4 In this embodiment, the system first determines the location coordinates of the wireless signal transmitter in the indoor environment and obtains the first location information of that location.

[0096] Based on the acquired location information and combined with the transmission parameters of the wireless signal transmitter (such as transmission power, signal frequency, etc.), the theoretical signal strength distribution at different spatial locations is calculated using a signal propagation model to obtain signal strength data.

[0097] The system draws the outline of the signal coverage area based on the signal strength data, that is, it calculates the theoretical coverage area of ​​the current transmitter in the indoor environment.

[0098] The system pre-sets a weak signal strength threshold and compares the calculated signal strength data with this threshold one by one. For spatial locations with signal strength below the threshold, the system determines that they are areas significantly affected by obstacles and marks these areas as shadow effect areas within the coverage area.

[0099] 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.).

[0100] By combining the transmitter location, transmission frequency, and indoor propagation model to calculate the signal strength and comparing it with a preset threshold, the specific location where the signal attenuation occurs can be accurately identified, avoiding reliance on human experience or blind testing and improving positioning accuracy.

[0101] After generating the target weak signal area, it can provide a clear area range for subsequent camera image acquisition, obstacle feature recognition and optimal reflection path calculation, which greatly improves the pertinence and efficiency of optimization and adjustment.

[0102] In scenarios such as shopping malls and supermarkets, the layout may change over time (e.g., shelf adjustments, temporary display setups). This method can dynamically generate new weak signal areas through real-time calculation and comparison, enabling rapid response and adaptive optimization to environmental changes.

[0103] In at least one embodiment of this application, the specific steps of acquiring images of the target camera near the target weak signal area and generating the target image include:

[0104] S206. Calculate the first direction based on the first position information and the target weak signal area.

[0105] S207. Adjust the target camera near the weak signal area of ​​the target according to the first direction.

[0106] S208. Acquire the image captured by the target camera based on the first direction, and generate the target image.

[0107] 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 location information of the wireless signal transmitter and the location of the target weak signal area identified in the previous step, so as to ensure that the camera's field of view can cover the target weak signal area and take into account its surrounding environment.

[0108] 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 any possible obstructions.

[0109] After adjustment, the camera takes pictures of the target weak signal area and its surroundings in the first set direction, obtains an image containing complete environmental information, and generates the target image.

[0110] 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, thus significantly improving the targeting and effectiveness of the image data.

[0111] Because the shooting direction is precisely aimed at the weak signal area, the target image can fully reflect the environmental characteristics along the signal propagation path, providing accurate visual information support for subsequent obstacle recognition, 3D modeling and reflection path calculation.

[0112] This process can automatically adjust the camera's direction through calculation, eliminating the need for repeated manual adjustments to the position and angle. It is especially suitable for environments with frequently changing layouts, such as shopping malls and supermarkets, enabling rapid adaptation to new layouts.

[0113] Because the camera can automatically adjust its shooting direction according to changes in weak signal areas, the system can acquire the latest environmental images in real time, thereby quickly updating the signal optimization strategy and enabling continuous dynamic optimization of signal coverage.

[0114] In at least one embodiment of this application, the specific steps of filtering obstacle features from the target image based on the location 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 location coordinates of the wireless signal transmitter include:

[0115] S209. Based on the first direction, filter out the obstacle features from the target image according to the edge detection algorithm.

[0116] S210. Calculate the geometric data of the obstacle features to generate obstacle data.

[0117] Please refer to Figures 1-4 In this embodiment, 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.

[0118] Based on the first direction calculated in the previous step, the system uses an edge detection algorithm in the target image to analyze information such as contours and edge changes in the image, and filters out obstacle features that may cause wireless signal attenuation, such as shelves, partition walls, and pillars. This step can effectively extract key obstacle information in complex backgrounds.

[0119] For the selected obstacle features, the system further calculates their geometric parameters, including the obstacle's height, width, position coordinates, orientation, and spatial relationship with the wireless signal transmitter and camera.

[0120] These geometric parameters are used to generate corresponding obstacle data, providing accurate spatial references for subsequent construction of 3D environment models and calculation of signal reflection paths.

[0121] By using edge detection based on the first direction, obstacle features related to signal propagation can be quickly filtered out from complex indoor images, reducing interference from irrelevant information and improving recognition accuracy.

[0122] Obstacle features are transformed into structured obstacle data through geometric calculations, which can be directly used for 3D modeling and path calculation, avoiding the ambiguity problem when relying solely on image information.

[0123] The geometric data of obstacles enables the system to more accurately analyze the reflection, refraction, and attenuation relationship between signals and obstacles, thereby deriving a more realistic optimal reflection path and improving the optimization effect of weak signal area coverage.

[0124] When the indoor layout changes (such as moving shelves or setting up temporary partitions), the system can quickly adapt to the latest environment by reacquiring images, re-extracting obstacle features, and calculating geometric data, thus maintaining the dynamic effectiveness of signal optimization.

[0125] The method for calculating reflection loss is as follows:

[0126] .

[0127] Where: Lref is the path length; These are the coordinates of the wireless signal transmitter's location. The coordinates of the point of reflection from the obstacle; These are the coordinates of the receiving point in the weak signal area.

[0128] Reflection loss:

[0129] .

[0130] Where Lossref is the reflection path loss; Wavelength; This represents the reflection coefficient loss.

[0131] In at least one embodiment of this application, the specific steps of filtering obstacle features from the target image based on the location 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 location coordinates of the wireless signal transmitter include:

[0132] S211. Perform three-dimensional modeling based on the obstacle data, the position information of the target camera, and the position coordinates of the wireless signal transmitter.

[0133] S212. Calculate the optimal path for signal reflection in 3D modeling.

[0134] Please refer to Figures 1-4In this embodiment, the system first combines the obstacle data obtained in the previous step (including the geometric dimensions, shape, position coordinates and orientation of the obstacles) with the position information of the target camera and the position coordinates of the wireless signal transmitter to construct a three-dimensional model of the indoor environment.

[0135] This 3D model fully reflects the spatial relationships between the transmitter, camera, obstacles, and weak signal areas, providing a realistic spatial scene for accurate calculation of the signal propagation path.

[0136] In the established three-dimensional model, the system simulates the path of a signal from the transmitter, after being reflected by the surface of an obstacle, and finally reaching the weak signal area, based on the propagation characteristics of radio waves.

[0137] The system analyzes and compares different reflection paths, taking into account factors such as the number of reflections, path loss, incident angle, and reflection angle, to select the reflection path with the least signal attenuation and the highest arrival efficiency, which is the optimal reflection path.

[0138] By combining obstacle data, camera and transmitter positions for 3D modeling, the indoor space structure can be realistically reproduced, so that path calculation no longer relies on a two-dimensional approximation model, thereby improving the accuracy of path calculation.

[0139] By simulating and analyzing multiple possible reflection paths in a 3D model, the reflection path with the least loss and the best coverage effect can be found. Compared with the traditional method of adjusting the emission angle manually, the accuracy is significantly improved.

[0140] When the interior layout (such as obstacles like shelves and partitions) changes, the system can quickly update the 3D model and recalculate the optimal path by reacquiring obstacle data, thereby maintaining the effectiveness of optimization in weak signal areas.

[0141] Through precise 3D modeling and path optimization, it is possible to specifically compensate for signal coverage in weak signal areas, significantly reduce the communication quality degradation caused by the shadow effect, and improve the signal uniformity and stability of the entire indoor space.

[0142] In at least one embodiment of this application, the indoor-based wireless signal control method further includes:

[0143] S301. After the wireless signal transmitter adjusts its angle along the optimal path, and when in use, it receives the return signal strength from the receiving device in the target weak signal area to obtain the return signal strength.

[0144] S302. Calculate the difference between the returned signal strength and the transmitted signal strength of the wireless signal transmitter to obtain the signal strength difference.

[0145] S303. Adjust the transmission signal frequency band of the wireless signal transmitter according to the signal strength difference.

[0146] Please refer to Figures 1-4 In this embodiment, after the wireless signal transmitter adjusts its 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.

[0147] The system compares the strength of the received return signal with the strength of the transmitter's own transmitted signal, and calculates the signal strength difference by the difference.

[0148] 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 to ensure that the signal avoids frequency bands with large attenuation as much as possible during indoor propagation, thereby further improving the coverage quality of the target weak signal area.

[0149] 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, thereby improving the overall communication quality.

[0150] In environments with severe shadowing effects or significant signal attenuation in specific frequency bands, frequency band adjustment can effectively avoid interfering frequencies, reduce signal attenuation, and improve coverage.

[0151] In at least one embodiment of this application, the step of adjusting the transmission signal frequency band of the wireless signal transmitter based on the signal strength difference further includes:

[0152] S304. Calculate the actual signal attenuation value based on the signal strength, the location coordinates of the wireless signal transmitter, and the target weak signal area.

[0153] S305. Adjust the transmission signal frequency band of the wireless signal transmitter according to the actual signal attenuation value.

[0154] Please refer to Figures 1-4 In this embodiment, the system calculates the actual attenuation value of the signal during propagation based on the transmitted signal strength and location coordinates of the wireless signal transmitter and the location of the target weak signal area, combined with the signal propagation path (including direct path or reflection path).

[0155] The calculation takes into account factors such as propagation distance, reflection loss from obstacles, and absorption by the indoor environment to obtain attenuation data that closely approximates the actual propagation situation.

[0156] After obtaining the actual signal attenuation value, the system analyzes the adaptability of the signal under the current attenuation conditions in different frequency bands and selects the transmission frequency band that can achieve better propagation effect at that attenuation level.

[0157] Switching to a suitable frequency band can effectively reduce signal loss in shadowed areas, thereby improving reception quality in areas with weak signals.

[0158] This embodiment combines actual attenuation value calculations to more accurately select the frequency band most suitable for the current environment, avoiding the instability issues caused by blindly switching frequency bands.

[0159] In scenarios with significant attenuation, selecting a frequency band that adapts to the attenuation value can significantly improve signal reception in weak signal areas and enhance communication stability.

[0160] Because the attenuation calculation combines the transmitter location and the target area location in real time, even if the indoor layout changes (such as moving shelves or adding partitions), the system can quickly recalculate the attenuation value and adjust the frequency band to maintain the optimized effect.

[0161] In at least one embodiment of this application, the indoor-based wireless signal control method further includes:

[0162] S401. Obtain feature data near the obstacle features in the target image and generate nearby feature data.

[0163] S402. Based on the nearby feature data, filter the reflection points in the target image to generate a set of reflection points.

[0164] S403. Select the best reflection point from the set of reflection points.

[0165] S404. Calculate and correct the reflection path based on the optimal reflection point, and adjust the transmission angle of the wireless signal transmitter based on the corrected reflection path.

[0166] Please refer to Figures 1-4 In this embodiment, the system extracts image data around the features of the identified obstacles from the target image, analyzes the characteristics of these neighboring areas, including surface material, surface morphology, brightness and reflectivity, and so on, thereby generating nearby feature data.

[0167] Based on feature data near obstacles and reflection performance criteria, the system identifies specific locations in the target image that may generate effective signal reflections, and collects these locations as reflection points into a set of reflection points.

[0168] In the set of reflection points, the system analyzes the comprehensive performance of each reflection point in terms of reflection angle, reflection loss, and efficiency of signal reaching weak signal areas, and selects the best reflection point that can achieve low-loss reflection and improve signal coverage.

[0169] 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, reducing loss, and further improving the coverage effect.

[0170] By finely selecting the best reflection point from near the obstacle, it is possible to avoid using a large or blurry reflection surface, making the signal reflection more concentrated and efficient, thereby improving the accuracy of path calculation.

[0171] The selection of the optimal reflection point is based on reflection efficiency and loss analysis, which can significantly reduce unnecessary reflection and energy loss, and enable more signal energy to be effectively transmitted to the weak signal area.

[0172] When changes in the indoor environment cause changes in the position of obstacles and reflection conditions, the system can reacquire feature data and select the best reflection point to correct the reflection path in real time, ensuring that the signal coverage is always in the best state.

[0173] 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.

[0174] In at least one embodiment of this application, the specific steps of obtaining feature data near the obstacle features in the target image and generating nearby feature data include:

[0175] Surface features are extracted from the features near the obstacle in the target image to obtain the extracted image information.

[0176] The extracted image information is subjected to brightness processing to obtain the data feature with the highest brightness.

[0177] Based on the data feature with the highest brightness and the target image, nearby feature data is generated.

[0178] Please refer to Figures 1-4 In this embodiment, the system first extracts surface features from the region near the obstacle features in the target image. Then, using image analysis techniques (such as texture analysis and contour detection), it identifies the structural features, material texture, and surface properties related to reflectivity of the obstacle surface, generating the extracted image information.

[0179] The system performs brightness processing on the extracted image information to analyze the brightness performance of different regions on the obstacle surface. Brightness variations are usually closely related to the reflectivity of the surface material; areas with higher brightness typically have stronger signal reflection capabilities. Through brightness processing, the data features with the highest brightness can be identified as candidate features for potential high-efficiency reflective regions.

[0180] The system combines the data features with the highest brightness with overall target image information to generate feature data near the obstacle. This feature data contains information about the regions where the obstacle might form the best reflection points, and provides a precise reference for subsequent selection of reflection point sets.

[0181] By extracting surface features and analyzing brightness, we can identify local areas with better reflectivity from the surface of obstacles, avoiding the use of the entire obstacle surface as a general reflective surface, thereby improving the accuracy of subsequent reflection path optimization.

[0182] The brightest areas usually represent surfaces with stronger reflectivity. By identifying these areas as candidate reflection points, signal reflection loss can be reduced and signal transmission efficiency can be improved.

[0183] In at least one embodiment of this application, the specific steps of selecting the optimal reflection point from the set of reflection points include:

[0184] The brightest reflection point is selected from the set of reflection points as the optimal reflection point.

[0185] Please refer to Figures 1-4 In this embodiment, the brightness values ​​of different reflection points in the set of reflection points reflect the potential reflection performance of their surfaces to wireless signals. Generally, the higher the brightness of an area, the stronger its ability to reflect radio waves and the lower its reflection loss.

[0186] The system compares the brightness values ​​of all reflection points in the set and selects the reflection point with the highest brightness as the optimal reflection point. This optimal reflection point represents the specific location that can provide the best reflection path in the current environment, providing an optimal benchmark for subsequent reflection path correction.

[0187] By using brightness value, an indicator that directly represents reflectivity, we can quickly identify the position with the best reflection effect among many candidate reflection points, simplifying calculations and improving efficiency.

[0188] Choosing the brightest reflection point minimizes energy loss along the reflection path, thereby increasing the effective power of the wireless signal from the transmitter to the weak signal area via the reflection point and improving signal coverage.

[0189] Using the optimal reflection point as a reference for path correction can significantly improve the accuracy of the correction path, ensuring that the transmitter's adjusted transmission angle best matches the path, thereby enhancing the coverage stability in weak signal areas.

[0190] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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.

[0191] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A wireless signal control method based on indoor environments, characterized in that, The indoor-based wireless signal control method includes: Calculate the signal coverage range of the wireless signal transmitter based on its installation location, transmission power, and frequency data. Based on the signal coverage area, obtain the location information of the shadow effect area and generate the target weak signal area; Acquire images of the target camera near the target weak signal area and generate a target image; Based on the location coordinates of the wireless signal transmitter and the weak signal area of ​​the target, obstacle features are selected from the target image; The optimal path for signal reflection is calculated based on the obstacle features, the position coordinates of the target camera and the wireless signal transmitter; Adjust the transmission angle of the wireless signal transmitter 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 its installation location, transmission power, and frequency data, obtaining the location information of the shadow effect area based on the signal coverage range, and generating the target weak signal area include: Obtain the location information of the wireless signal transmitter to obtain the first location information; Based on the first location information and the signal frequency of the wireless signal transmitter, the signal strength of the wireless signal transmitter is calculated to obtain signal strength data; The signal coverage area is calculated based on the signal strength data; Obtain a weak signal strength threshold, compare the signal strength data with the weak signal strength threshold, and if it is less than the weak signal strength threshold, mark the location of the shadow effect area within the signal coverage area; The location information of the shadow effect region is obtained, and the target weak signal region is generated.

3. The indoor wireless signal control method according to claim 1, characterized in that, The specific steps for acquiring images of the target camera near the target weak signal area and generating the target image include: Calculate the first direction based on the first location information and the target weak signal region; Adjust the target camera near the target weak signal area according to the first direction; The target image is generated by acquiring an image captured by the target camera in the first direction.

4. The indoor wireless signal control method according to claim 3, characterized in that, The specific steps of filtering obstacle features from the target image based on the location 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 location coordinates of the wireless signal transmitter include: Based on the first direction, the obstacle features are selected from the target image using an edge detection algorithm; Calculate the geometric data of the obstacle features to generate obstacle data.

5. The indoor wireless signal control method according to claim 4, characterized in that, The specific steps of filtering obstacle features from the target image based on the location 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 location coordinates of the wireless signal transmitter include: A 3D model is created 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-based wireless signal control method further includes: After the wireless signal transmitter adjusts its angle along the optimal path, it receives the return signal strength from the receiving device in the target weak signal area when in use, and obtains the return signal strength. The signal strength difference is obtained by calculating the difference between the returned signal strength and the transmitted signal strength of the wireless signal transmitter; The frequency band of the wireless signal transmitter is adjusted based on 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 based on the signal strength difference further includes: The actual signal attenuation value is calculated based on the signal strength, the location coordinates of the wireless signal transmitter, and the target weak signal area; Adjust the transmission frequency band of the wireless signal transmitter based on the actual signal attenuation value.

8. The indoor wireless signal control method according to claim 1, characterized in that, The indoor-based wireless signal control method further includes: Obtain feature data near the obstacle features in the target image, and generate nearby feature data; Based on the nearby feature data, reflection points in the target image are filtered to generate a set of reflection points; The best reflection point is selected from the set of reflection points; The corrected reflection path is calculated based on the optimal reflection point, and the transmission angle of the wireless signal transmitter is adjusted based on the corrected reflection path.

9. The indoor wireless signal control method according to claim 8, characterized in that, The specific steps for obtaining feature data near the obstacle features in the target image and generating nearby feature data include: Surface feature extraction is performed on the features near the obstacle features in the target image to obtain the extracted image information; The extracted image information is subjected to brightness processing to obtain the data feature with the highest brightness. Based on the data feature with the highest brightness and the target image, nearby feature data is generated.

10. The indoor wireless signal control method according to claim 8, characterized in that, The specific steps for selecting the optimal reflection point from the set of reflection points include: The brightest reflection point is selected from the set of reflection points as the optimal reflection point.

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