A data interaction method and system for an Internet of Things platform

Abstract

The present invention discloses a data interaction method and system for an Internet of Things platform, and relates to the technical field of smart cities, a perception module, the perception module is used to collect data; a data management module, the data management module includes a management unit, an intercommunication unit and an optimization unit; the intercommunication unit is used to measure and optimize the interoperability and system complexity of the Internet of Things platform; the optimization unit is used to monitor and optimize the working performance of the Internet of Things platform; a security module, the security module is used to monitor the operating status of the Internet of Things platform in real time to ensure the security of data transmission and the security of equipment; by real-time monitoring and calculating the index parameters of the Internet of Things platform, real-time optimization can be performed when the performance of the Internet of Things platform in processing massive Internet of Things data is insufficient, and the data exchange efficiency of the Internet of Things platform between devices of different manufacturers and types can be evaluated in real time, and optimization can be performed as soon as possible when defects occur.

Description

Technical Field

[0001] The present invention relates to the field of smart city technology, and more specifically, to a data interaction method and system for an Internet of Things platform. Background Art

[0002] The data interaction systems of the IoT platform are widely used in many fields, including but not limited to smart homes, industrial automation, smart cities, healthcare, agricultural monitoring, energy management, etc. These systems help improve efficiency, reduce costs, enhance security and improve decision-making processes by collecting, transmitting, processing and analyzing data from various sensors and devices;

[0003] The Chinese patent application number 202211712611.X discloses a smart city service platform based on the Internet of Things, including: a feedback receiving module, which is used to receive city service feedback information input by city users based on multiple receiving channels; a strategy generation module, which is used to generate a city service verification strategy based on the potential correlation characteristics of all city service feedback information received within a preset period; a feedback verification module, which is used to verify all city service feedback information received within a preset period based on the city service verification strategy to obtain feedback verification results; a feedback follow-up module, which is used to generate feedback follow-up results based on the feedback verification results; it is used to automatically generate a reasonable city service verification strategy based on the potential correlation characteristics of the received city service feedback information, and receive and further follow up the feedback verification results based on the city service verification strategy, so as to realize the timely and efficient processing of feedback opinions on city services, and make the feedback implementation process of city services more systematic and process-oriented;

[0004] However, due to the large number of devices in smart cities, it is not only difficult to process massive amounts of IoT data, but it is also difficult to effectively exchange data between devices of different manufacturers and types. Moreover, if potential problems arise during use that affect the efficiency of the IoT platform, it is also difficult to handle them in a timely and efficient manner. Summary of the invention

[0005] In order to solve the above problems, the present invention provides a data interaction method and system for an Internet of Things platform.

[0006] On the one hand, the present invention proposes a data interaction method of an Internet of Things platform, comprising:

[0007] Step 1: First, collect parameter data in the IoT platform, and then evaluate the performance of the IoT platform based on the data;

[0008] Step 2: Perform corresponding optimization based on the performance of the IoT platform after evaluation;

[0009] Step 3: Monitor the operation status of the IoT platform in real time to ensure the security of data transmission and equipment;

[0010] The specific process of step one is: obtaining the data growth forecast value Q of the current time period of the Internet of Things platform;

[0011] Obtain the data compression rate value W of the IoT platform in the current time period;

[0012] Obtain the data redundancy value E of the IoT platform in the current time period;

[0013] According to the formula , calculate and obtain the data management efficiency value R of the IoT platform, where , and is the preset proportional coefficient;

[0014] Set a threshold value of data management efficiency value in advance;

[0015] The data management efficiency value R is compared with the threshold of the data management efficiency value. If the data management efficiency value R is less than or equal to the threshold of the data management efficiency value, optimization measures are taken according to each indicator.

[0016] On the other hand, the present invention also proposes a data interaction system of an Internet of Things platform, comprising:

[0017] A perception module, wherein the perception module is used to collect data;

[0018] A data management module, the data management module comprising a management unit, an intercommunication unit and an optimization unit;

[0019] The management unit is used to evaluate the data management efficiency and performance of the IoT platform based on the collected data, specifically:

[0020] Obtain the data growth forecast value Q of the IoT platform in the current time period;

[0021] Obtain the data compression rate value W of the IoT platform in the current time period;

[0022] Obtain the data redundancy value E of the IoT platform in the current time period;

[0023] According to the formula , calculate and obtain the data management efficiency value R of the IoT platform, where , and is the preset proportional coefficient;

[0024] Set a threshold value of data management efficiency value in advance;

[0025] Compare the data management efficiency value R with the threshold of the data management efficiency value. If the data management efficiency value R is less than or equal to the threshold of the data management efficiency value, take optimization measures according to each indicator.

[0026] The interoperability unit is used to measure and optimize the interoperability and system complexity of the Internet of Things platform;

[0027] The optimization unit is used to monitor and optimize the working performance of the Internet of Things platform;

[0028] The security module is used to monitor the operating status of the Internet of Things platform in real time to ensure the security of data transmission and the security of devices.

[0029] Preferably, the specific working mode of the intercommunication unit is as follows:

[0030] Obtain the protocol conversion efficiency value T of the current time period of the Internet of Things platform;

[0031] Obtain the complexity value Y of the device in the current time period of the IoT platform;

[0032] Obtain the API call frequency value U of the current time period of the IoT platform;

[0033] Obtain the data consistency value P of the current time period of the IoT platform;

[0034] According to the formula , calculate and obtain the IoT platform device interaction value ,in , , and is the preset proportional coefficient;

[0035] Set a threshold for device interaction value in advance;

[0036] The device interaction value Compare with the threshold of the device interaction value. If the device interaction value If the value is less than or equal to the threshold of the device interaction value, optimization measures are taken according to each indicator.

[0037] Preferably, the specific working mode of the optimization unit is as follows:

[0038] Obtain the resource utilization value F of the current time period of the Internet of Things platform;

[0039] Obtain the system throughput value G of the current time period of the Internet of Things platform;

[0040] Obtain the average response time value H of the current time period of the Internet of Things platform;

[0041] According to the formula , calculate and obtain the performance optimization value of the IoT platform ,in , and is the preset proportional coefficient;

[0042] Set a threshold for performance optimization value in advance;

[0043] Optimize performance value The performance optimization value is compared with the threshold. If the performance optimization value If the performance is less than or equal to the performance optimization threshold, optimization measures are taken according to each indicator.

[0044] Preferably, the data management module further includes a subsequent adjustment unit, which is used to regularly review the performance data and perform further optimization, specifically:

[0045] After the optimization measures of the management unit, the intercommunication unit and the optimization unit are taken, the difference between the IoT platform device interaction value S, the performance optimization value J and the efficiency management value R and the corresponding threshold is calculated and obtained. , and ;

[0046] According to the formula ,

[0047] Calculate and obtain the comprehensive performance gap value M of the IoT platform;

[0048] A threshold value of the comprehensive performance gap value is set in advance. If the comprehensive performance gap value M is greater than or equal to the threshold value of the comprehensive performance gap value, it is determined that the Internet of Things platform needs to be further optimized;

[0049] Reset the thresholds of IoT platform device interaction value, performance optimization value, and efficiency management value;

[0050] Then the data is transmitted to the management unit, the intercommunication unit and the optimization unit again for optimization until the optimized comprehensive performance gap value M is less than the threshold value of the comprehensive performance gap value.

[0051] Preferably, the subsequent adjustment unit resets the threshold of the Internet of Things platform device interaction value, the threshold of the performance optimization value, and the threshold of the efficiency management value in the following specific manner:

[0052] According to the formula , calculate and obtain the threshold growth rate of the IoT platform ,in represents the growth rate of the i-th indicator, represents the starting measurement value of the ith indicator, represents the current measured value of the i-th indicator, and N is the preset adaptation value;

[0053] The threshold growth rate of each indicator after calculation Substitute into the management unit, the intercommunication unit and the optimization unit to obtain new thresholds of the device interaction value, the performance optimization value and the efficiency management value.

[0054] Preferably, the specific method of obtaining the fitness value N is as follows:

[0055] Get the cost value of the IoT platform ;

[0056] Get the technical limit value of the IoT platform ;

[0057] Get the business demand indicator value of the IoT platform ;

[0058] According to the formula , calculate and obtain the fitness value N, where , and is the preset scaling factor.

[0059] Preferably, the security module includes an Internet of Things platform security unit and a data protection unit, and the data protection unit is used to encrypt data in the Internet of Things, specifically:

[0060] Storage encryption, by encrypting the stored data using AES;

[0061] The Internet of Things platform security unit is used to comprehensively calculate and reflect the security status of the Internet of Things devices.

[0062] Preferably, the specific method of storage encryption is:

[0063] Device identity authentication;

[0064] Data encryption;

[0065] Privacy protection;

[0066] Cybersecurity;

[0067] Access control.

[0068] Preferably, the specific working mode of the data protection unit is as follows, specifically:

[0069] According to the formula , get the security value A of the IoT platform, where is the total number of security dimensions;

[0070] is the weight of the i-th security dimension;

[0071] is the score value of the i-th security dimension;

[0072] A safety value threshold is set in advance. If the real-time safety value A is less than the safety value threshold, an alarm signal is generated and transmitted to the staff's mobile phone terminal.

[0073] Beneficial effects: By real-time monitoring and calculating the indicator parameters of the IoT platform, real-time optimization can be performed when the IoT platform's performance in processing massive IoT data is insufficient. In addition, the efficiency of data exchange between devices of different manufacturers and types on the IoT platform can be evaluated in real time, and optimization can be performed as soon as possible when defects occur. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 The present invention is a flow chart of the method.

[0075] Figure 2 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0076] like Figure 2 As shown, it should be noted that, in this embodiment, the Internet of Things platform is applied to the field of smart city technology. However, due to the large number of devices in the smart city, it is not only difficult to process massive amounts of Internet of Things data, but also difficult to effectively exchange data between devices of different manufacturers and types. This technical solution calculates the key performance parameters of multiple groups of data through comprehensive evaluation, and then performs targeted optimization based on the parameters, which can ensure that the data interaction system of the Internet of Things platform remains efficient, stable and scalable;

[0077] The present invention proposes a data interaction system for an Internet of Things platform, comprising:

[0078] A perception module, which is used to collect data; it should be noted that, in this embodiment, the data includes: device hardware data and software data parameters in the Internet of Things platform, specifically including device data volume information, device response time, etc.;

[0079] A data management module, the data management module comprising a management unit, an intercommunication unit and an optimization unit;

[0080] The management unit is used to evaluate the data management efficiency and performance of the IoT platform based on the collected data, specifically:

[0081] The data growth prediction value Q of the IoT platform in the current time period is obtained; it should be noted that the data growth prediction value Q is helpful for planning storage capacity and processing capacity. In this embodiment, the calculation method of the data growth prediction value Q can be: , where the current data volume is directly measured by system monitoring tools (such as database size and storage usage), the current data volume can be directly obtained, The growth rate is determined by analyzing the growth of the data volume over a period of time. In this embodiment, the growth rate can also be determined by , it is obtained that the time period is a preset time period. In this embodiment, the unit of the time period is week, and the time period is one week;

[0082] The data compression rate value W of the IoT platform in the current time period is obtained; it should be noted that the data compression rate value W is obtained by calculating the ratio of compressed data to original data to evaluate the compression. The specific calculation method can be , where the unit of data size is GB;

[0083] The data redundancy value E of the current time period of the Internet of Things platform is obtained; it should be noted that the data redundancy value E is used to represent the data storage efficiency. In this embodiment, the calculation formula of the data redundancy value E can be:

[0084] , where the unit of data size is GB;

[0085] It should also be noted that the size of data after deduplication refers to the amount of data remaining after all duplicates are deleted from the data. In many data sets, there may be duplicate data records, and these duplicates will occupy storage space meaninglessly. By identifying and removing these duplicate data, storage requirements can be reduced and storage efficiency can be improved. For example, if a database table has 100GB of data, including 10GB of duplicate records, the size of the data after deduplication will be 90GB, which means there is 10% redundant data.

[0086] According to the formula , calculate and obtain the data management efficiency value R of the IoT platform, where , and is a preset proportionality coefficient; it should be noted that in this embodiment , and The values ​​of can be 0.298, 0.218 and 0.484;

[0087] A threshold value of the data management efficiency value is set in advance; it should be noted that, in this embodiment, the threshold value of the data management efficiency value is determined based on industry standards, historical best practices or business needs;

[0088] The data management efficiency value R is compared with the threshold of the data management efficiency value. If the data management efficiency value R is less than or equal to the threshold of the data management efficiency value, optimization measures are taken according to each indicator. It should be noted that, in this embodiment, the optimization measures may be:

[0089] Data growth forecast: If the data growth forecast is too high, consider increasing storage capacity or optimizing data storage strategies;

[0090] Data compression ratio value: If the data compression ratio value is small, a more efficient compression algorithm is used;

[0091] Data redundancy value: If the data redundancy value is high, implement a more effective data deduplication strategy:

[0092] It should also be noted that the data growth forecast can help staff understand the data processing and storage requirements that grow over time, so as to choose the appropriate expansion strategy;

[0093] Optimizing the data compression rate can reduce the burden of network transmission, especially in areas with densely populated devices and huge amounts of data;

[0094] Data redundancy value calculation helps to identify and integrate data from different manufacturers and types of equipment, reducing the complexity of data integration;

[0095] Comprehensive evaluation and calculation can more effectively manage and exchange massive amounts of IoT data, while improving data interoperability and overall system efficiency;

[0096] The interoperability unit is used to measure and optimize the interoperability and system complexity of the Internet of Things platform;

[0097] The optimization unit is used to monitor and optimize the working performance of the Internet of Things platform;

[0098] It should be noted that by real-time monitoring and calculating the indicator parameters of the IoT platform, real-time optimization can be performed when the IoT platform is insufficient in processing massive IoT data. In addition, the efficiency of data exchange between devices of different manufacturers and types can be evaluated in real time, and optimization can be performed as soon as possible when defects occur.

[0099] As an optional embodiment: the specific working mode of the intercommunication unit is as follows:

[0100] The protocol conversion efficiency value T of the current time period of the Internet of Things platform is obtained; it should be noted that, in this embodiment, the protocol conversion efficiency value T is obtained by the staff according to the performance of different protocol conversion middlewares and the data packet size or conversion time before and after the calculation of the conversion, and the protocol conversion efficiency value T is any integer from 1 to 10;

[0101] Obtain the complexity value Y of the device in the current time period of the Internet of Things platform; it should be noted that, in this embodiment, the calculation method of the complexity value Y is obtained by software measurement, specifically: , where e is a variable, n is the number of nodes in the IoT platform, and the number of component connections is the number of component connections in the IoT platform;

[0102] Obtain the API call frequency value U of the current time period of the IoT platform; it should be noted that, in the embodiment, the value of the call frequency value U can evaluate the performance and load balancing requirements of the API gateway, and the specific calculation method can be the total number of calls divided by the time period;

[0103] Obtain the data consistency value P of the current time period of the Internet of Things platform; it should be noted that, in this embodiment, the data consistency value P is used to calculate the complexity and space complexity of data consistency;

[0104] According to the formula , calculate and obtain the IoT platform device interaction value ,in , , and is the preset proportional coefficient;

[0105] A threshold value of a device interaction value is set in advance; it should be noted that, in this embodiment, the threshold value of the data management efficiency value is determined based on industry standards, historical best practices or business needs;

[0106] The device interaction value Compare with the threshold of the device interaction value. If the device interaction value If the value is less than or equal to the threshold of the device interaction value, optimization measures are taken according to each indicator; it should be noted that, in this embodiment, the optimization measures may be:

[0107] Improve communication efficiency: By optimizing protocol conversion, reduce the time and size of data transmission, and improve network efficiency;

[0108] Simplify system integration: reduce the complexity of abstract models and simplify the integration process of different devices and technologies;

[0109] Enhanced API management: By monitoring the API call frequency, ensure that the API gateway can handle high concurrent requests and improve the scalability of the system;

[0110] Ensure data reliability: Ensure the accuracy and reliability of data in distributed systems through data consistency checks.

[0111] As an optional embodiment: the specific working mode of the optimization unit is as follows:

[0112] Obtain the resource utilization value F of the current time period of the Internet of Things platform; It should be noted that, in this embodiment, the resource utilization is used to represent the utilization of CPU and storage, and is used to optimize resource allocation. The calculation method can be 00%;

[0113] The system throughput value G of the current time period of the Internet of Things platform is obtained; it should be noted that, in this embodiment, the system throughput value is used to represent the processing capacity of the Internet of Things system during use, and the calculation method may be the number of times the Internet of Things successfully processes events divided by the time period;

[0114] The average response time value H of the current time period of the Internet of Things platform is obtained; it should be noted that, in this embodiment, the average response time is used to represent the average processing time of the Internet of Things system, and the calculation method is the total response time divided by the number of requests;

[0115] According to the formula , calculate and obtain the performance optimization value of the IoT platform ,in , and is a preset proportionality coefficient; it should be noted that, in this embodiment, , and The values ​​of can be 0.283, 0.296 and 0.421;

[0116] A threshold of a performance optimization value is set in advance; it should be noted that, in this embodiment, the threshold of the data management efficiency value is determined based on industry standards, historical best practices or business needs;

[0117] Optimize performance value The performance optimization value is compared with the threshold. If the performance optimization value If the value is less than or equal to the threshold of the performance optimization value, optimization measures are taken according to each indicator; it should be noted that, in this embodiment, the optimization measures may be:

[0118] Load balancing: Through load balancing technology, requests can be distributed to multiple servers or resources, thereby improving resource utilization and system throughput; Dynamic resource allocation: According to real-time monitoring of resource utilization, resource allocation is dynamically adjusted, such as automatically expanding cloud service instances;

[0119] Performance tuning: Perform performance tuning on the system, such as optimizing database queries, network configuration, and application code to reduce latency and improve response time.

[0120] As an optional embodiment: the data management module further includes a subsequent adjustment unit, which is used to regularly review the performance data and perform further optimization, specifically:

[0121] After the optimization measures of the management unit, the intercommunication unit and the optimization unit are taken, the difference between the IoT platform device interaction value S, the performance optimization value J and the efficiency management value R and the corresponding threshold is calculated and obtained. , and ;

[0122] According to the formula ,

[0123] Calculate and obtain the comprehensive performance gap value M of the IoT platform;

[0124] A threshold value of the comprehensive performance gap value is set in advance. If the comprehensive performance gap value M is greater than or equal to the threshold value of the comprehensive performance gap value, it is determined that the Internet of Things platform needs to be further optimized;

[0125] Reset the thresholds of IoT platform device interaction value, performance optimization value, and efficiency management value;

[0126] Then the data is transmitted to the management unit, the intercommunication unit and the optimization unit again for optimization until the optimized comprehensive performance gap value M is less than the threshold value of the comprehensive performance gap value.

[0127] As an optional embodiment: the specific manner in which the subsequent adjustment unit resets the threshold of the IoT platform device interaction value, the threshold of the performance optimization value, and the threshold of the efficiency management value is as follows:

[0128] According to the formula , calculate and obtain the threshold growth rate of the IoT platform ,in represents the growth rate of the i-th indicator, represents the starting measurement value of the ith indicator, represents the current measured value of the ith indicator, and N is the preset adaptation value; it should be noted that, in this embodiment, the number of indicators is three, namely, the device interaction value, the performance optimization value, and the efficiency management value. represents the starting measurement value of the ith indicator, namely, the device interaction value S, the performance optimization value J, and the efficiency management value R. represents the current measured value of the ith indicator, that is, the device interaction value, performance optimization value and efficiency management value measured after adjustment by the subsequent adjustment unit. The adaptation value is set in advance by the staff according to the environment. In this embodiment, the adaptation value is 96.7%;

[0129] The threshold growth rate of each indicator after calculation Substitute into the management unit, intercommunication unit and optimization unit to obtain the new threshold of device interaction value, performance optimization value and efficiency management value. It should be noted that in this embodiment, the specific calculation method is to multiply the original threshold of device interaction value, performance optimization value and efficiency management value by 1 plus the corresponding growth rate. The new threshold value obtained by calculating according to the optimized specific numerical feedback can reduce the time and number of times the overall Internet of Things platform reaches the target performance during the optimization process.

[0130] As an optional embodiment: the specific method of obtaining the fitness value N is as follows:

[0131] Get the cost value of the IoT platform ; It should be noted that, in this embodiment, the cost value is obtained through staff evaluation, and the cost value is any integer from 1 to 10, and the staff evaluates the comprehensive value of the hardware, software and operation and maintenance costs in the Internet of Things platform;

[0132] Get the technical limit value of the IoT platform It should be noted that, in this embodiment, the cost value is obtained through staff evaluation, and the cost value is any integer from 1 to 10, and the staff evaluates the system throughput and availability in the comprehensive Internet of Things platform;

[0133] Get the business demand indicator value of the IoT platform ; It should be noted that, in this embodiment, the cost value is obtained through evaluation by staff, and the cost value is any integer from 1 to 10, and the staff evaluates the comprehensive value of the hardware performance limitations and software architecture limitations in the Internet of Things platform;

[0134] According to the formula , calculate and obtain the fitness value N, where , and It should be noted that , and The value of can be 0.298, 0.128 and 0.574; it should also be noted that in actual use, the setting of the threshold will also be affected by the characteristics of the IoT platform itself. By comprehensively calculating the above indicators during the threshold calculation process, the optimized threshold can be more in line with the actual data.

[0135] As an optional embodiment: the security module includes an Internet of Things platform security unit and a data protection unit, and the data protection unit is used to encrypt data in the Internet of Things, specifically:

[0136] Storage encryption, by encrypting the stored data using AES;

[0137] The Internet of Things platform security unit is used to comprehensively calculate and reflect the security status of the Internet of Things devices.

[0138] As an optional embodiment: the specific method of storage encryption is:

[0139] Device authentication; it should be noted that strong authentication mechanisms are used, such as certificate authentication based on public key infrastructure (PKI), and multi-factor authentication is implemented, combining passwords, biometrics or physical tokens;

[0140] Data encryption: It should be noted that the data in transit is encrypted using TLS / SSL or DTLS protocols, and the stored data is encrypted using a strong encryption algorithm such as AES;

[0141] Privacy protection: It should be noted that the principle of data minimization is implemented, only necessary data is collected, and sensitive data is anonymized or de-identified;

[0142] Network security: It should be noted that VPN and firewall should be used to protect network traffic, and network security policies and rules should be updated regularly;

[0143] Access control: It should be noted that role-based access control should be implemented and access rights should be reviewed regularly to ensure that the principle of least privilege is followed.

[0144] As an optional embodiment: the specific working mode of the data protection unit is as follows, specifically:

[0145] According to the formula , get the security value A of the IoT platform, where is the total number of security dimensions; it should be noted that in this embodiment, the total number of security dimensions is five, namely identity authentication, data encryption, privacy protection, network security and access control;

[0146] is the weight of the i-th security dimension; it should be noted that, in this embodiment, the weights are obtained according to security policies and business requirements, and can be 0.125, 0.285, 0.14, 0.257 and 0.193 respectively;

[0147] is the score value of the i-th security dimension; it should be noted that, in this embodiment, the score of each security dimension is obtained by the installation staff and is any integer from 1 to 10;

[0148] A safety value threshold is set in advance. If the real-time safety value A is less than the safety value threshold, an alarm signal is generated and transmitted to the staff's mobile phone terminal.

[0149] On the other hand, the present invention also proposes a data interaction method of an Internet of Things platform, comprising:

[0150] Step 1: First, collect parameter data in the IoT platform, and then evaluate the performance of the IoT platform based on the data;

[0151] Step 2: Perform corresponding optimization based on the performance of the IoT platform after evaluation;

[0152] Step 3: Monitor the operation status of the IoT platform in real time to ensure the security of data transmission and equipment;

[0153] The specific process of step one is: obtaining the data growth forecast value Q of the current time period of the Internet of Things platform;

[0154] Obtain the data compression rate value W of the IoT platform in the current time period;

[0155] Obtain the data redundancy value E of the IoT platform in the current time period;

[0156] According to the formula, the data management efficiency value R of the Internet of Things platform is calculated and obtained, where, and are preset proportional coefficients;

[0157] Set a threshold value of data management efficiency value in advance;

[0158] The data management efficiency value R is compared with the threshold of the data management efficiency value. If the data management efficiency value R is less than or equal to the threshold of the data management efficiency value, optimization measures are taken according to each indicator.

[0159] Working principle:

[0160] By real-time monitoring and calculating the indicator parameters of the IoT platform, real-time optimization can be performed when the IoT platform's performance in processing massive IoT data is insufficient. The efficiency of data exchange between devices of different manufacturers and types of the IoT platform can also be evaluated in real time, and optimization can be performed as soon as possible when defects occur.

[0161] The above are only preferred implementations of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technical staff in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of this template.

Claims

1. A data interaction method for an Internet of Things platform, characterized in that: include: Step 1: First, collect parameter data in the IoT platform, and then evaluate the performance of the IoT platform based on the data; Step 2: Perform corresponding optimization based on the performance of the IoT platform after evaluation; Step 3: Monitor the operation status of the IoT platform in real time to ensure the security of data transmission and equipment; The specific process of step one is: obtaining the data growth forecast value Q of the current time period of the Internet of Things platform; Obtain the data compression rate value W of the IoT platform in the current time period; Obtain the data redundancy value E of the IoT platform in the current time period; According to the formula , calculate and obtain the data management efficiency value R of the Internet of Things platform, where , and is the preset proportional coefficient; Set a threshold value of data management efficiency value in advance; The data management efficiency value R is compared with the threshold of the data management efficiency value. If the data management efficiency value R is less than or equal to the threshold of the data management efficiency value, optimization measures are taken according to each indicator.

2. A data interaction system for an Internet of Things platform, applicable to a data interaction method for an Internet of Things platform proposed in claim 1, characterized in that: include: A perception module, wherein the perception module is used to collect data; A data management module, the data management module comprising a management unit, an intercommunication unit and an optimization unit; The management unit is used to evaluate the data management efficiency and performance of the IoT platform based on the collected data, specifically: Obtain the data growth forecast value Q of the IoT platform in the current time period; Obtain the data compression rate value W of the IoT platform in the current time period; Obtain the data redundancy value E of the IoT platform in the current time period; According to the formula , calculate and obtain the data management efficiency value R of the Internet of Things platform, where , and is the preset proportional coefficient; Set a threshold value of data management efficiency value in advance; Compare the data management efficiency value R with the threshold of the data management efficiency value. If the data management efficiency value R is less than or equal to the threshold of the data management efficiency value, take optimization measures according to each indicator. The interoperability unit is used to measure and optimize the interoperability and system complexity of the Internet of Things platform; The optimization unit is used to monitor and optimize the working performance of the Internet of Things platform; The security module is used to monitor the operating status of the Internet of Things platform in real time to ensure the security of data transmission and the security of devices.

3. The data interaction system of an Internet of Things platform according to claim 2, characterized in that: The specific working mode of the intercommunication unit is as follows: Obtain the protocol conversion efficiency value T of the current time period of the Internet of Things platform; Obtain the complexity value Y of the device in the current time period of the IoT platform; Obtain the API call frequency value U of the current time period of the IoT platform; Obtain the data consistency value P of the current time period of the IoT platform; According to the formula , calculate and obtain the IoT platform device interaction value ,in , , and is the preset proportional coefficient; Set a threshold for device interaction value in advance; The device interaction value Compare with the threshold of the device interaction value. If the device interaction value If the value is less than or equal to the threshold of the device interaction value, optimization measures are taken according to each indicator.

4. The data interaction system of an Internet of Things platform according to claim 2, characterized in that: The specific working mode of the optimization unit is as follows: Obtain the resource utilization value F of the current time period of the Internet of Things platform; Obtain the system throughput value G of the current time period of the Internet of Things platform; Obtain the average response time value H of the current time period of the Internet of Things platform; According to the formula , calculate and obtain the performance optimization value of the IoT platform ,in , and is the preset proportional coefficient; Set a threshold for performance optimization value in advance; Optimize performance value The performance optimization value is compared with the threshold. If the performance optimization value If the performance is less than or equal to the performance optimization threshold, optimization measures are taken according to each indicator.

5. The data interaction system of an Internet of Things platform according to claim 4, characterized in that: The data management module also includes a subsequent adjustment unit, which is used to regularly review the performance data and perform further optimization, specifically: After the optimization measures of the management unit, the intercommunication unit and the optimization unit are taken, the difference between the IoT platform device interaction value S, the performance optimization value J and the efficiency management value R and the corresponding threshold is calculated and obtained. , and ; According to the formula , Calculate and obtain the comprehensive performance gap value M of the IoT platform; A threshold value of the comprehensive performance gap value is set in advance. If the comprehensive performance gap value M is greater than or equal to the threshold value of the comprehensive performance gap value, it is determined that the Internet of Things platform needs to be further optimized; Reset the thresholds of IoT platform device interaction value, performance optimization value, and efficiency management value; Then the data is transmitted to the management unit, the intercommunication unit and the optimization unit again for optimization until the optimized comprehensive performance gap value M is less than the threshold value of the comprehensive performance gap value.

6. The data interaction system of an Internet of Things platform according to claim 5, characterized in that: The specific manner in which the subsequent adjustment unit resets the threshold of the IoT platform device interaction value, the threshold of the performance optimization value, and the threshold of the efficiency management value is as follows: According to the formula , calculate and obtain the threshold growth rate of the IoT platform ,in represents the growth rate of the i-th indicator, represents the starting measurement value of the ith indicator, represents the current measured value of the i-th indicator, and N is the preset adaptation value; The threshold growth rate of each indicator after calculation Substitute into the management unit, the intercommunication unit and the optimization unit to obtain new thresholds of the device interaction value, the performance optimization value and the efficiency management value.

7. The data interaction system of the Internet of Things platform according to claim 6, characterized in that: The specific method of obtaining the fitness value N is as follows: Get the cost value of the IoT platform ; Get the technical limit value of the IoT platform ; Get the business demand indicator value of the IoT platform ; According to the formula , calculate and obtain the fitness value N, where , and is the preset scaling factor.

8. The data interaction system of an Internet of Things platform according to claim 2, characterized in that: The security module includes an IoT platform security unit and a data protection unit. The data protection unit is used to encrypt data in the IoT, specifically: Storage encryption, by encrypting the stored data using AES; The Internet of Things platform security unit is used to comprehensively calculate and reflect the security status of the Internet of Things devices.

9. The data interaction system of the Internet of Things platform according to claim 8, characterized in that: The specific method of storage encryption is: Device identity authentication; Data encryption; Privacy protection; Cybersecurity; Access control.

10. The data interaction system of the Internet of Things platform according to claim 8, characterized in that: The specific working mode of the data protection unit is as follows: According to the formula , get the security value A of the IoT platform, where is the total number of security dimensions; is the weight of the i-th security dimension; is the score value of the i-th security dimension; A safety value threshold is set in advance. If the real-time safety value A is less than the safety value threshold, an alarm signal is generated and transmitted to the staff's mobile phone terminal.

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