Internet-of-things platform system and interconnection method

Abstract

The invention discloses an Internet of Things platform system and an interconnection method, and relates to the technical field of urban Internet of Things collaboration, and the method comprises the steps: building an identified geographic coordinate adjacent grid domain; forming a spatial position interconnection topology of the bidirectional adjacent association identifier; and configuring an association response rule for the established geographical coordinate two-way proximity association identifier by the Internet of Things middle station. According to the invention, automatic construction of the standardized identifier and the adjacency relation of the equipment position is realized, and the space management precision of equipment access is improved; the expression capability of the spatial topological relation between the devices is enhanced, so that the response behaviors between the associated devices have the capabilities of condition screening, aging control and dynamic negotiation, and the intelligent level and the execution reliability of the interconnection process are improved.

Description

Technical Field

[0001] This invention relates to the field of urban IoT collaboration technology, and in particular to an IoT middleware system and interconnection method. Background Technology

[0002] Currently, with the rapid development of society and the accelerating urbanization process, the application of information technology in urban management is becoming increasingly widespread. Especially under the promotion of the concept of smart cities, the IoT middleware system, as a key hub connecting various IoT devices and urban management platforms, is becoming increasingly important. Against the backdrop of the continuous deepening of the construction of new smart cities, urban governance is accelerating its transformation towards digitalization, intelligence, and refinement. As the core support of the urban perception system, the IoT middleware system plays a key role in promoting the operation of the city.

[0003] Currently, various IoT devices in cities are often built and managed independently by different departments and systems, lacking unified access standards and data models. This results in diverse device data formats and incompatible protocols, making it difficult to achieve cross-system and cross-domain data fusion and collaborative applications. This creates data silos and fails to effectively support the centralized aggregation, unified management, and efficient utilization of city-level digital twin platforms for IoT sensing data across the entire region. Summary of the Invention

[0004] In view of the problems existing in the current IoT middleware system and interconnection method, this invention is proposed.

[0005] Therefore, the problem to be solved by this invention is: how to break down the data silos caused by heterogeneous devices and dispersed systems in urban Internet of Things, and realize automatic device discovery and dynamic interconnection across regions, levels and systems; and overcome the defects of existing IoT platforms, such as lack of intelligent association mechanism based on spatial location, static solidification of collaborative strategies and unidirectional closed response logic.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, embodiments of the present invention provide an interconnection method for an IoT middleware platform, which includes converting the geographic coordinates of the newly registered device into a unified dynamic spatial grid code when the IoT middleware platform performs device access, identifying the geographic coordinates with the dynamic spatial grid code, and establishing an adjacent grid domain for the identified geographic coordinates. Based on the geographic coordinate adjacency grid domain, a two-way proximity association identifier for geographic coordinates is established, forming a spatial location interconnection topology of the two-way proximity association identifier; The IoT platform configures association response rules for the established bidirectional proximity association identifier of geographic coordinates. These association response rules include: A condition-triggered mechanism based on event priority; A time-window-based mechanism for constraining collaborative effectiveness; A dynamic execution negotiation mechanism based on load feedback; Perform a triple-determination based on the associated response rules to complete the interconnection with the IoT middleware platform.

[0007] As a preferred embodiment of the interconnection method for IoT middleware described in this invention, the conversion to a unified dynamic spatial grid code includes, when the IoT middleware performs device access, obtaining the latitude and longitude values ​​in the coordinate system of the newly registered device and initiating a multi-level dynamic grid mapping process: First, the latitude and longitude values ​​are input into the regional equipment density judgment module. The regional equipment density judgment module dynamically selects the regional equipment density level based on the real-time access of the area where the equipment is located, and generates a non-uniform grid of the regional equipment density level. Next, the spatiotemporal coding is invoked to calculate the timestamps of the dynamically selected regional device density level and the non-uniform grid. The calculation result is dynamically adjusted according to the coding length of the regional device density level, and converted into a dynamic spatial grid code in string form. The spatiotemporal coding includes determining the spatiotemporal coding of the eight directions of the eight-neighbor index mapping table (east, south, west, north, northeast, southeast, southwest, and northwest) through a preloaded eight-neighbor index mapping table.

[0008] As a preferred embodiment of the interconnection method for IoT middleware described in this invention, the step of calculating the dynamically selected regional device density level and the timestamp of the non-uniform grid includes determining the grid level based on the regional device density level: in, Indicates grid hierarchy; From grid hierarchy The quantization calculation formula is as follows: (The formula is missing from the original text.) in, This represents the quantization of regional equipment density levels and timestamps. Represents operators, Indicates the coordinate code of the area device. This represents the current timestamp in milliseconds. Represents remainder operations; According to grid level Dynamically determine the base : Will Convert to String encoding for base: in, This represents the dynamic space grid encoding converted to string form. Represents number system conversion functions. Indicates the base of the number system. This represents the quantization of regional equipment density levels and timestamps.

[0009] As a preferred embodiment of the interconnection method for IoT middleware described in this invention, the step of identifying geographic coordinates includes generating an identifier for the geographic coordinate point to be identified according to the grid level to which the geographic coordinate point belongs and the corresponding grid coding rule, and establishing the adjacent grid domain of the identified geographic coordinates. The identified geographic coordinate adjacency grid domain includes direct adjacency and indirect adjacency. Direct adjacency refers to finding the dynamic spatial grid code that is directly adjacent to the identified geographic coordinate point. The indirect adjacency refers to finding the indirectly adjacent dynamic spatial grid codes of an identified geographic coordinate point through directly adjacent dynamic spatial grid codes. The process of finding dynamic spatial grid codes that are directly adjacent to geographic coordinate points includes generating direct adjacency codes when the dynamic spatial grid coding conditions are met. Once the geographic coordinates point has completed the dynamic spatial grid encoding generation, the dynamic spatial grid encoding is used as the central node to start the adjacency domain construction, and the grid level and two-dimensional index position are resolved based on the dynamic spatial grid encoding. When it is determined that a direct spatial association needs to be established, the eight-neighbor index mapping table is called to predefine the coordinate offsets in the eight directions of east, south, west, north, northeast, southeast, southwest, and northwest under the current projected coordinate system. The grid coordinates corresponding to the center node are superimposed with the offset of the eight-neighbor index mapping table to obtain the coordinates of eight adjacent positions. When the coordinates of the eight adjacent positions meet the division boundary of the current grid level, the coordinates of the eight adjacent positions are substituted into the hierarchical coordinate mapping function to calculate the corresponding dynamic spatial grid code in reverse, forming a direct adjacency code set. The dynamic spatial grid coding for finding indirect adjacency with geographic coordinate points includes analyzing the grid coordinates corresponding to the central node and detecting indirect adjacency relationships based on the completion of direct adjacency coding generation. Obtain the parent grid code of the grid coordinates corresponding to the center node, find the coordinates of the eight adjacent positions of the parent grid code in the previous level, expand them level by level, and filter out the codes that match the current level to form an indirect adjacency code set.

[0010] As a preferred embodiment of the interconnection method for IoT middleware described in this invention, the establishment of bidirectional proximity association identifiers for geographic coordinates includes performing multi-source coding fusion operation based on the formed direct adjacency coding set and indirect adjacency coding set, and performing deduplication processing when the codes generated by different paths are duplicated. Once all codes are integrated, they are divided into two logical subdomains: a nearest neighbor domain and a far neighbor domain. These two logical subdomains are then packaged into a structured composite geographic coordinate adjacency grid domain, stored in JSON Schema format. This JSON Schema storage includes dividing the composite geographic coordinate adjacency grid domain into independent fields, organized as an array. Each subdomain is treated as an independent field, and the encoding is organized in the form of an array to establish a two-way proximity association identifier for geographic coordinates.

[0011] As a preferred embodiment of the interconnection method for IoT middleware described in this invention, the step of performing a triple determination based on the association response rules includes executing the following step-by-step interactive determination process sequentially based on the composite geographic coordinate adjacency grid domain and the bidirectional proximity association identifier: The event priority-based condition triggering mechanism initiates priority-matching path filtering when an event occurs. The collaborative validity constraint mechanism based on time windows verifies timeliness and generates a validity period instruction package when entering the execution phase. The dynamic execution negotiation mechanism based on load feedback initiates timing adjustments for the execution phase when a coordination instruction is received.

[0012] As a preferred embodiment of the interconnection method for IoT middleware described in this invention, the path filtering for priority matching includes the IoT middleware first parsing the type label of the event and determining the priority level of the type label according to the event priority mapping; The verification of timeliness and generation of validity period instruction package includes loading the time validity window parameter set in the configuration stage of the path filtering after the path filtering that has passed the first level of judgment is filtered by the IoT platform. The dynamic execution negotiation mechanism based on load feedback includes establishing a collaborative execution end through path filtering based on the first two judgments and loading a time validity window parameter after path filtering, and dynamically executing the negotiation mechanism to complete the interconnection for the IoT platform.

[0013] Secondly, embodiments of the present invention provide an IoT middleware system, which includes: Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any step of the above-described interconnection method for IoT middleware.

[0014] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the above-described interconnection method for IoT middleware.

[0015] The beneficial effects of this invention are as follows: By converting the geographical coordinates of devices into a unified dynamic spatial grid code, this invention realizes the standardized identification of device locations and the automated construction of adjacency relationships, thereby improving the spatial management accuracy of device access; the composite geographical coordinate adjacency grid domain and bidirectional proximity association identifier established based on this code enhance the expressive ability of spatial topological relationships between devices; by introducing a triple judgment mechanism of event priority, time window and load feedback, the response behavior between associated devices has the ability to conditionally filter, control timeliness and dynamically negotiate, thereby improving the intelligence level and execution reliability of the interconnection process. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a flowchart of an IoT middleware system and interconnection method provided in an embodiment of the present invention.

[0017] Figure 2 This is a system diagram illustrating an IoT middleware system and interconnection method provided in an embodiment of the present invention.

[0018] Figure 3 This is a schematic diagram of the structure of a medium for an IoT middleware system and interconnection method provided in an embodiment of the present invention.

[0019] Figure 4 This is a schematic diagram of the structure of a computing device that provides an IoT middleware system and interconnection method according to an embodiment of the present invention. Detailed Implementation

[0020] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0021] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0023] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0024] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0025] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0026] Example 1 Reference Figures 1-4 This is the first embodiment of the present invention, which provides an interconnection method for an IoT middleware platform, including: S1: When the IoT platform performs device access, the geographic coordinates of the newly registered device are converted into a unified dynamic spatial grid code. The geographic coordinates are identified by the dynamic spatial grid code, and the adjacent grid domain of the identified geographic coordinates is established.

[0027] The conversion to a unified dynamic spatial grid encoding includes obtaining the latitude and longitude values ​​in the coordinate system of the newly registered device when the IoT platform executes device access, and initiating a multi-level dynamic grid mapping process: First, input the latitude and longitude values ​​into the regional equipment density judgment module. The regional equipment density judgment module dynamically selects the regional equipment density level based on the real-time access of the area where the equipment is located, and generates a non-uniform grid of the regional equipment density level. Next, the spatiotemporal coding is invoked to calculate the timestamps of the dynamically selected regional device density level and the non-uniform grid. The calculation result is dynamically adjusted according to the coding length of the regional device density level, and converted into a dynamic spatial grid code in string form. Spatiotemporal coding involves determining the spatiotemporal codes for the eight directions of the eight-neighbor index mapping table (east, south, west, north, northeast, southeast, southwest, and northwest) through a preloaded eight-neighbor index mapping table.

[0028] S1.1: Calculate the dynamically selected regional device density level with the timestamp of the non-uniform grid, including the grid level determined based on the regional device density level: in, Indicates grid hierarchy; From grid hierarchy The formula for quantizing the device density level and the timestamp of the non-uniform grid in the calculation area is as follows: in, This represents the quantization of regional equipment density levels and timestamps. Represents operators, Indicates the coordinate code of the area device. This represents the current timestamp in milliseconds. Represents remainder operations; According to grid level Dynamically determine the base : Will Convert to String encoding for base: in, This represents the dynamic space grid encoding converted to string form. Represents number system conversion functions. Indicates the base of the number system. This represents the quantization of regional equipment density levels and timestamps.

[0029] S1.2: Identifying geographic coordinates includes generating identifiers for geographic coordinate points that need to be identified according to the grid level to which the geographic coordinate points belong and the corresponding grid coding rules, and establishing the adjacent grid domains of the identified geographic coordinates. The identified geographic coordinate adjacency grid domain includes direct adjacency and indirect adjacency. Direct adjacency refers to finding the dynamic spatial grid code that is directly adjacent to the identified geographic coordinate point. Indirect adjacency refers to finding the indirectly adjacent dynamic spatial grid codes of an identified geographic coordinate point through directly adjacent dynamic spatial grid codes. Finding the dynamic spatial grid code directly adjacent to the geographic coordinate point includes generating a direct adjacency code when the dynamic spatial grid code conditions are met. Once the geographic coordinates point has completed the dynamic spatial grid encoding generation, the dynamic spatial grid encoding is used as the central node to start the adjacency domain construction, and the grid level and two-dimensional index position are resolved based on the dynamic spatial grid encoding. When it is determined that a direct spatial association needs to be established, the eight-neighbor index mapping table is called to predefine the coordinate offsets in the eight directions of east, south, west, north, northeast, southeast, southwest, and northwest under the current projected coordinate system. The grid coordinates corresponding to the center node are superimposed with the offset of the eight-neighbor index mapping table to obtain the coordinates of eight adjacent positions. When the coordinates of the eight adjacent positions meet the division boundary of the current grid level, the coordinates of the eight adjacent positions are substituted into the hierarchical coordinate mapping function to calculate the corresponding dynamic spatial grid code in reverse, forming a direct adjacency code set. Finding dynamic spatial grid codes that are indirectly adjacent to geographic coordinate points involves analyzing the grid coordinates corresponding to the central node and detecting indirect adjacency relationships after completing the generation of direct adjacency codes. Obtain the parent grid code of the grid coordinates corresponding to the center node, find the coordinates of the eight adjacent positions of the parent grid code in the previous level, expand them level by level, and filter out the codes that match the current level to form an indirect adjacency code set.

[0030] S2: Based on the geographic coordinate adjacency grid domain, establish a two-way proximity association identifier for geographic coordinates, forming a spatial location interconnection topology of the two-way proximity association identifier.

[0031] Establishing a bidirectional proximity association identifier for geographic coordinates involves performing multi-source coding fusion based on the formed direct adjacency coding set and indirect adjacency coding set, and deduplicating codes generated by different paths when duplicates are identified. Once all codes are integrated, they are divided into two logical subdomains: a nearest neighbor domain and a far neighbor domain. These two subdomains are then packaged into a structured composite geographic coordinate adjacency grid domain, stored in JSON Schema format. This JSON Schema storage includes dividing the composite geographic coordinate adjacency grid domain into independent fields, organized as an array. Each subdomain is treated as an independent field, and the encoding is organized in the form of an array to establish a two-way proximity association identifier for geographic coordinates.

[0032] S3: The IoT platform configures association response rules for the established bidirectional proximity association identifier of geographic coordinates. The association response rules include: A condition-triggered mechanism based on event priority; A time-window-based mechanism for constraining collaborative effectiveness; A dynamic execution negotiation mechanism based on load feedback; Perform a triple-determination based on the associated response rules to complete the interconnection with the IoT middleware platform.

[0033] The process of performing a triple determination based on the associated response rules includes using a composite geographic coordinate adjacency grid domain and a bidirectional proximity association identifier, and then performing the following step-by-step interactive determination process: The event priority-based condition triggering mechanism initiates priority-matching path filtering when an event occurs. The collaborative validity constraint mechanism based on time windows verifies timeliness and generates a validity period instruction package when entering the execution phase. The dynamic execution negotiation mechanism based on load feedback initiates timing adjustments for the execution phase when a coordination instruction is received.

[0034] Furthermore, the path filtering for priority matching involves the IoT platform first parsing the event type label and determining the priority level of the type label based on the event priority mapping; Verifying timeliness and generating validity period instruction packages includes loading the time validity window parameters set in the configuration phase of the path filtering after the IoT platform filters the paths that have passed the first level of judgment for priority matching. The dynamic execution negotiation mechanism based on load feedback includes path filtering through the first two judgments and the time validity window parameter loaded after path filtering, establishing a collaborative execution end, and dynamically executing the negotiation mechanism to complete the interconnection for the IoT middleware platform.

[0035] Furthermore, the IoT platform configures associated response rules for the established bidirectional proximity association identifiers based on geographic coordinates, including a conditional triggering mechanism based on event priority, a collaborative effectiveness constraint mechanism based on time windows, and a dynamic execution negotiation mechanism based on load feedback. After completing the construction of the bidirectional proximity association identifiers, the platform initiates a multi-dimensional response rule binding process. For each pair of devices with spatial proximity (the main trigger end and the collaborative execution end), the platform issues a capability exploration command to obtain the event types that the main device can report and their priority classifications. Based on the device's executable action capabilities and resource consumption thresholds, a collaborative response rule package containing the three mechanisms is generated and synchronized to the local devices on both ends.

[0036] When the master device reports an event, the middleware first performs the first judgment: parsing the event type and determining the priority, combined with the device's composite geographic coordinate adjacency grid domain structure; if it is a high-priority event, all associated devices in the nearest and far-reaching domains are activated; if it is a general priority event, only the nearest-neighbor devices are activated, achieving dynamic shrinkage of the response range; then it enters the second judgment: loading preset time validity window parameters for the selected collaborative execution terminals, embedding the start timestamp and expiration deadline in the generated cross-domain collaborative message packet, and pushing it to the target device, where its edge collaborative agent verifies the receiving time. If the timeout period expires, execution will be rejected and a status code will be returned. For devices that pass the timeout verification, a third judgment is initiated: the edge agent monitors the local system load in real time. If the load exceeds the safety threshold, it will send a delay suggestion or refuse to execute the negotiation message to the middle platform. After receiving the message, the middle platform will trigger a renegotiation process, forwarding the delay request to the master device for confirmation. Based on the response of the master device, it will decide whether to continue the delayed execution or terminate the collaboration. If the load is normal, the action will be executed directly and the execution feedback will be returned. This completes the closed-loop interconnection response based on the four-dimensional linkage of spatial topology, event level, time constraints and device status.

[0037] Preferably, the thresholds include multi-dimensional preset judgment boundaries, used to dynamically control the triggering and execution behavior of device collaboration during the triple judgment process. Specifically, in the event priority judgment stage, a priority trigger threshold is set to distinguish whether to activate remote domain device responses. For example, when the event priority score is higher than 7 (out of 10), it is considered high priority, triggering a full-range response; if it is lower than or equal to 7, only nearby domain devices are activated. In the time validity constraint stage, a time window threshold is set, i.e., the maximum allowable delay from event occurrence to instruction execution, configured as 5 seconds, 8 seconds, or 12 seconds depending on the application scenario. Exceeding this time range is considered a failure. In the load feedback negotiation stage, system resource security thresholds are defined, including CPU utilization not exceeding 75%, memory utilization not exceeding 80%, and network IO latency less than 200ms. When the collaborative execution end detects any indicator exceeding the corresponding threshold, it is judged as a high-load state, triggering a dynamic negotiation mechanism. The above thresholds are dynamically configured by the IoT platform according to city area, device type, and business scenario, and support remote updates through the policy center to ensure that collaborative decisions conform to the carrying capacity of the actual operating environment.

[0038] In a preferred embodiment, an IoT middleware system includes a geographic coordinate identification module, which converts the geographic coordinates of newly registered devices into a unified dynamic spatial grid code when the IoT middleware executes device access, identifies the geographic coordinates with the dynamic spatial grid code, and establishes an adjacent grid domain for the identified geographic coordinates. The geographic coordinate bidirectional proximity association identification module establishes a geographic coordinate bidirectional proximity association identification based on the geographic coordinate adjacency grid domain, forming a spatial location interconnection topology of the bidirectional proximity association identification; The associated response rule execution triple judgment module configures associated response rules for the established bidirectional proximity association identifier of geographic coordinates in the IoT platform, and performs triple judgment according to the associated response rules to complete the interconnection to the IoT platform; The regional device density determination module dynamically selects the regional device density level based on the real-time access of the area where the device is located, and generates a non-uniform grid for the regional device density level.

[0039] The above-mentioned unit modules can be embedded in the processor of the computer device in hardware form or independent of it, or they can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of the above modules.

[0040] In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, memory, a communication interface, a display screen, and an input device connected via a system bus. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The communication interface of the computer device is used for wired or wireless communication with external terminals. Wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen of the computer device may be an LCD screen or an e-ink display screen. The input device of the computer device may be a touch layer covering the display screen, or buttons, a trackball, or a touchpad located on the casing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0041] In summary, this invention converts device geographic coordinates into a unified dynamic spatial grid code, thereby achieving standardized identification of device locations and automated construction of adjacency relationships, improving the spatial management accuracy of device access. The composite geographic coordinate adjacency grid domain and bidirectional proximity association identifier established based on this code enhance the expressive ability of spatial topological relationships between devices. By introducing a triple judgment mechanism of event priority, time window, and load feedback, the response behavior between associated devices is equipped with conditional filtering, timeliness control, and dynamic negotiation capabilities, improving the intelligence level and execution reliability of the interconnection process.

[0042] Example 2 Reference Figures 1-4 This is the second embodiment of the present invention, which provides an IoT middleware system and interconnection method. In order to verify the beneficial effects of the present invention, a simulation experiment is conducted for scientific demonstration.

[0043] In the construction of the IoT platform in the smart city demonstration zone, the interconnection method of this invention was adopted to solve the problems of slow response and low linkage rate between streetlights, cameras and environmental monitoring equipment across departments. 1,200 IoT devices were deployed in the area. Due to the lack of a unified spatial index, the original system had an average linkage response time of 12.8 seconds and a cross-system collaboration success rate of only 63%.

[0044] After implementing the present invention, the WGS84 coordinates of all devices are first input into the regional device density judgment module. Based on the device density in urban areas, the area is dynamically divided into three grid layers (0.0005°×0.0005° for high-density areas and 0.001°×0.001° for suburban areas), generating a dynamic spatial grid code with a timestamp. The code length adaptively adjusts between 8 and 14 bits depending on the layer. Based on this, a composite geographic coordinate adjacency grid domain is constructed, with an average of 12.6 bidirectional proximity association identifiers established for each device. In a nighttime sudden flooding scenario test, when a monitoring point triggers a high-priority alarm, the triple judgment mechanism is activated: The first layer activates eight related devices in the vicinity (including three streetlights and four cameras) based on priority. The second layer verifies the time window (set to 10 seconds), with seven of the eight devices receiving the instruction within the validity period. In the third layer of load negotiation, one camera reported a 3-second delay in executing the request due to CPU utilization reaching 82% (exceeding the 75% threshold). After confirmation by the master device, the execution plan was adjusted. Ultimately, the device linkage response time was shortened to 3.2 seconds, and the collaborative execution success rate reached 96.7%. During 30 days of continuous operation testing, the efficiency of automatic cross-system device association establishment improved by 4.3 times, significantly improving the level of intelligence in urban operation management.

[0045] The comparison between the present invention and the prior art is shown in Table 1 below: Table 1. Comparison of the present invention with the prior art Comparison items Existing technology Technical solution of the present invention Equipment space identification method The use of raw latitude and longitude coordinates or static area coding lacks a unified coding standard. Dynamic spatial grid coding is adopted, and the grid granularity is adaptively adjusted based on device density to achieve unified and scalable spatial identification. Methods for establishing connections between devices Relying on manual configuration or fixed topology, it cannot automatically discover nearby devices. Based on the adjacency grid domain, bidirectional proximity association identifiers are automatically constructed, supporting intelligent discovery of direct and indirect adjacency relationships. Collaborative Response Mechanism Single trigger or fixed rule linkage, lacking multi-dimensional judgment capability. A triple-determination mechanism is adopted: event priority filtering, time window constraints, and load feedback negotiation, to improve response intelligence and reliability. Cross-system collaboration efficiency Low collaboration success rate, long average response time (>10 seconds), and susceptible to equipment status. The actual collaborative success rate has been improved to 96.7%, the average response time has been shortened to 3.2 seconds, and dynamic adjustment of execution timing is supported. System scalability and adaptability Difficult to adapt to changes in equipment density and new application scenarios It supports non-uniform grid partitioning, variable base encoding, and JSON structured storage, and has high scalability and adaptability to various scenarios. Table 1 shows that the automatic and intelligent construction of spatial relationships between devices is achieved through dynamic spatial grid coding and bidirectional proximity association mechanism. Compared with existing technologies, it has significantly improved the accuracy, real-time performance and system adaptability of collaborative response, and effectively solved the problems of low efficiency and rigid configuration in cross-system linkage in city-level Internet of Things.

[0046] After introducing the method and system of exemplary embodiments of the present invention, the following references are made. Figure 3 A computer-readable storage medium according to exemplary embodiments of the present invention will be described, please refer to... Figure 3The computer-readable storage medium shown is an optical disc 30, on which a computer program (i.e., a program product) is stored. When the computer program is run by a processor, it implements the steps described in the above method implementation. For example, when the IoT platform executes device access, the geographic coordinates of the newly registered device are converted into a unified dynamic spatial grid code. The geographic coordinates are identified by the dynamic spatial grid code, and an adjacent grid domain of the identified geographic coordinates is established. Based on the adjacent grid domain of the geographic coordinates, a bidirectional proximity association identifier of the geographic coordinates is established, forming a spatial location interconnection topology of the bidirectional proximity association identifier. The IoT platform configures association response rules for the established bidirectional proximity association identifier of the geographic coordinates. The association response rules include: a condition triggering mechanism based on event priority; a collaborative effectiveness constraint mechanism based on time window; a dynamic execution negotiation mechanism based on load feedback; and a triple judgment is performed according to the association response rules to complete the interconnection to the IoT platform.

[0047] It should be noted that examples of computer-readable storage media may also 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 optical and magnetic storage media, which will not be elaborated here.

[0048] After introducing the methods and media of exemplary embodiments of the present invention, the following references are made. Figure 4 A computational device for adaptive recovery of low-voltage power grid self-healing control according to an exemplary embodiment of the present invention.

[0049] Figure 4 A block diagram is shown of an exemplary computing device 40 suitable for implementing embodiments of the present invention. The computing device 40 may be a computer system or a server. Figure 4 The computing device 40 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0050] like Figure 4 As shown, the components of computing device 40 may include, but are not limited to: one or more processors or processing units 401, system memory 402, and bus 403 connecting different system components (including system memory 402 and processing unit 401).

[0051] The computing device 40 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computing device 40, including volatile and non-volatile media, and removable and non-removable media.

[0052] System memory 402 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 4021 and / or cache memory 4022. Computing device 40 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, ROM 4023 may be used to read and write non-removable, non-volatile magnetic media (…). Figure 4 (Not shown in the image, usually referred to as "hard drive"). Although not shown in... Figure 4 The diagram illustrates that disk drives for reading and writing to removable non-volatile disks (e.g., "floppy disks") and optical disc drives for reading and writing to removable non-volatile optical discs (e.g., CD-ROMs, DVD-ROMs, or other optical media) can be provided. In these cases, each drive can be connected to bus 403 via one or more data media interfaces. System memory 402 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0053] A program / utility 4025 having a set (at least one) of program modules 4024 may be stored, for example, in system memory 402, and such program modules 4024 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment. Program modules 4024 typically perform the functions and / or methods described in the embodiments of the present invention.

[0054] The computing device 40 can also communicate with one or more external devices 404 (such as a keyboard, pointing device, display, etc.). This communication can be performed via the input / output (I / O) interface 405. Furthermore, the computing device 40 can also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 406. Figure 4 As shown, network adapter 406 communicates with other modules of computing device 40 (such as processing unit 401) via bus 403. It should be understood that, although... Figure 4 As not shown, it can be used in conjunction with computing device 40 with other hardware and / or software modules.

[0055] The processing unit 401 executes various functional applications and data processing by running programs stored in the system memory 402. For example, when the IoT platform performs device access, it converts the geographic coordinates of the newly registered device into a unified dynamic spatial grid code, identifies the geographic coordinates using the dynamic spatial grid code, and establishes an adjacent grid domain for the identified geographic coordinates. Based on the adjacent grid domain, it establishes a bidirectional proximity association identifier for the geographic coordinates, forming a spatial location interconnection topology for the bidirectional proximity association identifier. The IoT platform configures association response rules for the established bidirectional proximity association identifier for the geographic coordinates. The association response rules include: a condition triggering mechanism based on event priority; a collaborative effectiveness constraint mechanism based on time window; and a dynamic execution negotiation mechanism based on load feedback. The system performs a triple judgment according to the association response rules to complete the interconnection to the IoT platform.

[0056] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0057] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interface; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0058] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0059] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0060] If the functionality is implemented as a software functional unit and sold or used as an independent product, it can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0061] Finally, it should be noted that the above embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, 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, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0062] Furthermore, although the operations of the method of the present invention are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0063] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An interconnection method for an Internet-of-Things middle station, characterized in that: Comprising, In the implementation of equipment access in the Internet of Things platform, the geographical coordinates of newly registered equipment are converted into a unified dynamic spatial grid code, and the geographical coordinates are identified by the dynamic spatial grid code, and a neighboring grid domain of the identified geographical coordinates is established; Based on the neighboring grid domain of the geographical coordinates, a bidirectional adjacent correlation identifier of the geographical coordinates is established, and a spatial position interconnection topology of the bidirectional adjacent correlation identifier is formed; The Internet of Things platform configures a correlation response rule for the established bidirectional adjacent correlation identifier of the geographical coordinates, and the correlation response rule comprises: a condition triggering mechanism based on event priority; a collaborative effectiveness constraint mechanism based on a time window; a dynamic execution negotiation mechanism based on load feedback; According to the correlation response rule, a triple judgment is performed to complete the interconnection of the Internet of Things platform. 2.The method of claim 1, wherein: The conversion into a unified dynamic spatial grid code comprises, in the implementation of equipment access in the Internet of Things platform, acquiring longitude and latitude values in the coordinate system of new registered equipment, and starting a multi-level dynamic grid mapping process: Firstly, the longitude and latitude values are input into a regional equipment density judgment module, and the regional equipment density judgment module dynamically selects a regional equipment density level according to real-time access of equipment in a region, and generates a non-uniform grid of the regional equipment density level; Secondly, a space-time code is called to operate the dynamically selected regional equipment density level and the time stamp of the non-uniform grid, and the operation result is dynamically adjusted in base according to the coding length of the regional equipment density level, and is converted into a dynamic spatial grid code in the form of a string; The space-time code comprises determining the space-time codes of the east, south, west, north, northeast, southeast, southwest, and northwest eight directions of the eight-neighborhood index mapping table through the preloaded eight-neighborhood index mapping table. 3.The method of claim 2, wherein: The operation of the dynamically selected regional equipment density level and the time stamp of the non-uniform grid comprises determining the grid level according to the regional equipment density level: wherein represents the grid level; from the grid hierarchy Quantize the computed region device density level with the timestamp of the non-uniform grid, the formula of the quantization computation is: wherein, represents quantization of the area device density level and the timestamp, represents an operator, represents a coordinate encoding of the area device, represents a millisecond value of the current timestamp, represents a remainder operation; According to grid hierarchy Dynamically determining radix base : Converting to a string encoding in base wherein, represents a dynamic spatial mesh encoding converted into a string form, represents a base conversion function, represents a base of the base conversion function, represents quantization of the area device density level and the time stamp. 4.The method of claim 3, wherein: The identification of the geographical coordinates comprises, for a geographical coordinate point to be identified, generating an identifier according to the grid level and the corresponding grid coding rule to which the geographical coordinate point belongs, and establishing a neighboring grid domain of the identified geographical coordinates; The neighboring grid domain of the identified geographical coordinates comprises direct adjacency and indirect adjacency, the direct adjacency refers to finding the dynamic spatial grid code directly adjacent to the identified geographical coordinate point; The indirect adjacency refers to finding the dynamic spatial grid code indirectly adjacent to the identified geographical coordinate point through the directly adjacent dynamic spatial grid code; The finding of the dynamic spatial grid code directly adjacent to the geographical coordinate point comprises generating a direct adjacency code when the dynamic spatial grid code condition is met; After the dynamic spatial grid code of the geographical coordinate point is generated, the dynamic spatial grid code is taken as a center node to start the construction of an adjacent domain, and the grid level and two-dimensional index position where the dynamic spatial grid code is located are parsed; When it is determined that direct spatial correlation needs to be established, the eight-neighborhood index mapping table is called to predefine the coordinate offset of the east, south, west, north, northeast, southeast, southwest, and northwest eight directions in the current projection coordinate system; The grid coordinates corresponding to the center node are sequentially superimposed with the offset of the eight-neighborhood index mapping table to obtain the coordinates of eight adjacent positions. When the coordinates of the eight adjacent positions meet the division boundary of the current grid level, the coordinates of the eight adjacent positions are substituted into the hierarchical coordinate mapping function to reversely calculate the corresponding dynamic spatial grid code to form a direct adjacency code set; The finding of the dynamic spatial grid code indirectly adjacent to the geographic coordinate point comprises, on the basis of the generation of the direct adjacency code, analyzing the grid coordinates corresponding to the center node to detect the indirect adjacency relationship; The upper parent grid code of the grid coordinates corresponding to the center node is obtained, the coordinates of eight adjacent positions of the upper parent grid code in the previous level are found, and the eight adjacent positions are sequentially unfolded level by level downward, and the codes matched with the current level are screened out to form an indirect adjacency code set. 5.The method of claim 4, wherein: The establishment of the bidirectional adjacent correlation identifier of the geographic coordinate comprises, on the basis of the formed direct adjacency code set and indirect adjacency code set, performing a multi-source code fusion operation. When the codes generated by different paths exist repetition, the codes are processed to remove the repetition. When all the codes are integrated, the integrated codes are divided into two logical subdomains, the two logical subdomains comprise a near-neighbor domain and a far-cooperative domain, the two logical subdomains are packaged to generate a structured composite geographic coordinate adjacency grid domain, and the structured composite geographic coordinate adjacency grid domain is stored in a JSON Schema format. The JSON Schema format storage comprises dividing the composite geographic coordinate adjacency grid domain into independent fields and organizing the fields in an array form. Each subdomain is an independent field, and the codes are organized in an array form to establish the bidirectional adjacent correlation identifier of the geographic coordinate. 6.The method of claim 5, wherein: The threefold judgment according to the correlation response rule comprises sequentially performing the following step-by-step interactive judgment process based on the composite geographic coordinate adjacency grid domain and the bidirectional adjacent correlation identifier: A condition triggering mechanism based on event priority. When an event occurs, the priority matching path screening is started. A collaborative effectiveness constraint mechanism based on a time window. When entering the execution stage, the time effectiveness is verified and an effective period instruction package is generated. A dynamic execution negotiation mechanism based on load feedback. When a collaborative instruction is received, the timing adjustment of the execution stage is started. 7.The method of claim 6, wherein: The starting of the priority matching path screening comprises that the Internet of Things middle station first analyzes the type label of the event, and determines the priority level of the type label according to the event priority mapping; The verification of the time effectiveness and the generation of the effective period instruction package comprise that the Internet of Things middle station loads the time effectiveness window parameter set in the configuration stage by the priority matching path screening of the first fold judgment; The dynamic execution negotiation mechanism based on load feedback comprises that the collaborative execution end is established based on the path screening of the first two fold judgments and the time effectiveness window parameter loaded after the path screening, the dynamic execution negotiation mechanism is established, and the Internet of Things middle station is connected.

8. An IOT middle platform system based on the IOT middle platform oriented interconnection method of any one of claims 1-7, characterized in that: The geographic coordinate identification module converts the geographic coordinates of a newly registered device into a unified dynamic spatial grid code when the device accesses the Internet of Things middle station, identifies the geographic coordinates by the dynamic spatial grid code, and establishes an identified geographic coordinate adjacency grid domain. ​ The geographical coordinate bidirectional adjacent correlation identification module is based on a geographical coordinate adjacent grid domain, establishes a bidirectional adjacent correlation identification of geographical coordinates, and forms a spatial position interconnection topology of the bidirectional adjacent correlation identification. The correlation response rule execution triple determination module configures a correlation response rule for the geographical coordinate bidirectional adjacent correlation identification established by the IOT middle platform, performs triple determination according to the correlation response rule, and completes the interconnection facing the IOT middle platform. The regional device density judgment module dynamically selects a regional device density level according to real-time access of devices in a region, and generates a non-uniform grid of the regional device density level. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is characterized in that: The processor executes the computer program to realize the steps of the interconnection method facing the IOT middle platform in any one of claims 1-7.

10. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program is executed by the processor to realize the steps of the interconnection method facing the IOT middle platform in any one of claims 1-7.

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