Adaptive Network Management Methods and Systems for Smart Homes

Abstract

The application discloses a smart home-oriented adaptive network management method and system, relates to the technical field of communication management, and comprises the following steps: obtaining a signal coverage area and a regional network signal quality distribution map, performing spatial division, and obtaining L signal coverage division sub-areas; monitoring node arrangement is performed, and L monitoring nodes are obtained; a preset moving track of a target mobile home device is acquired, associated sub-area identification is performed in combination with L sub-area positions, M associated signal coverage division sub-areas are obtained; the L monitoring nodes are matched, M associated monitoring nodes are obtained, real-time network signal quality monitoring is performed, and adaptive network management is performed on a wireless communication network. The application solves the technical problems of insufficient wireless communication signal coverage, unreasonable bandwidth allocation and network quality fluctuation of smart home devices in a complex indoor environment in the prior art, and achieves the technical effect of improving the efficient operation of the mobile home device.

Description

Technical Field

[0001] This invention relates to the field of communication management technology, and more specifically to an adaptive network management method and system for smart homes. Background Technology

[0002] With the rapid development of smart home technology, more and more home devices and systems have become intelligent and interconnected through wireless communication networks. This is especially true for portable smart home devices such as smart robotic vacuum cleaners, portable smart speakers, and smart home control centers, whose functionality and performance are highly dependent on the quality and stability of the indoor wireless communication network. However, existing wireless communication network management methods typically focus on signal coverage and bandwidth allocation for fixed devices, neglecting the dynamic network needs and changes of portable smart devices in different areas. This can lead to problems such as weak network signals and uneven bandwidth distribution in certain situations, particularly when mobile devices move around in the home environment, affecting device performance and user experience. Summary of the Invention

[0003] This application provides an adaptive network management method and system for smart homes, which addresses the technical problems of insufficient wireless communication signal coverage, unreasonable bandwidth allocation, and network quality fluctuations faced by smart home devices in complex indoor environments.

[0004] In view of the above problems, this application provides an adaptive network management method and system for smart homes.

[0005] The first aspect of this application provides an adaptive network management method for smart homes, the method comprising:

[0006] A Wi-Fi analyzer is used to scan and analyze the network signal coverage and quality of the wireless communication network in the target indoor area, obtaining a signal coverage area and a regional network signal quality distribution map. The regional network signal quality distribution map describes the signal quality distribution of the wireless communication network within the signal coverage area. Based on the regional network signal quality distribution map, the signal coverage area is spatially divided into L signal coverage sub-regions, where L is an integer greater than or equal to 1, and each of the L signal coverage sub-regions includes L sub-region locations. Monitoring is performed within each of the L signal coverage sub-regions. The system deploys L monitoring nodes to obtain the preset movement trajectory of the target mobile home device in the target indoor area. It then identifies associated sub-regions based on the L sub-region locations, obtaining M associated signal coverage sub-regions, where M is a positive integer less than or equal to L. Based on the M associated signal coverage sub-regions, the system matches the L monitoring nodes to obtain M matched associated monitoring nodes. Real-time network signal quality monitoring is performed using these M associated monitoring nodes. Adaptive network management is then implemented for the wireless communication network in the M associated signal coverage sub-regions based on the obtained M real-time network signal quality monitoring results.

[0007] A second aspect of this application provides an adaptive network management system for smart homes, the system comprising:

[0008] The system comprises the following modules: a scanning and analysis module, which uses a Wi-Fi analyzer to scan and analyze the network signal coverage and quality of the wireless communication network in the target indoor area, obtaining a signal coverage area and a regional network signal quality distribution map, wherein the regional network signal quality distribution map describes the signal quality distribution of the wireless communication network within the signal coverage area; a spatial division module, which divides the signal coverage area spatially based on the regional network signal quality distribution map, obtaining L signal coverage sub-regions, where L is an integer greater than or equal to 1, and the L signal coverage sub-regions include L sub-region locations; and a monitoring node deployment module, which is used to deploy monitoring nodes in the L signal coverage sub-regions. The system deploys monitoring nodes within the area to obtain L monitoring nodes. A sub-area identification module is used to acquire the preset movement trajectory of the target mobile home device within the target indoor area. Combined with the locations of the L sub-areas, it identifies M associated signal coverage sub-areas, where M is a positive integer less than or equal to L. A network management module is used to match the L monitoring nodes based on the M associated signal coverage sub-areas to obtain M matched associated monitoring nodes. These M associated monitoring nodes are then used for real-time network signal quality monitoring. Based on the obtained M real-time network signal quality monitoring results, adaptive network management is performed on the wireless communication network of the M associated signal coverage sub-areas.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] This application utilizes a Wi-Fi analyzer to scan and analyze the network signal coverage and quality of a wireless communication network in a target indoor area, obtaining a signal coverage area and a regional network signal quality distribution map. The regional network signal quality distribution map describes the signal quality distribution of the wireless communication network within the signal coverage area. Based on the regional network signal quality distribution map, the signal coverage area is spatially divided into L signal coverage sub-regions, where L is an integer greater than or equal to 1, and each of the L signal coverage sub-regions includes a location within a sub-region. Monitoring is then performed within each of the L signal coverage sub-regions. The system deploys monitoring nodes to obtain L completed monitoring nodes; acquires the preset movement trajectory of the target mobile home device in the target indoor area; identifies associated sub-regions based on the L sub-region locations to obtain M associated signal coverage sub-regions, where M is a positive integer less than or equal to L; matches the L monitoring nodes based on the M associated signal coverage sub-regions to obtain M matched associated monitoring nodes; uses the M associated monitoring nodes to perform real-time network signal quality monitoring; and performs adaptive network management of the wireless communication network in the M associated signal coverage sub-regions based on the obtained M real-time network signal quality monitoring results. This invention addresses the technical problems of insufficient wireless communication signal coverage, unreasonable bandwidth allocation, and network quality fluctuations faced by smart home devices in complex indoor environments. By using a Wi-Fi analyzer to scan the target indoor area, a signal coverage area and network signal quality distribution map are obtained. The signal coverage area is then spatially divided into L signal coverage sub-regions. Monitoring nodes are deployed in each sub-region to monitor network signal quality in real time. Based on the monitoring results, adaptive network management is performed to optimize the performance and bandwidth allocation of the wireless communication network, thereby improving the efficient operation of mobile home devices. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0012] Figure 1 A schematic diagram of the adaptive network management method for smart homes provided in an embodiment of this application;

[0013] Figure 2 This is a schematic diagram of the structure of an adaptive network management system for smart homes provided in an embodiment of this application.

[0014] Figure labeling: Scanning analysis module 11, Spatial division module 12, Monitoring node deployment module 13, Associated sub-region identification module 14, Network management module 15. Detailed Implementation

[0015] This application provides an adaptive network management method and system for smart homes, addressing the technical problems of insufficient wireless communication signal coverage, unreasonable bandwidth allocation, and network quality fluctuations faced by smart home devices in complex indoor environments. By using a Wi-Fi analyzer to scan the target indoor area, the method obtains the signal coverage area and network signal quality distribution map. The signal coverage area is spatially divided into L sub-regions. Monitoring nodes are deployed in each sub-region to monitor network signal quality in real time. Based on the monitoring results, adaptive network management is performed to optimize the performance and bandwidth allocation of the wireless communication network, thereby improving the efficient operation of mobile home devices.

[0016] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0017] It should be noted that any variation of the terms "comprising" and "having" is intended to cover non-exclusive inclusion, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to such processes, methods, products, or devices.

[0018] Example 1, as Figure 1 As shown, this application provides an adaptive network management method for smart homes, the method comprising:

[0019] Step S100: Use a Wi-Fi analyzer to scan and analyze the network signal coverage and network signal quality of the wireless communication network in the target indoor area to obtain the signal coverage area and the regional network signal quality distribution map, wherein the regional network signal quality distribution map is used to describe the signal quality distribution of the wireless communication network in the signal coverage area.

[0020] In this embodiment, a Wi-Fi analyzer is used to comprehensively scan and analyze the wireless signals in the target indoor area. Wi-Fi analyzers, such as Ekahau or NetSpot, can accurately measure the wireless communication network in the target area. These analyzers scan multiple frequency bands (e.g., 2.4GHz and 5GHz bands) and record key information such as wireless signal strength, signal quality, noise level, bandwidth utilization, and interference sources in real time for each area. During signal scanning, the Wi-Fi analyzer traverses multiple locations in the target area, monitoring signal strength and quality at each point in real time. The collected data includes parameters such as signal strength index (RSSI) and signal-to-noise ratio (SNR). Based on this information, the analyzer plots a signal coverage area map, showing the distribution of signal strength in each area and determining the signal coverage area. Simultaneously, a regional network signal quality distribution map is generated based on the obtained signal quality data. This map displays the wireless network quality at different locations within the signal coverage area, including areas with weak signals and hotspots experiencing interference.

[0021] Step S200: Based on the regional network signal quality distribution map, the signal coverage area is spatially divided to obtain L signal coverage sub-regions, where L is an integer greater than or equal to 1, and the L signal coverage sub-regions include L sub-region locations.

[0022] Furthermore, in the method provided in the application embodiment, the signal coverage area is spatially divided based on the regional network signal quality distribution map to obtain L signal coverage sub-regions, and the method further includes:

[0023] Extract the minimum regional network signal quality from the regional network signal quality distribution map, use the regional network signal quality distribution map as a simulated mountain area, and use the regional network signal quality as the mountain height; take the simulated mountain corresponding to the minimum regional network signal quality as the starting point for water injection, and inject water into the simulated mountain. As the water level rises, stop injecting water when the first simulated mountain is submerged; use the mountain height at the water injection starting point as the authentication benchmark, and perform ridge line generation authentication on the first simulated mountain. If the authentication is successful, generate a ridge line at the first simulated mountain, and update the authentication benchmark based on the mountain height of the first simulated mountain to obtain a first updated authentication benchmark, wherein the ridge line rises as the water level rises; continue injecting water into the simulated mountain, and stop injecting water when the second simulated mountain is submerged, using the first The updated certification benchmark is used to generate ridge lines for the second simulated mountain. If the certification is successful, a ridge line is generated at the second simulated mountain, and the first updated certification benchmark is updated based on the mountain height of the second simulated mountain to obtain a second updated certification benchmark. This process is repeated, with water being added to the simulated mountain and ridge line generation certification performed based on the second updated certification benchmark, until the simulated mountain corresponding to the maximum mountain height in the simulated mountain area is submerged. The ridge lines on the water surface are then collected to obtain a set of ridge lines. The signal coverage area is initially spatially divided based on the set of ridge lines to obtain Q initial signal coverage sub-regions, where Q is a positive integer greater than or equal to L. The initial signal coverage sub-regions are then integrated according to their area sizes to obtain the L signal coverage sub-regions.

[0024] In this embodiment, the minimum signal quality of the regional network is first extracted from the regional network signal quality distribution map. Specifically, the signal quality value for each location is extracted from the distribution map, and then a minimum value search algorithm, such as a minimum value search based on traversal, is used to find the lowest point of signal quality in the regional network signal quality distribution map. Next, the regional network signal quality distribution map is transformed into a simulated mountain area. This step maps the signal quality data to a three-dimensional terrain model, where each value in the regional signal quality distribution map is used as the height of the simulated mountain. At this point, the regional network signal quality is used as the mountain height; areas with low signal quality have low mountain heights, and areas with high signal quality have high mountain heights. The key method for this mapping is numerical mapping and graphics rendering technology, where signal quality values ​​and height values ​​are mapped one-to-one, and simulated mountainous areas resembling mountains are generated through graphical visualization.

[0025] Then, water injection begins on the simulated hill corresponding to the minimum regional network signal quality. During this process, water flow simulation algorithms, such as digital terrain analysis, are used to inject water from the point with the worst signal quality into the surrounding area. The water injection process stops when the water level rises to a certain height and covers the first simulated hill. The first simulated hill is defined as a point whose network signal quality is only slightly higher than the minimum value.

[0026] Subsequently, the elevation of the mountain at the water injection starting point is used as the certification benchmark to generate ridge lines for the first simulated mountain. Specifically, the certification benchmark is subtracted from the elevation of the first simulated mountain, and the calculated difference is compared with a preset mountain elevation difference threshold. If the difference is greater than the preset threshold, the certification is successful. The preset mountain elevation difference threshold is pre-set by technical experts. When certification is successful, ridge lines are generated at the first simulated mountain, and the certification benchmark is updated based on the elevation of the first simulated mountain, using the elevation of the first simulated mountain as the first updated certification benchmark. The ridge lines rise as the water level rises. The ridge lines serve to separate the first simulated mountain from the water injection starting point.

[0027] Next, water is continuously added to the simulated mountain, and the water level gradually rises until it covers the second simulated mountain, at which point the water addition stops. The second simulated mountain is the first mountain area that is higher than the first simulated mountain and immediately adjacent to it. When the water level rises and covers this area, the second simulated mountain is certified using the first updated certification benchmark in the same manner as described above. If the certification is successful, a ridgeline is generated at the second simulated mountain, and the first updated certification benchmark is updated based on the mountain height of the second simulated mountain, using the mountain height of the second simulated mountain as the second updated certification benchmark.

[0028] This process continues, adding water to the simulated mountains and generating ridge lines based on the updated certification benchmarks, until the water level rises to the mountain corresponding to the maximum mountain height in the simulated mountain region. Finally, the ridge lines above the water surface are aggregated to obtain a set of ridge lines.

[0029] Subsequently, the signal coverage area is initially spatially divided based on the set of dividing ridge lines. Specifically, based on the position of each dividing ridge line in the set within the simulated mountainous area, the simulated mountainous area is divided into multiple simulated mountainous sub-regions. Furthermore, based on the one-to-one correspondence between the simulated mountainous areas and the regional network signal quality distribution map, the goal of dividing the regional network signal quality distribution map is achieved. Since the regional network signal quality distribution map describes the signal quality distribution of the wireless communication network within the signal coverage area, by establishing a one-to-one correspondence between the regional locations in the regional network signal quality distribution map and the signal coverage area, combined with the previously analyzed one-to-one correspondence between the simulated mountainous areas and the regional network signal quality distribution map, it can be concluded that the simulated mountainous areas and the signal coverage area also have a one-to-one correspondence. Therefore, based on this one-to-one correspondence, the multiple simulated mountainous sub-regions are mapped to the signal coverage area, obtaining L signal coverage sub-regions at corresponding locations, thereby achieving the goal of dividing the signal coverage area.

[0030] By using the previously generated set of dividing ridges to initially spatially divide the signal coverage area, Q initial signal coverage sub-regions are obtained. Each initial signal coverage sub-region corresponds to a relatively uniform signal quality area, and the signal intensity variations between these areas are obvious and distinguishable.

[0031] Finally, the initial signal coverage sub-regions are integrated based on their areas. First, the Q initial signal coverage sub-regions are traversed, and the area of ​​each region is calculated using a geometric algorithm (such as polygon area calculation). Next, based on a preset area threshold, these initial signal coverage sub-regions are classified into P initial signal coverage sub-regions to be merged and L initial signal coverage sub-regions that can be merged. The sum of P and L is Q, i.e., P + L = Q. Regions to be merged are typically smaller, while mergeable regions are larger. Finally, by performing a fusion operation on these regions, the smaller sub-regions are merged into a larger, more stable signal coverage sub-region, resulting in the final L signal coverage sub-regions. Here, L is an integer greater than or equal to 1, and the L signal coverage sub-regions include L sub-region locations. That is, one signal coverage sub-region corresponds to one sub-region location.

[0032] Furthermore, in the method provided in the application embodiment, using the water injection starting point as the authentication benchmark to perform ridgeline generation authentication on the first simulated mountain, it further includes:

[0033] Determine whether the difference between the height of the first simulated mountain and the authentication benchmark is less than or equal to a preset mountain height difference threshold. If yes, the authentication fails; otherwise, the authentication passes.

[0034] In this embodiment, the difference between the height of the first simulated mountain and the authentication benchmark is first calculated. Then, the calculated difference is compared with a preset mountain height difference threshold. If the calculated difference is less than or equal to the preset threshold, it means the signal quality difference of the first simulated mountain is insufficient to affect subsequent partitioning, and authentication fails. If the difference is greater than the threshold, it indicates a significant difference between the height of the first simulated mountain and the authentication benchmark, meeting the conditions for re-partitioning, and authentication passes.

[0035] Furthermore, the method provided in the application embodiments also includes:

[0036] Using the mountain height at the water injection starting point as the authentication benchmark, the first simulated mountain is divided into ridge lines for authentication. If the authentication fails, water is continuously injected into the simulated mountain, and the authentication benchmark is used to divide the simulated mountain into ridge lines for authentication during the water injection process, until the simulated mountain corresponding to the maximum mountain height in the simulated mountain area is submerged. The ridge lines located on the water surface are then summarized to obtain a set of ridge lines.

[0037] In this embodiment, the mountain height at the water injection starting point is first set as the authentication benchmark. Next, the first simulated mountain is authenticated by generating ridge lines, i.e., by comparing the differences mentioned above. If the authentication fails, water continues to be injected into the simulated mountain, and the water level gradually rises. Each time the water level reaches a new mountain, the ridge line generation authentication is performed again, and the water level is compared with the authentication benchmark again, until the water level reaches the simulated mountain corresponding to the maximum mountain height in the simulated mountain area. Each time the ridge line generation authentication passes, the authentication benchmark is updated based on the water level at the time of authentication, and a corresponding ridge line is generated for each successful authentication.

[0038] When the water level reaches its maximum height, all generated dividing ridge lines are aggregated to form a complete set of dividing ridge lines.

[0039] Furthermore, in the method provided in the application embodiment, the initial signal coverage sub-regions are integrated according to the area size of the Q initial signal coverage sub-regions to obtain the L signal coverage sub-regions, which further includes:

[0040] The area of ​​each of the Q initial signal coverage sub-regions is calculated by traversing the network. Based on a preset area threshold, the areas of the Q initial signal coverage sub-regions are divided to obtain P initial signal coverage sub-regions to be merged and L initial signal coverage sub-regions that can be merged, where P + L = Q. According to the regional network signal quality distribution map, the P initial signal coverage sub-regions to be merged are integrated into the nearest mergeable initial signal coverage sub-region among the L mergeable initial signal coverage sub-regions to obtain the L signal coverage sub-regions.

[0041] In this embodiment, firstly, Q initial signal coverage sub-regions are traversed, and the area of ​​each sub-region is calculated. Geometric calculation methods, such as polygon area algorithms, are used to calculate the actual coverage area of ​​each sub-region. If the shape of a sub-region is an irregular polygon, a segmentation method (such as dividing the region into small rectangles or triangles) is used to progressively calculate the total area of ​​each region. Through this process, the areas of the Q initial signal coverage sub-regions are obtained.

[0042] Next, based on a preset area threshold, the Q initial signal coverage sub-regions are divided into P initial signal coverage sub-regions to be merged and L initial signal coverage sub-regions that can be merged. Specifically, by comparing the areas of the Q initial signal coverage sub-regions with the preset area threshold, initial signal coverage sub-regions with areas larger than the preset area threshold are classified as initial signal coverage sub-regions that can be merged, while initial signal coverage sub-regions with areas smaller than or equal to the preset area threshold are classified as initial signal coverage sub-regions to be merged. Here, the preset area threshold is pre-set by technical experts based on needs, P represents the small areas to be merged, L represents the larger areas, and P + L = Q.

[0043] Then, based on the regional network signal quality distribution map, regional integration and fusion are performed. Specifically, for each initial signal coverage sub-region to be fused, its center point coordinates are first determined. This process is accomplished by calculating the geometric center point of the region boundary, either by calculating the centroid of the polygon or by finding the geometric center of the region through rasterization. After obtaining the center point coordinates, the next step is to calculate the straight-line distance between the center point of the initial signal coverage sub-region to be fused and the center point of each fused initial signal coverage sub-region. For this purpose, the distance between each pair of region center points is calculated using a distance formula, such as the Euclidean distance formula. For each initial signal coverage sub-region to be fused, the distance from its center point to the center points of all fused regions is calculated. Then, the closest fused initial signal coverage sub-region is selected, and the initial signal coverage sub-region to be fused is integrated into this closest fused region. Through this process, L signal coverage sub-regions are obtained.

[0044] Step S300: Deploy monitoring nodes in the L signal coverage sub-regions respectively to obtain L monitoring nodes after deployment.

[0045] In this embodiment, when deploying monitoring nodes within L signal coverage sub-regions, the geometric center method is used to calculate the center point of each sub-region. Specifically, the boundary of the sub-region is determined, and the center position of the boundary polygon is calculated. Typically, the centroid algorithm of the polygon is used, i.e., the center point is determined by calculating the average coordinates of all boundary points. Through this process, L center points corresponding to the L signal coverage sub-regions are obtained. Then, monitoring nodes are deployed at these L center points, resulting in L monitoring nodes, each located at the geometric center point of a signal coverage sub-region.

[0046] Step S400: Obtain the preset movement trajectory of the target mobile home device in the target indoor area, and identify the associated sub-regions by combining the L sub-region locations to obtain M associated signal coverage sub-regions, where M is a positive integer less than or equal to L.

[0047] In this embodiment, the preset movement trajectory of the target mobile home device within the target indoor area is first obtained. This trajectory is achieved through positioning technology (such as Wi-Fi positioning, Bluetooth positioning, or UWB positioning), enabling precise tracking of the device's movement path. The preset movement trajectory of the target device describes the possible routes the device may take within the indoor area, and is typically preset based on the device's operating mode, mobile task, or user behavior pattern.

[0048] Then, based on the locations of the L signal coverage sub-regions, the movement trajectory of the target mobile home device is associated with these sub-regions. This process involves calculating the overlap between the trajectory and the region, which is achieved through geometric spatial analysis. For example, the spatial relationship between the movement trajectory and each sub-region (such as the intersection or distance between the trajectory and the region) is used to determine whether the device has passed through a certain signal coverage sub-region.

[0049] Based on this association, the relevant areas traversed by the device are identified, thereby obtaining M associated signal coverage sub-regions, where M is a positive integer less than or equal to L.

[0050] Step S500: Based on the M associated signal coverage sub-regions, match the L monitoring nodes to obtain the M matched associated monitoring nodes, and use the M associated monitoring nodes to perform real-time network signal quality monitoring. Based on the obtained M real-time network signal quality monitoring results, perform adaptive network management on the wireless communication network of the M associated signal coverage sub-regions.

[0051] In this embodiment, a region matching algorithm is first used to match M associated signal coverage sub-regions with L known monitoring nodes. Specifically, the spatial location information of each monitoring node's signal coverage sub-region is used to associate these nodes with their corresponding associated signal coverage sub-regions. This process, based on location mapping, ensures that each associated signal coverage sub-region is matched with a monitoring node, thereby obtaining M matched associated monitoring nodes.

[0052] Then, M associated monitoring nodes are used to perform real-time network signal quality monitoring on the corresponding M associated signal coverage sub-regions. The monitoring nodes collect network signal quality data in real time according to preset network signal quality monitoring indicators, such as signal strength.

[0053] Next, a pre-trained network signal quality identifier is used to analyze and process the obtained M real-time network signal quality monitoring indicators. The network signal quality identifier can identify and evaluate signal data, generating corresponding real-time network signal quality monitoring results. Finally, based on the generated M real-time network signal quality monitoring results, adaptive network management is performed on the wireless communication network divided into M sub-regions by related signal coverage.

[0054] Furthermore, the method provided in the application embodiment, which utilizes the M associated monitoring nodes for real-time network signal quality monitoring and performs adaptive network management of the wireless communication network covering the M associated signal sub-regions based on the obtained M real-time network signal quality monitoring results, further includes:

[0055] The M associated monitoring nodes are used to monitor the M associated signal coverage sub-areas in real time according to preset network signal quality monitoring indicators to obtain M real-time network signal quality monitoring indicators; the network signal quality identifier is used to identify the M real-time network signal quality monitoring indicators to obtain the M real-time network signal quality monitoring results; when the M real-time network signal quality monitoring results are less than or equal to the preset network signal quality monitoring result threshold, the bandwidth allocation priority of the target mobile home device is adjusted to the high priority of the bandwidth allocation of the wireless communication network within the M associated signal coverage sub-areas.

[0056] Furthermore, the method provided in the application embodiments also includes:

[0057] The preset network signal quality monitoring indicators include signal strength, network bandwidth utilization, and interference source strength.

[0058] In this embodiment, M associated monitoring nodes are first used to collect real-time signal quality data for each of the M associated signal coverage sub-regions based on preset network signal quality monitoring indicators (such as signal strength, bandwidth, interference source strength, etc.). Each monitoring node obtains M real-time network signal quality monitoring indicators by measuring information such as signal strength, bandwidth utilization, and interference source strength.

[0059] Next, a network signal quality identifier is used to identify M real-time network signal quality monitoring indicators, obtaining M real-time network signal quality monitoring results. The network signal quality identifier is pre-trained. During training, a set of sample signal strength, a set of sample network bandwidth utilization, a set of sample interference source strength, and the corresponding set of sample quality identification results are first obtained from a historical database. This quality identification result set represents the scores and annotations given by technical experts based on their experience. Using the sample signal strength, sample network bandwidth utilization, and sample interference source strength sets as input data, and the sample quality identification result set as output data, a support vector machine is used for training to obtain the network signal quality identifier. The M real-time network signal quality monitoring indicators are then input into the network signal quality identifier for identification, resulting in the M real-time network signal quality monitoring results.

[0060] Next, the M real-time network signal quality monitoring results are compared with a preset network signal quality monitoring result threshold. If any one of the M real-time network signal quality monitoring results is less than or equal to the preset network signal quality monitoring result threshold, it indicates that the network quality in that area is poor and may not meet the normal usage requirements of home appliances. The preset network signal quality monitoring result threshold is a value pre-set by technical experts. In this case, within the areas where the real-time network signal quality monitoring result is less than or equal to the preset network signal quality monitoring result threshold, the bandwidth allocation priority for the target mobile home appliances in these areas is adjusted to a higher priority to ensure that the target mobile home appliances can obtain sufficient bandwidth resources in these areas to guarantee their normal operation.

[0061] In summary, the embodiments of this application have at least the following technical effects:

[0062] This application utilizes a Wi-Fi analyzer to scan and analyze the network signal coverage and quality of a wireless communication network in a target indoor area, obtaining a signal coverage area and a regional network signal quality distribution map. The regional network signal quality distribution map describes the signal quality distribution of the wireless communication network within the signal coverage area. Based on the regional network signal quality distribution map, the signal coverage area is spatially divided into L signal coverage sub-regions, where L is an integer greater than or equal to 1, and each of the L signal coverage sub-regions includes a location within a sub-region. Monitoring is then performed within each of the L signal coverage sub-regions. The system deploys monitoring nodes to obtain L completed monitoring nodes; acquires the preset movement trajectory of the target mobile home device in the target indoor area; identifies associated sub-regions based on the L sub-region locations to obtain M associated signal coverage sub-regions, where M is a positive integer less than or equal to L; matches the L monitoring nodes based on the M associated signal coverage sub-regions to obtain M matched associated monitoring nodes; uses the M associated monitoring nodes to perform real-time network signal quality monitoring; and performs adaptive network management of the wireless communication network in the M associated signal coverage sub-regions based on the obtained M real-time network signal quality monitoring results. This invention addresses the technical problems of insufficient wireless communication signal coverage, unreasonable bandwidth allocation, and network quality fluctuations faced by smart home devices in complex indoor environments. By using a Wi-Fi analyzer to scan the target indoor area, a signal coverage area and network signal quality distribution map are obtained. The signal coverage area is then spatially divided into L signal coverage sub-regions. Monitoring nodes are deployed in each sub-region to monitor network signal quality in real time. Based on the monitoring results, adaptive network management is performed to optimize the performance and bandwidth allocation of the wireless communication network, thereby improving the efficient operation of mobile home devices.

[0063] Example 2, based on the same inventive concept as the adaptive network management method for smart homes in the foregoing examples, such as... Figure 2 As shown, this application provides an adaptive network management system for smart homes. The system and method embodiments in this application are based on the same inventive concept. The system includes:

[0064] Scanning analysis module 11 is used to scan and analyze the network signal coverage and quality of the wireless communication network in the target indoor area using a Wi-Fi analyzer, obtaining a signal coverage area and a regional network signal quality distribution map, wherein the regional network signal quality distribution map is used to describe the signal quality distribution of the wireless communication network within the signal coverage area; Spatial division module 12 is used to spatially divide the signal coverage area based on the regional network signal quality distribution map, obtaining L signal coverage sub-regions, where L is an integer greater than or equal to 1, and the L signal coverage sub-regions include L sub-region locations; Monitoring node deployment module 13 is used to respectively divide the L signal coverage areas into L sub-regions. The system deploys monitoring nodes within a molecular region to obtain L monitoring nodes. A sub-region identification module 14 is used to acquire the preset movement trajectory of the target mobile home device within the target indoor area. It then identifies the associated sub-regions based on the L sub-region locations to obtain M associated signal coverage sub-regions, where M is a positive integer less than or equal to L. A network management module 15 is used to match the L monitoring nodes based on the M associated signal coverage sub-regions to obtain M matched associated monitoring nodes. It then uses these M associated monitoring nodes to perform real-time network signal quality monitoring and performs adaptive network management of the wireless communication network within the M associated signal coverage sub-regions based on the obtained M real-time network signal quality monitoring results.

[0065] Furthermore, the system is also used to implement the following functions:

[0066] Extract the minimum regional network signal quality from the regional network signal quality distribution map, use the regional network signal quality distribution map as a simulated mountain area, and use the regional network signal quality as the mountain height; take the simulated mountain corresponding to the minimum regional network signal quality as the starting point for water injection, and inject water into the simulated mountain. As the water level rises, stop injecting water when the first simulated mountain is submerged; use the mountain height at the water injection starting point as the authentication benchmark, and perform ridge line generation authentication on the first simulated mountain. If the authentication is successful, generate a ridge line at the first simulated mountain, and update the authentication benchmark based on the mountain height of the first simulated mountain to obtain a first updated authentication benchmark, wherein the ridge line rises as the water level rises; continue injecting water into the simulated mountain, and stop injecting water when the second simulated mountain is submerged, using the first The updated certification benchmark is used to generate ridge lines for the second simulated mountain. If the certification is successful, a ridge line is generated at the second simulated mountain, and the first updated certification benchmark is updated based on the mountain height of the second simulated mountain to obtain a second updated certification benchmark. This process is repeated, with water being added to the simulated mountain and ridge line generation certification performed based on the second updated certification benchmark, until the simulated mountain corresponding to the maximum mountain height in the simulated mountain area is submerged. The ridge lines on the water surface are then collected to obtain a set of ridge lines. The signal coverage area is initially spatially divided based on the set of ridge lines to obtain Q initial signal coverage sub-regions, where Q is a positive integer greater than or equal to L. The initial signal coverage sub-regions are then integrated according to their area sizes to obtain the L signal coverage sub-regions.

[0067] Furthermore, the system is also used to implement the following functions:

[0068] Determine whether the difference between the height of the first simulated mountain and the authentication benchmark is less than or equal to a preset mountain height difference threshold. If yes, the authentication fails; otherwise, the authentication passes.

[0069] Furthermore, the system is also used to implement the following functions:

[0070] Using the mountain height at the water injection starting point as the authentication benchmark, the first simulated mountain is divided into ridge lines for authentication. If the authentication fails, water is continuously injected into the simulated mountain, and the authentication benchmark is used to divide the simulated mountain into ridge lines for authentication during the water injection process, until the simulated mountain corresponding to the maximum mountain height in the simulated mountain area is submerged. The ridge lines located on the water surface are then summarized to obtain a set of ridge lines.

[0071] Furthermore, the system is also used to implement the following functions:

[0072] The area of ​​each of the Q initial signal coverage sub-regions is calculated by traversing the network. Based on a preset area threshold, the areas of the Q initial signal coverage sub-regions are divided to obtain P initial signal coverage sub-regions to be merged and L initial signal coverage sub-regions that can be merged, where P + L = Q. According to the regional network signal quality distribution map, the P initial signal coverage sub-regions to be merged are integrated into the nearest mergeable initial signal coverage sub-region among the L mergeable initial signal coverage sub-regions to obtain the L signal coverage sub-regions.

[0073] Furthermore, the system is also used to implement the following functions:

[0074] The M associated monitoring nodes are used to monitor the M associated signal coverage sub-areas in real time according to preset network signal quality monitoring indicators to obtain M real-time network signal quality monitoring indicators; the network signal quality identifier is used to identify the M real-time network signal quality monitoring indicators to obtain the M real-time network signal quality monitoring results; when the M real-time network signal quality monitoring results are less than or equal to the preset network signal quality monitoring result threshold, the bandwidth allocation priority of the target mobile home device is adjusted to the high priority of the bandwidth allocation of the wireless communication network within the M associated signal coverage sub-areas.

[0075] Furthermore, the system is also used to implement the following functions:

[0076] The preset network signal quality monitoring indicators include signal strength, network bandwidth utilization, and interference source strength.

[0077] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0078] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0079] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A self-adapting network management method for smart home, characterized in that, The method comprises: using a Wi-Fi analyzer to scan and analyze network signal coverage and network signal quality of a wireless communication network in a target indoor area, to obtain a signal coverage area and an area network signal quality distribution map, wherein the area network signal quality distribution map is used to describe signal quality distribution of the wireless communication network in the signal coverage area; spatially dividing the signal coverage area based on the area network signal quality distribution map, to obtain L signal coverage division sub-areas, wherein L is an integer greater than or equal to 1, and the L signal coverage division sub-areas include L sub-area positions; respectively deploying monitoring nodes in the L signal coverage division sub-areas, to obtain L deployed monitoring nodes; obtaining a preset moving track of a target mobile home equipment in the target indoor area, and associating and identifying a sub-area based on the L sub-area positions, to obtain M associated signal coverage division sub-areas, wherein M is a positive integer less than or equal to L; matching the L monitoring nodes based on the M associated signal coverage division sub-areas, to obtain M matched associated monitoring nodes, and using the M associated monitoring nodes to perform real-time network signal quality monitoring, and performing adaptive network management on the M associated signal coverage division sub-areas based on M obtained real-time network signal quality monitoring results; wherein spatially dividing the signal coverage area based on the area network signal quality distribution map to obtain L signal coverage division sub-areas comprises: extracting a minimum area network signal quality value from the area network signal quality distribution map, taking the area network signal quality distribution map as a simulated mountain area, and taking the area network signal quality as a mountain height; taking the simulated mountain corresponding to the minimum area network signal quality value as a water injection starting point, and injecting water into the simulated mountain, and stopping water injection when the water surface rises to the first simulated mountain; taking the mountain height of the water injection starting point as a certification reference, performing a division ridge line generation certification on the first simulated mountain, and if the certification is passed, generating a division ridge line at the first simulated mountain, and updating the certification reference based on the mountain height of the first simulated mountain to obtain a first updated certification reference, wherein the division ridge line rises with the rising of the water surface; continuing to inject water into the simulated mountain, and stopping water injection when the water surface rises to the second simulated mountain, performing a division ridge line generation certification on the second simulated mountain using the first updated certification reference, and if the certification is passed, generating a division ridge line at the second simulated mountain, and updating the first updated certification reference based on the mountain height of the second simulated mountain to obtain a second updated certification reference; continuing to inject water into the simulated mountain, and performing a division ridge line generation certification based on the second updated certification reference, until the water surface rises to the simulated mountain corresponding to the maximum mountain height in the simulated mountain area, and collecting the division ridge lines on the water surface to obtain a division ridge line set. perform initial spatial division on the signal coverage area based on the set of division ridge lines, to obtain Q initial signal coverage division sub-regions, wherein Q is a positive integer greater than or equal to L; perform initial signal coverage division sub-region integration according to the area size of the Q initial signal coverage division sub-regions, to obtain the L signal coverage division sub-regions; wherein the water injection starting point is used as a certification reference to perform division ridge line generation certification on the first simulated mountain, including: determining whether the difference between the mountain height of the first simulated mountain and the certification reference is less than or equal to a preset mountain height difference threshold value, and if so, the certification is failed; if not, the certification is passed; using the mountain height of the water injection starting point as a certification reference to perform division ridge line generation certification on the first simulated mountain, if the certification is failed, continue to inject water into the simulated mountain, and use the certification reference to perform division ridge line generation certification on the simulated mountain during the water injection process, until the simulated mountain corresponding to the maximum mountain height in the simulated mountain region, and the division ridge lines located on the water surface are collected to obtain a set of division ridge lines; wherein the initial signal coverage division sub-region integration according to the area size of the Q initial signal coverage division sub-regions, to obtain the L signal coverage division sub-regions, includes: traversing the Q initial signal coverage division sub-regions to calculate the area, to obtain Q initial signal coverage division sub-region areas; based on a preset area threshold, divide the Q initial signal coverage division sub-region areas to obtain P initial signal coverage division sub-regions to be merged and L initial signal coverage division sub-regions that can be merged, wherein P+L=Q; according to the regional network signal quality distribution map, merge the P initial signal coverage division sub-regions to be merged into the nearest initial signal coverage division sub-region that can be merged in the L initial signal coverage division sub-regions that can be merged, to obtain the L signal coverage division sub-regions; wherein, the M associated monitoring nodes are also used for real-time network signal quality monitoring, and the M associated signal coverage division sub-regions are adaptively managed according to the obtained M real-time network signal quality monitoring results, including: using the M associated monitoring nodes to monitor the M associated signal coverage division sub-regions in real time according to a preset network signal quality monitoring index, to obtain M real-time network signal quality monitoring indexes; using a network signal quality identifier to identify the M real-time network signal quality monitoring indexes, to obtain the M real-time network signal quality monitoring results; when the M real-time network signal quality monitoring results are less than or equal to a preset network signal quality monitoring result threshold value, the bandwidth allocation priority of the target mobile home equipment is adjusted to a high priority of the bandwidth allocation of the wireless communication network in the M associated signal coverage division sub-regions; wherein, the preset network signal quality monitoring index includes signal strength, network bandwidth utilization rate and interference source strength.

2. A self-adapting network management system for smart home, characterized in that, The system for executing the smart home-oriented adaptive network management method of claim 1, the system comprising: The scanning analysis module is configured to perform scanning analysis on network signal coverage and network signal quality of a wireless communication network in a target indoor area by using a Wi-Fi analyzer, to obtain a signal coverage area and an area network signal quality distribution map, wherein the area network signal quality distribution map is configured to describe signal quality distribution of the wireless communication network in the signal coverage area; The space division module is configured to perform space division on the signal coverage area based on the area network signal quality distribution map, to obtain L signal coverage division sub-areas, wherein L is an integer greater than or equal to 1, and the L signal coverage division sub-areas include L sub-area positions; The monitoring node arrangement module is configured to arrange monitoring nodes in the L signal coverage division sub-areas respectively based on the area network signal quality distribution map, to obtain L arranged monitoring nodes; The associated sub-area identification module is configured to obtain a preset moving track of a target mobile home equipment in the target indoor area, and identify associated sub-areas based on the L sub-area positions, to obtain M associated signal coverage division sub-areas, wherein M is a positive integer less than or equal to L; The network management module is configured to match the L monitoring nodes based on the M associated signal coverage division sub-areas, to obtain M associated monitoring nodes, to perform real-time network signal quality monitoring by using the M associated monitoring nodes, and to perform adaptive network management on the M associated signal coverage division sub-areas based on M obtained real-time network signal quality monitoring results.

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