Data interaction method and system for concentrator and collector

Abstract

The invention provides a data interaction method and a data interaction system for a concentrator and a collector, which are applied to the technical field of data interaction. And the protocol adaptation layer dynamically selects a protocol conversion module to realize data protocol conversion based on the protocol type of the collector, the equipment ID and the network environment of the system and transmits the converted data to the concentrator. And the concentrator unpacks, analyzes, stores or decides the received data. After the concentrator processes the data, generated feedback data are returned to the corresponding collector through the protocol adaptation layer, and closed-loop control is completed. Based on a real-time data analysis result of the concentrator, the protocol adaptation layer automatically adjusts a protocol adaptation mode, a data compression strategy or a load balancing mechanism. Through multi-layer protocol discovery and dynamic adaptation, intelligent data flow optimization and real-time conversion, and distributed intelligent decision and autonomous adjustment processes, the data transmission efficiency is improved, the flexibility of the system is enhanced, and the data security is ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of data interaction, and in particular relates to a data interaction method and system between a concentrator and a collector. Background Art

[0002] With the development of the Internet of Things, data interaction between concentrators and collectors has become a vital part of the Internet of Things system. Traditional data interaction methods usually rely on fixed protocols and transmission methods, which leads to protocol incompatibility between different devices and reduces the flexibility and efficiency of the system.

[0003] The existing technology lacks a dynamic adaptation mechanism and cannot be flexibly adjusted according to the network environment, device status and data requirements, resulting in problems such as network bandwidth waste and transmission delay. In addition, data security and reliability issues are also technical problems that need to be solved urgently in the current system.

[0004] Therefore, how to design a data interaction method that can adaptively select protocols, intelligently optimize data flows, and ensure security has become the key to solving these technical problems. Summary of the invention

[0005] In view of the above-mentioned problems in the prior art, the purpose of the present invention is to provide a data interaction method between a concentrator and a collector, which improves data transmission efficiency, enhances system flexibility, and ensures data security through multi-layer protocol discovery and dynamic adaptation, intelligent data flow optimization and real-time conversion, distributed intelligent decision-making and autonomous adjustment process.

[0006] A data interaction method between a concentrator and a collector comprises the following steps:

[0007] Step 1: Multi-layer protocol discovery and dynamic adaptation: Based on the protocol type and network environment supported by the collector, the protocol adapter module is automatically selected for protocol adaptation, and the data collected by the collector is converted into a data format supported by the concentrator through protocol conversion;

[0008] Step 2: Intelligent data flow optimization and real-time conversion: The data collected by the collector forms a data flow, and the data flow rate and data conversion strategy are dynamically adjusted according to the network load and data flow priority;

[0009] Step 3: Distributed intelligent decision-making and autonomous adjustment: The protocol adaptation layer dynamically adjusts according to the feedback information of each collector and makes intelligent selections among multiple protocol conversion modules and communication protocols;

[0010] Step 4: Blockchain and end-to-end security authentication: Encrypted transmission is performed during data interaction, and the data packet and the generated hash value are stored in the blockchain;

[0011] Step 5: Data aggregation and centralized processing: The concentrator aggregates and centrally processes the received data;

[0012] Step 6: System optimization and feedback adjustment: The system continuously updates global and local decisions based on the feedback mechanism.

[0013] Preferably, the specific process of step 1, multi-layer protocol discovery and dynamic adaptation is as follows: the collector sends a list of supported protocols to the protocol adaptation layer via broadcast, and the protocol adaptation layer dynamically selects a matching protocol adaptation module for data conversion based on the protocol list sent by the protocol collector.

[0014] Preferably, the selection formula of the protocol adaptation module is: adapt =Protocol_Adaptation(P device , N status ), where M adapt is the selected protocol adapter module, P device N is the protocol type of the collector. status It is the current network status, which includes network bandwidth and network delay.

[0015] Preferably, the specific process of step 2, intelligent data flow optimization and real-time conversion is as follows:

[0016] Under normal circumstances, after the protocol adaptation layer receives the data sent by the collector, it first removes the useless data fields, then incrementally updates the data stream, and only converts the incremental data and sends it to the concentrator:

[0017] In special cases, when there is bandwidth limitation or delay between the collector and the protocol adaptation layer, the data stream is cached by the edge computing device, which filters and compresses the cached data and waits for the network to recover. The protocol adaptation layer converts the data processed by the edge computing device and sends it to the concentrator:

[0018] The data conversion formula is: D converted =Format_Conversion(P device , D raw ), where P device D is the collector protocol; raw is the original data.

[0019] Preferably, step three, the process of distributed intelligent decision-making and autonomous adjustment, includes the following steps:

[0020] Distributed data perception: Each collector collects its own status information in real time, including data load and battery status, and reports it to the protocol adaptation layer;

[0021] Establish a global model: Based on the local data collected by each collector, establish a global environment model to reflect the status of the current network and each collector in real time;

[0022] Global intelligent decision-making: The protocol adaptation layer makes global intelligent decisions and local optimization decisions through intelligent algorithms based on the global model and local data collected by each collector;

[0023] The global intelligent decision is used to dynamically optimize the transmission path of the data flow, adjust the transmission protocol according to the network conditions, and perform load balancing among the collectors; the local optimization decision is used to drive each collector to adjust the data collection frequency, modify the data transmission method, and adjust the transmission rate.

[0024] Preferably, the intelligent algorithm formula is: D decision =Decision(M env , P local , A action ), D decision For the decision made, M env is the environmental model, P local is the local device parameter, A action Actions to be performed, including traffic shaping and protocol switching;

[0025] Among them, M env =f(D sensor , N status , E history ), D sensor is the local data collected by the collector, N status is the network status, including bandwidth, delay, and packet loss rate, E history For historical environmental data.

[0026] Preferably, the specific process of blockchain and end-to-end security authentication is as follows:

[0027] The protocol adaptation layer generates a unique hash value for each data packet during each data interaction, and stores each data packet and its hash value in a decentralized blockchain network;

[0028] After receiving the data, the concentrator first calculates the hash value of the received data and compares it with the data packet and its hash value stored in the blockchain for verification.

[0029] Preferably, the process of step five, data aggregation and centralized processing is as follows: after receiving the data, the concentrator parses, integrates and stores the data, performs deep learning and predictive analysis on the data, and performs real-time analysis on the data.

[0030] Preferably, the process of step six, system optimization and feedback adjustment is as follows:

[0031] After the concentrator processes the data, it returns the generated feedback data to the corresponding collector through the protocol adaptation layer to complete the closed-loop control. In the closed-loop control process, the global and local decisions are continuously updated through the feedback mechanism to optimize the environmental model. updated =Feedback(M env , A adjusted ), M updated is the updated environment model, M env is the environmental model, A adjusted For the adjusted action.

[0032] The second object of the present invention is to provide a data interaction system between a concentrator and a collector, which is used to implement the above-mentioned data interaction method between the concentrator and the collector, including:

[0033] Collector layer: It is composed of different types of collectors, each of which uses a unique communication protocol and data format;

[0034] Protocol Adaptation Layer: Located between the collector layer and the concentrator layer, it is used for dynamic protocol discovery, adaptation, conversion, and data optimization;

[0035] Concentrator layer: includes concentrators, which are used to aggregate, analyze and transmit the data transmitted by each collector.

[0036] The beneficial effects of the present invention are as follows: the data interaction method and system between the concentrator and the collector make full use of technologies such as multi-layer protocol discovery and dynamic adaptation, intelligent data flow optimization and real-time conversion, distributed intelligent decision-making and autonomous adjustment, and improve data interaction efficiency through distributed intelligent algorithms and autonomous adjustment mechanisms, thereby ensuring efficient, stable and safe operation of the system.

[0037] Through the intelligent protocol discovery and adaptation mechanism, the system can dynamically select and switch the most appropriate protocol according to the actual collector support, network environment and the characteristics of the transmitted data, which can significantly improve the interoperability of various modules in the system and reduce protocol incompatibility.

[0038] By intelligently analyzing the priority and transmission requirements of data streams, dynamically selecting compression algorithms and data format conversion, bandwidth pressure is reduced and data transmission efficiency is improved, ensuring a reasonable distinction between real-time data and non-real-time data.

[0039] Through distributed intelligent algorithms, global and local decisions are constantly adjusted to achieve adaptive global optimization, which can respond to network changes in real time and improve the robustness and flexibility of the system. In addition, through continuous performance evaluation and feedback adjustment, the entire system is intelligent and continuously learned, ensuring the long-term and efficient operation of the system in complex environments.

[0040] In addition, the introduction of blockchain technology ensures the security and immutability of data, enhances the trust of the system, and protects sensitive data between devices from attacks and leaks. Through data aggregation and centralized processing, the system can effectively integrate heterogeneous data from different devices, and conduct unified analysis and processing, improving data utilization and decision-making efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0042] Figure 1 is a flow chart of the method of the present invention;

[0043] Figure 2 It is a system structure block diagram of the present invention. DETAILED DESCRIPTION

[0044] Embodiment 1

[0045] like Figure 1 As shown, a data interaction method between a concentrator and a collector includes the following steps:

[0046] Step 1: Multi-layer protocol discovery and dynamic adaptation:

[0047] Based on the protocol type supported by the collector and the system's network environment, the appropriate protocol adapter module is automatically selected for protocol adaptation, and the data collected by the collector is converted into a data format supported by the concentrator through protocol conversion.

[0048] The collector sends a list of supported protocols to the protocol adaptation layer through broadcasting. The protocol adaptation layer dynamically selects a matching protocol adaptation module for data conversion based on the protocol list sent by the protocol collector. The protocol adaptation module automatically selects the optimized data transmission protocol based on the current network status.

[0049] The selection formula of the protocol adapter module is: adapt =Protocol_Adaptation(P device , N status ), where M adapt is the selected protocol adapter module, P device N is the protocol type of the collector. status The current network status includes bandwidth, delay, etc.

[0050] Step 2: Intelligent data flow optimization and real-time conversion

[0051] The data collected by the collector forms a data stream, and the data stream rate and data conversion strategy are dynamically adjusted according to the network load and data stream priority. During real-time data transmission, different protocol adapter modules are selected for protocol conversion to ensure a smooth transmission process.

[0052] Under normal circumstances, after receiving the data sent by the collector, the protocol adaptation layer first removes the useless data fields, then incrementally updates the data stream, and only converts the incremental data before sending it to the concentrator.

[0053] For real-time data streams, streaming processing technology is used to transform and send data. Data is incrementally updated during transmission and is transmitted only when the incremental data reaches the threshold, which can reduce the network burden. In addition, each time the data changes, the protocol adaptation layer performs incremental compression on the data to reduce the transmission of redundant parts and the amount of data transmitted.

[0054] In special cases, when there is bandwidth limitation or delay between the collector and the protocol adaptation layer, the data stream is cached by the edge computing device, which filters and compresses the cached data and waits for the network to recover. The protocol adaptation layer converts the data processed by the edge computing device and sends it to the concentrator.

[0055] The data conversion formula is: D converted =Format_Conversion(P device , D raw ), where P device D is the collector protocol; raw is the original data.

[0056] Step 3: Distributed intelligent decision-making and autonomous adjustment

[0057] The protocol adaptation layer dynamically adjusts according to the feedback information of each collector and makes intelligent selections between multiple protocol conversion modules and communication protocols. The feedback information of the collector includes the network status, protocol support capability, data processing status, etc. of the collector.

[0058] The load balancing formula is:

[0059]

[0060] , where L balance is the average load, L i is the load of the ith route, and n is the total number of routes. In the process of intelligent selection, when the load of a certain protocol conversion module exceeds the average load, the protocol adaptation layer distributes the load to the backup module or adopts multi-threaded parallel processing to achieve load balancing and ensure efficient and stable data exchange.

[0061] Through real-time feedback from collectors and networks, adaptive decisions are made and dynamic adjustments are made to improve the intelligence level of the system and optimize the data interaction process. This process can not only reduce manual intervention, but also make real-time adjustments according to environmental changes to ensure efficient, stable and secure transmission of data streams.

[0062] Specifically, distributed intelligent decision-making and autonomous adjustment include the following steps:

[0063] Distributed data perception: Each collector collects its own status information in real time, including data load and battery status, and reports it to the protocol adaptation layer.

[0064] Establish a global model: Based on the local data collected by each collector, establish a global environment model to reflect the status of the current network and each collector in real time, and provide a basis for subsequent decision-making. The establishment of the global model is based on machine learning model training, which usually includes decision trees, neural networks, etc., which will not be elaborated here.

[0065] Global intelligent decision-making: The protocol adaptation layer makes global intelligent decisions and local optimization decisions through intelligent algorithms based on the global model and the local data collected by each collector.

[0066] Through global intelligent decision-making, the transmission path of data streams is dynamically optimized, the transmission protocol is adjusted according to network conditions, and load balancing is performed among various collectors.

[0067] Through local optimization decisions, each collector is driven to adjust the data collection frequency, modify the data transmission method, adjust the transmission rate, etc.

[0068] The intelligent algorithm formula is: D decision =Decision(M env , P local , A action ), D decision For the decision made, M env is the environmental model, P local is the local device parameter, A action The actions to be performed include traffic adjustment and protocol switching. env =f(D sensor , N status , E history ), where D sensor is the local data collected by the collector, N status is the network status, including bandwidth, delay, and packet loss rate, E history For historical environmental data.

[0069] Through distributed intelligent decision-making and autonomous adjustment, it is possible to make dynamic adjustments based on network conditions, collector status and data flow requirements, and effectively collaborate in a distributed environment. This process ensures the efficiency, stability and adaptability of data interaction through real-time feedback and continuous optimization.

[0070] Step 4: Blockchain and end-to-end security authentication

[0071] The protocol adaptation layer generates a unique hash value for each data packet during each data interaction, and stores each data packet and its hash value in the decentralized blockchain network.

[0072] After receiving the data, the concentrator first calculates the hash value of the received data and compares it with the data packet and its hash value stored in the blockchain for verification.

[0073] It should be noted that: in order to ensure the security of data transmission, the protocol adaptation layer is configured with a multi-layer identity authentication mechanism. When a collector is connected, the system verifies the identity of the collector and the source of the data through public key encryption and digital signature technology. The communication between each collector and the concentrator is encrypted, and the key is updated regularly to prevent key leakage or malicious attacks.

[0074] For sensitive data such as user privacy and corporate secrets, the protocol adaptation layer will perform data desensitization and anonymization during data transmission to avoid data leakage. All sensitive data is encrypted and can only be decrypted and viewed by devices and users with specific permissions.

[0075] Step 5: Data aggregation and centralized processing

[0076] After receiving the data, the concentrator parses, integrates and stores the data, performs deep learning and predictive analysis on the data, and performs real-time analysis on the data.

[0077] The concentrator can assign data to different processing units for parallel processing based on their characteristics, priority, and timeliness. For example, event data with high real-time requirements will be processed by the concentrator first, while data with delay tolerance, such as historical data or status reports, can be processed in batches. The specific functions of the concentrator are not described here.

[0078] Step 6: System optimization and feedback adjustment

[0079] After the concentrator processes the data, it returns the generated feedback data to the corresponding collector through the protocol adaptation layer to complete the closed-loop control. During the closed-loop control process, based on the real-time data analysis results of the concentrator, the protocol adaptation layer automatically adjusts the protocol adaptation mode, data compression strategy or load balancing mechanism according to the feedback information such as collector performance and network status to improve the overall performance and stability of the system.

[0080] Continuous optimization is performed based on the actual feedback results of the system's adaptive adjustment, and global and local decisions are continuously updated through the feedback mechanism to achieve better data interaction efficiency. This feedback mechanism is a continuous iterative process that ensures that the system can always maintain a high level of intelligence under changing environments and requirements. updated =Feedback(M env , A adjusted ), M updated is the updated environment model, M env is the environmental model, A adjusted For the adjusted action.

[0081] It should be noted that in the process of distributed intelligent decision-making and autonomous adjustment, the system performance can be evaluated regularly to collect indicators such as the working status of each collector and concentrator, data transmission efficiency, and delay, and the system can be fully optimized based on these indicators. Evaluation indicators may also include data transmission success rate, average delay, bandwidth utilization, energy consumption, etc., which need to be set according to actual conditions.

[0082] Embodiment 2

[0083] like Figure 2 As shown, the second aspect of the present invention proposes a data interaction system between a concentrator and a collector, comprising: a collector layer, a protocol adaptation layer and a concentrator layer. The collector layer is composed of different types of collectors, each of which uses a unique communication protocol and data format. The protocol adaptation layer is located between the collector layer and the concentrator layer, and is used for dynamic protocol discovery, adaptation, conversion and data optimization. The concentrator layer includes a concentrator, which is used to aggregate, analyze and transmit the received data.

[0084] When the collector is connected to the system, it sends the information of the protocol type it supports. The protocol adaptation layer dynamically selects the appropriate protocol conversion module based on the protocol type, device ID and network environment of the collector to realize data protocol conversion, and transmits the converted data to the concentrator. After receiving the data, the concentrator first unpacks the data, and further analyzes, stores or makes decisions on the data, and takes corresponding actions based on the data content. After the concentrator processes the data, it returns the generated feedback data to the corresponding collector through the protocol adaptation layer to complete the closed-loop control. Among them, based on the real-time data analysis results of the concentrator, the protocol adaptation layer automatically adjusts the protocol adaptation method, data compression strategy or load balancing mechanism according to the collector performance, network status, etc., to improve the overall performance and stability of the system.

[0085] Specifically, after the protocol adaptation layer receives the data sent by the collector, it first performs compression processing, removes useless data fields and reduces the data size to reduce bandwidth consumption and improve data transmission efficiency. The incremental data is gradually converted using a streaming method instead of converting all the data at once, which can reduce memory usage, reduce latency, and improve the real-time performance of the system. The compressed and incrementally processed data is then converted into a standard format and transmitted to the concentrator. The converted data is easy to further analyze, store and transmit, and is compatible with a variety of protocols and devices.

[0086] During data interaction, the protocol adaptation layer first evaluates the optimal communication protocol based on the system's network status, which includes network bandwidth, network latency, etc., and selects the routing path based on protocol priority and network bandwidth limitations. For example, high-speed communication protocols such as Modbus are preferred in a local area network, while low-bandwidth protocols such as MQTT are selected when remote devices or network bandwidth is limited.

[0087] The protocol adaptation layer diverts the heavily loaded protocol adaptation modules and distributes the load to the backup modules or uses multi-threaded parallel processing to achieve load balancing. This avoids performance degradation due to overloading of a certain protocol conversion module and reasonably distributes the load to multiple protocol adaptation modules to ensure the stability of data interaction.

[0088] In order to prevent data from being tampered with during the protocol conversion process, the protocol adaptation layer generates a unique hash value for each data packet during each data interaction. Each data packet and its hash value are recorded in the blockchain network. The decentralization and immutability of the blockchain ensure the integrity of the data and the credibility of the source.

[0089] When the concentrator receives data, it will first calculate the hash value of the received data and compare it with the hash value recorded in the blockchain. If the two hash values ​​match, it means that the data has not been tampered with. This process ensures the integrity and reliability of the data.

[0090] In addition, in special cases, there may be large bandwidth limitations or delay bottlenecks between the collector and the protocol adaptation layer. In order to avoid data loss, the system is also equipped with edge computing devices to cache data when there is a delay in the system, filter the cached data, and compress the data until the network conditions allow it to be transmitted. Real-time data processing by edge computing devices can reduce transmission delays.

[0091] By introducing a protocol adaptation layer, the existing problems of protocol incompatibility, performance bottlenecks, increased latency, and potential safety hazards between collectors and concentrators can be effectively solved. This method improves the performance, flexibility, and security of the system through dynamic protocol discovery and adaptation, lightweight data conversion and optimization, intelligent routing and load balancing, and blockchain-based security authentication, while reducing the complexity and management costs of the system.

[0092] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention is described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A data interaction method between a concentrator and a collector, characterized in that: The steps include: Step 1: Multi-layer protocol discovery and dynamic adaptation: Based on the protocol type and network environment supported by the collector, the protocol adapter module is automatically selected for protocol adaptation, and the data collected by the collector is converted into a data format supported by the concentrator through protocol conversion; Step 2: Intelligent data flow optimization and real-time conversion: The data collected by the collector forms a data flow, and the data flow rate and data conversion strategy are dynamically adjusted according to the network load and data flow priority; Step 3: Distributed intelligent decision-making and autonomous adjustment: The protocol adaptation layer dynamically adjusts according to the feedback information of each collector and makes intelligent selections among multiple protocol conversion modules and communication protocols; Step 4: Blockchain and end-to-end security authentication: Encrypted transmission is performed during data interaction, and the data packet and the generated hash value are stored in the blockchain; Step 5: Data aggregation and centralized processing: The concentrator aggregates and centrally processes the received data; Step 6: System optimization and feedback adjustment: The system continuously updates global and local decisions based on the feedback mechanism.

2. The data interaction method between a concentrator and a collector according to claim 1, characterized in that: The specific process of step 1, multi-layer protocol discovery and dynamic adaptation is as follows: the collector sends a list of supported protocols to the protocol adaptation layer through broadcasting, and the protocol adaptation layer dynamically selects a matching protocol adaptation module for data conversion based on the protocol list sent by the protocol collector.

3. The data interaction method between a concentrator and a collector according to claim 2, characterized in that: The selection formula of the protocol adapter module is: adapt =Protocol_Adaptation(P device ,N status ), where M adapt is the selected protocol adapter module, P device N is the protocol type of the collector. status It is the current network status, which includes network bandwidth and network delay.

4. The data interaction method between a concentrator and a collector according to claim 1, characterized in that: The specific process of step 2, intelligent data flow optimization and real-time conversion is as follows: Under normal circumstances, after receiving the data sent by the collector, the protocol adaptation layer first removes the useless data fields, then incrementally updates the data stream, and only converts the incremental data before sending it to the concentrator; In special cases, when there is bandwidth limitation or delay between the collector and the protocol adaptation layer, the data stream is cached by the edge computing device, which filters and compresses the cached data and waits for the network to recover. The protocol adaptation layer converts the data processed by the edge computing device and sends it to the concentrator. The data conversion formula is: D converted =Format_Conversion(P device , D raw ), where P device D is the collector protocol; raw is the original data.

5. The data interaction method between a concentrator and a collector according to claim 1, characterized in that: The process of step 3, distributed intelligent decision-making and autonomous adjustment, includes the following steps: Distributed data perception: Each collector collects its own status information in real time, including data load and battery status, and reports it to the protocol adaptation layer; Establish a global model: Based on the local data collected by each collector, establish a global environment model to reflect the status of the current network and each collector in real time; Global intelligent decision-making: The protocol adaptation layer makes global intelligent decisions and local optimization decisions through intelligent algorithms based on the global model and local data collected by each collector; The global intelligent decision is used to dynamically optimize the transmission path of the data flow, adjust the transmission protocol according to the network conditions, and perform load balancing among the collectors; the local optimization decision is used to drive each collector to adjust the data collection frequency, modify the data transmission method, and adjust the transmission rate.

6. The data interaction method between the concentrator and the collector according to claim 5, characterized in that: The intelligent algorithm formula is: decision =Decision(M env ,P local ,A action ), D decision For the decision made, M env is the environmental model, P local is the local device parameter, A action Actions to be performed, including traffic shaping and protocol switching; Among them, M env =f(D sensor ,N status ,E history ),D sensor is the local data collected by the collector, N status is the network status, including bandwidth, delay, and packet loss rate, E history For historical environmental data.

7. The data interaction method between a concentrator and a collector according to claim 1, characterized in that: The specific process of blockchain and end-to-end security authentication is as follows: The protocol adaptation layer generates a unique hash value for each data packet during each data interaction, and stores each data packet and its hash value in a decentralized blockchain network; After receiving the data, the concentrator first calculates the hash value of the received data and compares it with the data packet and its hash value stored in the blockchain for verification.

8. The data interaction method between a concentrator and a collector according to claim 1, characterized in that: The process of step five, data aggregation and centralized processing, is as follows: after receiving the data, the concentrator parses, integrates and stores the data, performs deep learning and predictive analysis on the data, and performs real-time analysis on the data.

9. The data interaction method between a concentrator and a collector according to claim 1, characterized in that: The process of step six, system optimization and feedback adjustment is as follows: After the concentrator processes the data, it returns the generated feedback data to the corresponding collector through the protocol adaptation layer to complete the closed-loop control. In the process of closed-loop control, the global and local decisions are continuously updated through the feedback mechanism to optimize the environmental model. updated =Feedback(M env ,A adjusted ), M updated is the updated environment model, M env is the environmental model, A adjusted For the adjusted action.

10. A data interaction system between a concentrator and a collector, characterized in that: A method for implementing data interaction between a concentrator and a collector according to any one of claims 1 to 9, comprising: Collector layer: It is composed of different types of collectors, each of which uses a unique communication protocol and data format; Protocol Adaptation Layer: Located between the collector layer and the concentrator layer, it is used for dynamic protocol discovery, adaptation, conversion, and data optimization; Concentrator layer: includes concentrators, which are used to aggregate, analyze and transmit the data transmitted by each collector.

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