A Home Appliance Networking Method and System Based on Dynamic Programming Algorithm

Abstract

This invention discloses a home device networking method and system based on dynamic programming algorithm. The method includes: responding to a target user's networking operation, acquiring device parameters of multiple home devices to be networked and area parameters of the networking area; determining the networking requirements corresponding to the target user based on the area parameters and the networking operation; determining the relevant function conditions corresponding to the current networking operation based on the networking requirements and the device parameters; and performing calculations on the multiple home devices based on the dynamic programming algorithm, according to the relevant function conditions and the device parameters, to obtain the networking scheme corresponding to the networking operation. Therefore, this invention can fully combine the user's networking requirements and device parameters to determine the networking scheme, achieving more intelligent and reasonable home device networking and improving communication stability in home scenarios.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method and system for networking home devices based on dynamic programming algorithms. Background Technology

[0002] With the increasing intelligence of home appliances and the development of network technology, the demand for communication networking in home scenarios is also rising. In particular, the increasing number of smart home devices necessitates more complex and refined networking strategies for device management. Existing device networking solutions generally rely on manual setup by engineers, failing to fully consider user networking needs and the characteristics of devices in the scenario to achieve intelligent automatic networking. Therefore, their networking effectiveness and efficiency are generally limited. Clearly, existing technologies have shortcomings that urgently need to be addressed. Summary of the Invention

[0003] The technical problem to be solved by this invention is to provide a home device networking method and system based on dynamic programming algorithm, which can fully combine the user's networking needs and device parameters to determine the networking scheme, realize more intelligent and reasonable home device networking, and improve communication stability in home scenarios.

[0004] To address the aforementioned technical problems, the first aspect of this invention discloses a home appliance networking method based on a dynamic programming algorithm, the method comprising:

[0005] In response to the target user's networking operation, obtain the device parameters of multiple home devices to be networked and the area parameters of the networking area;

[0006] Based on the regional parameters and the networking operation, determine the networking requirements corresponding to the target user;

[0007] Based on the networking requirements and the device parameters, determine the relevant function conditions corresponding to the current networking.

[0008] Based on the dynamic programming algorithm, the network scheme corresponding to the networking operation is obtained by performing calculations on the multiple home devices according to the relevant function conditions and the device parameters.

[0009] As an optional implementation, in the first aspect of the present invention, the networking operation includes the target user's selection operation and information input operation of at least one of the home devices; the device parameters include device location, device performance, device hardware model, and device software version.

[0010] As an optional implementation, in a first aspect of the invention, the regional parameters include the area, geographic location, and shape of the network region.

[0011] As an optional implementation, in the first aspect of the invention, the region parameters are obtained through the following steps:

[0012] Obtain the device locations of the multiple home appliances;

[0013] The device parameters and device locations of all the home appliances are input into a trained region shape prediction neural network to obtain the output region shape;

[0014] The shape of the region is determined to be the shape of the network region;

[0015] Calculate the shape region with the smallest area that contains the device locations of all the home appliances on its edges, using the shape of the region as a template.

[0016] Calculate the geometric center position of the shape region, and determine the latitude and longitude position corresponding to the geometric center position as the geographic location of the network region;

[0017] Calculate the area of ​​the shaped region and determine it as the area of ​​the network region.

[0018] As an optional implementation, in the first aspect of the present invention, determining the networking requirements corresponding to the target user based on the regional parameters and the networking operation includes:

[0019] Based on the selection operation in the networking operation, obtain the device historical networking record of the home device corresponding to the selection operation;

[0020] The networking purpose is selected from multiple networking records in the network area from the historical networking records of the device to obtain a set of historical networking purposes;

[0021] The regional parameters are input into a trained regional networking demand prediction neural network to obtain multiple output regional networking demands.

[0022] Calculate the intersection between the multiple regional networking requirements and the historical networking target set to obtain the multiple networking requirements corresponding to the target user.

[0023] As an optional implementation, in the first aspect of the present invention, the networking requirements are communication optimization requirements, device synchronization requirements, device control requirements, function combination requirements, or access control requirements.

[0024] As an optional implementation, in the first aspect of the present invention, determining the relevant function conditions corresponding to the current network configuration based on the network requirements and the device parameters includes:

[0025] Based on the pre-defined correspondence between requirements and constraints, the algorithm constraints corresponding to each networking requirement are determined; the algorithm constraints include device performance constraints, device location constraints, and device software function constraints.

[0026] Based on the clustering algorithm and the algorithm constraints, all the network requirements are clustered to obtain a target network requirement set; wherein, the similarity between the algorithm constraints corresponding to any two network requirements in the target network requirement set is greater than a first similarity threshold, and the similarity between the algorithm constraint corresponding to any network requirement in the target network requirement set and the algorithm constraint of any network requirement not in the target network requirement set is less than a second similarity threshold; the second similarity threshold is less than the first similarity threshold;

[0027] The objective function is to minimize the number of devices in the network topology scheme.

[0028] The limiting conditions are defined as the algorithmic limiting conditions corresponding to all the network requirements in the target network requirement set, as determined by the network topology scheme.

[0029] As an optional implementation, in the first aspect of the present invention, the step of using a dynamic programming algorithm to calculate the networking scheme corresponding to the networking operation based on the relevant function conditions and the device parameters for the plurality of home devices includes:

[0030] Based on the spatial search algorithm, the networking schemes corresponding to the multiple home devices are iteratively calculated according to the objective function and the constraints.

[0031] In the iterative calculation, it is repeatedly determined whether the networking scheme meets the constraints and the objective function until the optimal networking scheme is obtained and determined as the networking scheme corresponding to the networking operation.

[0032] A second aspect of this invention discloses a home appliance networking system based on a dynamic programming algorithm, the system comprising:

[0033] The acquisition module is used to respond to the networking operation of the target user and acquire the device parameters of multiple home devices to be networked and the area parameters of the networking area.

[0034] The first determining module is used to determine the networking requirements corresponding to the target user based on the regional parameters and the networking operation.

[0035] The second determining module is used to determine the relevant function conditions corresponding to the current networking based on the networking requirements and the device parameters.

[0036] The calculation module is used to perform calculations on the multiple home devices based on the dynamic programming algorithm, according to the relevant function conditions and the device parameters, to obtain the networking scheme corresponding to the networking operation.

[0037] As an optional implementation, in a second aspect of the invention, the networking operation includes the target user's selection operation and information input operation of at least one of the home devices; the device parameters include device location, device performance, device hardware model, and device software version.

[0038] As an optional implementation, in a second aspect of the invention, the regional parameters include the area, geographic location, and shape of the network region.

[0039] As an optional implementation, in a second aspect of the invention, the region parameters are obtained through the following steps:

[0040] Obtain the device locations of the multiple home appliances;

[0041] The device parameters and device locations of all the home appliances are input into a trained region shape prediction neural network to obtain the output region shape;

[0042] The shape of the region is determined to be the shape of the network region;

[0043] Calculate the shape region with the smallest area that contains the device locations of all the home appliances on its edges, using the shape of the region as a template.

[0044] Calculate the geometric center position of the shape region, and determine the latitude and longitude position corresponding to the geometric center position as the geographic location of the network region;

[0045] Calculate the area of ​​the shaped region and determine it as the area of ​​the network region.

[0046] As an optional implementation, in a second aspect of the invention, the first determining module determines the specific method by which it determines the networking requirements corresponding to the target user based on the regional parameters and the networking operation, including:

[0047] Based on the selection operation in the networking operation, obtain the device historical networking record of the home device corresponding to the selection operation;

[0048] The networking purpose is selected from multiple networking records in the network area from the historical networking records of the device to obtain a set of historical networking purposes;

[0049] The regional parameters are input into a trained regional networking demand prediction neural network to obtain multiple output regional networking demands.

[0050] Calculate the intersection between the multiple regional networking requirements and the historical networking target set to obtain the multiple networking requirements corresponding to the target user.

[0051] As an optional implementation, in the second aspect of the present invention, the networking requirements are communication optimization requirements, device synchronization requirements, device control requirements, function combination requirements, or access control requirements.

[0052] As an optional implementation, in a second aspect of the invention, the second determining module determines the specific method by which it determines the relevant function conditions corresponding to the current network configuration based on the network requirements and the device parameters, including:

[0053] Based on the pre-defined correspondence between requirements and constraints, the algorithm constraints corresponding to each networking requirement are determined; the algorithm constraints include device performance constraints, device location constraints, and device software function constraints.

[0054] Based on the clustering algorithm and the algorithm constraints, all the network requirements are clustered to obtain a target network requirement set; wherein, the similarity between the algorithm constraints corresponding to any two network requirements in the target network requirement set is greater than a first similarity threshold, and the similarity between the algorithm constraint corresponding to any network requirement in the target network requirement set and the algorithm constraint of any network requirement not in the target network requirement set is less than a second similarity threshold; the second similarity threshold is less than the first similarity threshold;

[0055] The objective function is to minimize the number of devices in the network topology scheme.

[0056] The limiting conditions are defined as the algorithmic limiting conditions corresponding to all the network requirements in the target network requirement set, as determined by the network topology scheme.

[0057] As an optional implementation, in a second aspect of the invention, the calculation module, based on a dynamic programming algorithm, performs calculations on the plurality of home devices according to the relevant function conditions and the device parameters to obtain a specific method for the networking scheme corresponding to the networking operation, including:

[0058] Based on the spatial search algorithm, the networking schemes corresponding to the multiple home devices are iteratively calculated according to the objective function and the constraints.

[0059] In the iterative calculation, it is repeatedly determined whether the networking scheme meets the constraints and the objective function until the optimal networking scheme is obtained and determined as the networking scheme corresponding to the networking operation.

[0060] A third aspect of this invention discloses another home appliance networking system based on a dynamic programming algorithm, the system comprising:

[0061] Memory containing executable program code;

[0062] A processor coupled to the memory;

[0063] The processor calls the executable program code stored in the memory to execute some or all of the steps in the home device networking method based on dynamic programming algorithm disclosed in the first aspect of the present invention.

[0064] The fourth aspect of the present invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute some or all of the steps in the home device networking method based on dynamic programming algorithm disclosed in the first aspect of the present invention.

[0065] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0066] This invention can determine the networking requirements of a target user based on the regional parameters of the networking area and the user's networking operations. Then, based on the networking requirements and the device parameters of multiple home devices to be networked, it determines the relevant function conditions for the current networking. Based on the dynamic programming algorithm, it calculates the corresponding networking scheme according to the relevant function conditions and device parameters. This allows for a more intelligent and reasonable home device networking, improving communication stability in home scenarios. Attached Figure Description

[0067] 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.

[0068] Figure 1 This is a flowchart illustrating a home device networking method based on dynamic programming algorithm disclosed in an embodiment of the present invention.

[0069] Figure 2 This is a schematic diagram of a home appliance networking system based on dynamic programming algorithm disclosed in an embodiment of the present invention.

[0070] Figure 3 This is a schematic diagram of another home device networking system based on dynamic programming algorithm disclosed in an embodiment of the present invention. Detailed Implementation

[0071] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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.

[0072] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0073] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0074] This invention discloses a home device networking method and system based on dynamic programming algorithms. It can determine the networking requirements of a target user based on the area parameters of the networking region and the user's networking operations. Then, based on the networking requirements and the device parameters of multiple home devices to be networked, it determines the relevant function conditions for the current networking operation. Using dynamic programming algorithms, it calculates the corresponding networking scheme based on the relevant function conditions and device parameters. This allows for a more intelligent and rational home device networking solution that fully combines the user's networking requirements and device parameters, improving communication stability in home scenarios. Detailed explanations follow.

[0075] Example 1

[0076] Please see Figure 1 , Figure 1 This is a flowchart illustrating a home appliance networking method based on dynamic programming algorithm disclosed in an embodiment of the present invention. Figure 1 As shown, the home device networking method based on dynamic programming algorithm can include the following operations:

[0077] 101. In response to the target user's networking operation, obtain the device parameters of the multiple home devices to be networked and the area parameters of the networking area.

[0078] 102. Based on the regional parameters and network operations, determine the network requirements corresponding to the target users.

[0079] 103. Based on the networking requirements and equipment parameters, determine the relevant function conditions corresponding to the current networking.

[0080] 104. Based on the dynamic programming algorithm, and according to the relevant function conditions and device parameters, perform calculations on multiple home devices to obtain the networking scheme corresponding to the networking operation.

[0081] As can be seen, the above-described embodiments of the invention can determine the networking requirements of the target user based on the regional parameters of the networking area and the user's networking operations. Then, based on the networking requirements and the device parameters of the multiple home devices to be networked, the relevant function conditions corresponding to the current networking are determined. The corresponding networking scheme is calculated based on the relevant function conditions and device parameters using a dynamic programming algorithm. This allows for a full combination of the user's networking requirements and device parameters to determine the networking scheme, achieving more intelligent and reasonable home device networking and improving communication stability in home scenarios.

[0082] As an optional embodiment, the networking operation in the above steps includes the target user's selection operation and information input operation of at least one home device; the device parameters include device location, device performance, device hardware model, and device software version.

[0083] As can be seen, the above optional embodiments limit the content of network operation and device parameters to comprehensively characterize the user's operating characteristics and the device characteristics of home devices, so as to facilitate the determination of subsequent network schemes, assist in determining the network scheme by fully combining the user's network needs and device parameters, achieve more intelligent and reasonable home device networking, and improve communication stability in home scenarios.

[0084] As an optional embodiment, the regional parameters in the above steps include the area, geographic location, and shape of the network area.

[0085] As can be seen, the above optional embodiments define the content of the regional parameters to comprehensively characterize the features of the network area, so as to facilitate the determination of the subsequent network scheme. This helps to fully combine the user's network needs and device parameters to determine the network scheme, achieve more intelligent and reasonable home device networking, and improve the communication stability in the home scenario.

[0086] As an optional embodiment, the region parameters in the above steps are obtained through the following steps:

[0087] Get the device locations of multiple home appliances;

[0088] The device parameters and device locations of all home appliances are input into a trained region shape prediction neural network to obtain the output region shape;

[0089] The shape of the region is determined to be the shape of the network region;

[0090] Calculate the smallest shape region with the device locations of all home appliances on its edges, using the region shape as a template.

[0091] Calculate the geometric center of the shape region and determine the latitude and longitude of the corresponding geometric center as the geographic location of the network area;

[0092] Calculate the area of ​​the shape region and determine it as the area of ​​the network region.

[0093] As can be seen, through the above optional embodiments, the location of home devices in the scene can be predicted and calculated to obtain regional parameters, so as to comprehensively characterize the characteristics of the networking area, so as to facilitate the determination of subsequent networking schemes, assist in determining the networking scheme by fully combining the user's networking needs and device parameters, realize more intelligent and reasonable home device networking, and improve the communication stability in the home scene.

[0094] As an optional embodiment, the step above, determining the network requirements corresponding to the target user based on regional parameters and network operations, includes:

[0095] Based on the selection operation in the networking operation, obtain the device historical networking records of the home device corresponding to the selected operation;

[0096] Filter out the networking purposes from multiple networking records that are networking in the networking area in the device's historical networking records to obtain the historical networking purpose set;

[0097] The regional parameters are input into a trained regional networking demand prediction neural network to obtain multiple regional networking demands in the output.

[0098] Calculate the intersection between multiple regional networking requirements and the historical set of networking objectives to obtain multiple networking requirements corresponding to the target user.

[0099] As can be seen, through the above optional embodiments, based on the preset objective function and constraints, the most reasonable and similar three-dimensional spatial model that conforms to the characteristics of the target space can be calculated by dynamic programming algorithm, so as to facilitate subsequent accurate simulation prediction, assist in determining the networking scheme by fully combining the user's networking needs and device parameters, realize more intelligent and reasonable home device networking, and improve the communication stability in the home scene.

[0100] As an optional embodiment, the networking requirements in the above steps may be communication optimization requirements, device synchronization requirements, device control requirements, function combination requirements, or access control requirements.

[0101] As can be seen, the above optional embodiments define the types of networking requirements to accurately characterize the features of users' networking needs, so as to facilitate the determination of subsequent networking schemes. This helps to fully combine users' networking needs and device parameters to determine the networking scheme, achieve more intelligent and reasonable home device networking, and improve communication stability in home scenarios.

[0102] As an optional embodiment, the step above, determining the relevant function conditions corresponding to the current network configuration based on network requirements and device parameters, includes:

[0103] Based on the pre-defined correspondence between requirements and constraints, the algorithm constraints corresponding to each network requirement are determined; optionally, the algorithm constraints include equipment performance constraints, equipment location constraints, and equipment software function constraints.

[0104] Based on clustering algorithms and algorithm constraints, all networking requirements are clustered to obtain a target networking requirement set. Optionally, the similarity between the algorithm constraints corresponding to any two networking requirements in the target networking requirement set is greater than a first similarity threshold, and the similarity between the algorithm constraints corresponding to any networking requirement in the target networking requirement set and the algorithm constraints of any networking requirement in a non-target networking requirement set is less than a second similarity threshold; the second similarity threshold is less than the first similarity threshold.

[0105] The objective function is to minimize the number of devices in the network topology scheme.

[0106] The constraints are defined as the algorithmic constraints that ensure the networking scheme meets all networking requirements in the target networking requirement set.

[0107] As can be seen, through the above optional embodiments, the algorithm constraints corresponding to each network requirement can be determined based on the correspondence between preset requirements and constraints. After clustering the optimal requirement set based on the similarity between the algorithm constraints, the objective function and constraints are determined based on the constraints in the set, so as to obtain the optimal networking scheme in subsequent calculations. This helps to fully combine the user's networking requirements and device parameters to determine the networking scheme, realize more intelligent and reasonable home device networking, and improve the communication stability in home scenarios.

[0108] As an optional embodiment, the above steps, based on a dynamic programming algorithm, calculate the networking scheme corresponding to the networking operation for multiple home devices according to relevant function conditions and device parameters, including:

[0109] Based on the spatial search algorithm, the networking schemes for multiple home devices are iteratively calculated according to the objective function and constraints;

[0110] In the iterative calculation, it is repeatedly determined whether the networking scheme meets the constraints and objective function until the optimal networking scheme is obtained and determined as the networking scheme corresponding to the networking operation.

[0111] As can be seen, through the above optional embodiments, the networking schemes corresponding to multiple home devices can be iteratively calculated based on the objective function and constraints according to the spatial search algorithm until the optimal networking scheme is obtained. This fully combines the user's networking needs and device parameters to determine the networking scheme, achieving more intelligent and reasonable home device networking and improving communication stability in home scenarios.

[0112] Example 2

[0113] Please see Figure 2 , Figure 2 This is a schematic diagram of a home appliance networking system based on a dynamic programming algorithm, as disclosed in an embodiment of the present invention. Figure 2 As shown, the home device networking system based on dynamic programming algorithm may include:

[0114] The acquisition module 201 is used to respond to the networking operation of the target user and acquire the device parameters of multiple home devices to be networked and the area parameters of the networking area.

[0115] The first determining module 202 is used to determine the networking requirements of the target user based on the regional parameters and networking operations.

[0116] The second determining module 203 is used to determine the relevant function conditions corresponding to the current networking based on networking requirements and device parameters.

[0117] The calculation module 204 is used to perform calculations on multiple home devices based on dynamic programming algorithms, relevant function conditions, and device parameters to obtain the networking scheme corresponding to the networking operation.

[0118] As can be seen, the above-described embodiments of the invention can determine the networking requirements of the target user based on the regional parameters of the networking area and the user's networking operations. Then, based on the networking requirements and the device parameters of the multiple home devices to be networked, the relevant function conditions corresponding to the current networking are determined. The corresponding networking scheme is calculated based on the relevant function conditions and device parameters using a dynamic programming algorithm. This allows for a full combination of the user's networking requirements and device parameters to determine the networking scheme, achieving more intelligent and reasonable home device networking and improving communication stability in home scenarios.

[0119] As an optional embodiment, the networking operation includes the target user's selection of at least one home device and information input; the device parameters include device location, device performance, device hardware model, and device software version.

[0120] As can be seen, the above optional embodiments limit the content of network operation and device parameters to comprehensively characterize the user's operating characteristics and the device characteristics of home devices, so as to facilitate the determination of subsequent network schemes, assist in determining the network scheme by fully combining the user's network needs and device parameters, achieve more intelligent and reasonable home device networking, and improve communication stability in home scenarios.

[0121] As an optional embodiment, the regional parameters include the area, geolocation, and shape of the network area.

[0122] As can be seen, the above optional embodiments define the content of the regional parameters to comprehensively characterize the features of the network area, so as to facilitate the determination of the subsequent network scheme. This helps to fully combine the user's network needs and device parameters to determine the network scheme, achieve more intelligent and reasonable home device networking, and improve the communication stability in the home scenario.

[0123] As an optional embodiment, the region parameters are obtained through the following steps:

[0124] Get the device locations of multiple home appliances;

[0125] The device parameters and device locations of all home appliances are input into a trained region shape prediction neural network to obtain the output region shape;

[0126] The shape of the region is determined to be the shape of the network region;

[0127] Calculate the smallest shape region with the device locations of all home appliances on its edges, using the region shape as a template.

[0128] Calculate the geometric center of the shape region and determine the latitude and longitude of the corresponding geometric center as the geographic location of the network area;

[0129] Calculate the area of ​​the shape region and determine it as the area of ​​the network region.

[0130] As can be seen, through the above optional embodiments, the location of home devices in the scene can be predicted and calculated to obtain regional parameters, so as to comprehensively characterize the characteristics of the networking area, so as to facilitate the determination of subsequent networking schemes, assist in determining the networking scheme by fully combining the user's networking needs and device parameters, realize more intelligent and reasonable home device networking, and improve the communication stability in the home scene.

[0131] As an optional embodiment, the first determining module determines the specific method of the network requirements corresponding to the target user based on the regional parameters and network operations, including:

[0132] Based on the selection operation in the networking operation, obtain the device historical networking records of the home device corresponding to the selected operation;

[0133] Filter out the networking purposes from multiple networking records that are networking in the networking area in the device's historical networking records to obtain the set of historical networking purposes;

[0134] The regional parameters are input into a trained regional networking demand prediction neural network to obtain multiple regional networking demands in the output.

[0135] Calculate the intersection between multiple regional networking requirements and the historical set of networking objectives to obtain multiple networking requirements corresponding to the target user.

[0136] As can be seen, through the above optional embodiments, based on the preset objective function and constraints, the most reasonable and similar three-dimensional spatial model that conforms to the characteristics of the target space can be calculated by dynamic programming algorithm, so as to facilitate subsequent accurate simulation prediction, assist in determining the networking scheme by fully combining the user's networking needs and device parameters, realize more intelligent and reasonable home device networking, and improve the communication stability in the home scene.

[0137] As an optional embodiment, the networking requirements include communication optimization requirements, device synchronization requirements, device control requirements, function combination requirements, or access control requirements.

[0138] As can be seen, the above optional embodiments define the types of networking requirements to accurately characterize the features of users' networking needs, so as to facilitate the determination of subsequent networking schemes. This helps to fully combine users' networking needs and device parameters to determine the networking scheme, achieve more intelligent and reasonable home device networking, and improve communication stability in home scenarios.

[0139] As an optional embodiment, the second determining module determines the specific method of the relevant function conditions corresponding to the current network configuration based on network requirements and device parameters, including:

[0140] Based on the pre-defined correspondence between requirements and constraints, the algorithm constraints corresponding to each network requirement are determined; optionally, the algorithm constraints include equipment performance constraints, equipment location constraints, and equipment software function constraints.

[0141] Based on clustering algorithms and algorithm constraints, all networking requirements are clustered to obtain a target networking requirement set. Optionally, the similarity between the algorithm constraints corresponding to any two networking requirements in the target networking requirement set is greater than a first similarity threshold, and the similarity between the algorithm constraints corresponding to any networking requirement in the target networking requirement set and the algorithm constraints of any networking requirement in a non-target networking requirement set is less than a second similarity threshold; the second similarity threshold is less than the first similarity threshold.

[0142] The objective function is to minimize the number of devices in the network topology scheme.

[0143] The constraints are defined as the algorithmic constraints that ensure the networking scheme meets all networking requirements in the target networking requirement set.

[0144] As can be seen, through the above optional embodiments, the algorithm constraints corresponding to each network requirement can be determined based on the correspondence between preset requirements and constraints. After clustering the optimal requirement set based on the similarity between the algorithm constraints, the objective function and constraints are determined based on the constraints in the set, so as to obtain the optimal networking scheme in subsequent calculations. This helps to fully combine the user's networking requirements and device parameters to determine the networking scheme, realize more intelligent and reasonable home device networking, and improve the communication stability in home scenarios.

[0145] As an optional embodiment, the calculation module, based on a dynamic programming algorithm, performs calculations on multiple home devices according to relevant function conditions and device parameters to obtain the specific method of the networking scheme corresponding to the networking operation, including:

[0146] Based on the spatial search algorithm, the networking schemes for multiple home devices are iteratively calculated according to the objective function and constraints;

[0147] In the iterative calculation, it is repeatedly determined whether the networking scheme meets the constraints and objective function until the optimal networking scheme is obtained and determined as the networking scheme corresponding to the networking operation.

[0148] As can be seen, through the above optional embodiments, the networking schemes corresponding to multiple home devices can be iteratively calculated based on the objective function and constraints according to the spatial search algorithm until the optimal networking scheme is obtained. This fully combines the user's networking needs and device parameters to determine the networking scheme, achieving more intelligent and reasonable home device networking and improving communication stability in home scenarios.

[0149] Example 3

[0150] Please see Figure 3 , Figure 3This is another home device networking system based on dynamic programming algorithm disclosed in the embodiments of the present invention. Figure 3 The described home appliance networking system based on dynamic programming algorithms is applied in a data processing system / data processing device / data processing server (wherein, the server includes a local processing server or a cloud processing server). For example... Figure 3 As shown, the home device networking system based on dynamic programming algorithm may include:

[0151] Memory 301 storing executable program code;

[0152] Processor 302 coupled to memory 301;

[0153] The processor 302 calls the executable program code stored in the memory 301 to execute the steps of the home device networking method based on dynamic programming algorithm described in Embodiment 1.

[0154] Example 4

[0155] This invention discloses a computer read storage medium that stores a computer program for electronic data interchange, wherein the computer program causes a computer to execute the steps of the home device networking method based on dynamic programming algorithm described in Embodiment 1.

[0156] Example 5

[0157] This invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps of the home device networking method based on dynamic programming algorithm described in Embodiment 1.

[0158] The foregoing has described specific embodiments of this specification; other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than those shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily have to follow the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0159] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0160] For ease of description, the above devices are described in terms of function, divided into various units. Of course, in implementing this specification, the functions of each unit can be implemented in one or more software and / or hardware components.

[0161] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the embodiments of this specification can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0162] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0163] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0164] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0165] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0166] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0167] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0168] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0169] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0170] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0171] Finally, it should be noted that the home device networking method and system based on dynamic programming algorithm disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A home appliance networking method based on dynamic programming algorithm, characterized in that, The method includes: In response to the target user's networking operation, obtain the device parameters of multiple home devices to be networked and the area parameters of the networking area; Based on the regional parameters and the networking operation, determine the networking requirements corresponding to the target user; Based on the network requirements and the device parameters, determine the relevant function conditions corresponding to the current network configuration, including: Based on the pre-defined correspondence between requirements and constraints, the algorithm constraints corresponding to each networking requirement are determined; the algorithm constraints include device performance constraints, device location constraints, and device software function constraints. Based on the clustering algorithm and the algorithm constraints, all the network requirements are clustered to obtain a target network requirement set; wherein, the similarity between the algorithm constraints corresponding to any two network requirements in the target network requirement set is greater than a first similarity threshold, and the similarity between the algorithm constraint corresponding to any network requirement in the target network requirement set and the algorithm constraint of any network requirement not in the target network requirement set is less than a second similarity threshold; the second similarity threshold is less than the first similarity threshold; The objective function is to minimize the number of devices in the network topology scheme. The limiting condition is determined to be the algorithm limiting condition that the networking scheme satisfies all the networking requirements in the target networking requirement set; Based on the dynamic programming algorithm, the network scheme corresponding to the networking operation is obtained by performing calculations on the multiple home devices according to the relevant function conditions and the device parameters.

2. The home appliance networking method based on dynamic programming algorithm according to claim 1, characterized in that, The networking operation includes the target user's selection and information input operations for at least one of the home devices; the device parameters include device location, device performance, device hardware model, and device software version.

3. The home appliance networking method based on dynamic programming algorithm according to claim 1, characterized in that, The regional parameters include the area, geographic location, and shape of the network region.

4. The home appliance networking method based on dynamic programming algorithm according to claim 3, characterized in that, The region parameters are obtained through the following steps: Obtain the device locations of the multiple home appliances; The device parameters and device locations of all the home appliances are input into a trained region shape prediction neural network to obtain the output region shape; The shape of the region is determined to be the shape of the network region; Calculate the shape region with the smallest area that contains the device locations of all the home appliances on its edges, using the shape of the region as a template. Calculate the geometric center position of the shape region, and determine the latitude and longitude position corresponding to the geometric center position as the geographic location of the network region; Calculate the area of ​​the shaped region and determine it as the area of ​​the network region.

5. The home appliance networking method based on dynamic programming algorithm according to claim 2, characterized in that, The step of determining the network requirements corresponding to the target user based on the regional parameters and the network operation includes: Based on the selection operation in the networking operation, obtain the device historical networking record of the home device corresponding to the selection operation; The networking purpose is selected from multiple networking records in the network area from the historical networking records of the device to obtain a set of historical networking purposes; The regional parameters are input into a trained regional networking demand prediction neural network to obtain multiple output regional networking demands. Calculate the intersection between the multiple regional networking requirements and the historical networking target set to obtain the multiple networking requirements corresponding to the target user.

6. The home appliance networking method based on dynamic programming algorithm according to claim 5, characterized in that, The networking requirements include communication optimization requirements, device synchronization requirements, device control requirements, function combination requirements, or access control requirements.

7. The home appliance networking method based on dynamic programming algorithm according to claim 1, characterized in that, The method based on dynamic programming algorithm, according to the relevant function conditions and the device parameters, calculates the network scheme corresponding to the network operation for the multiple home devices, including: Based on the spatial search algorithm, the networking schemes corresponding to the multiple home devices are iteratively calculated according to the objective function and the constraints. In the iterative calculation, it is repeatedly determined whether the networking scheme meets the constraints and the objective function until the optimal networking scheme is obtained and determined as the networking scheme corresponding to the networking operation.

8. A home appliance networking system based on dynamic programming algorithm, characterized in that, The system includes: The acquisition module is used to respond to the networking operation of the target user and acquire the device parameters of multiple home devices to be networked and the area parameters of the networking area. The first determining module is used to determine the networking requirements corresponding to the target user based on the regional parameters and the networking operation. The second determining module is used to determine the relevant function conditions corresponding to the current network configuration based on the network requirements and the device parameters, including: Based on the pre-defined correspondence between requirements and constraints, the algorithm constraints corresponding to each networking requirement are determined; the algorithm constraints include device performance constraints, device location constraints, and device software function constraints. Based on the clustering algorithm and the algorithm constraints, all the network requirements are clustered to obtain a target network requirement set; wherein, the similarity between the algorithm constraints corresponding to any two network requirements in the target network requirement set is greater than a first similarity threshold, and the similarity between the algorithm constraint corresponding to any network requirement in the target network requirement set and the algorithm constraint of any network requirement not in the target network requirement set is less than a second similarity threshold; the second similarity threshold is less than the first similarity threshold; The objective function is to minimize the number of devices in the network topology scheme. The limiting condition is determined to be the algorithm limiting condition that the networking scheme satisfies all the networking requirements in the target networking requirement set; The calculation module is used to perform calculations on the multiple home devices based on the dynamic programming algorithm, according to the relevant function conditions and the device parameters, to obtain the networking scheme corresponding to the networking operation.

9. A home appliance networking system based on dynamic programming algorithm, characterized in that, The system includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the home device networking method based on dynamic programming algorithm as described in any one of claims 1-7.

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