Carbon emission sensing system based on electric power data

Abstract

The invention discloses a carbon emission sensing system based on electric power data, and particularly relates to the technical field of carbon emission, the system comprises a data acquisition unit, a data transmission unit, a data preprocessing unit, a data storage unit, a data analysis unit and a result display unit, and the data acquisition equipment is used for transmitting the acquired data to the central processing system, ensuring that the data acquisition equipment can be stably connected with the central processing system, and ensuring that the format and the protocol of the data transmission are consistent based on the communication protocol. According to the carbon emission sensing system based on the electric power data, errors in the data transmission process are obtained and detected through the fault detection module in the data acquisition unit, measures are taken for recovery, and when the fault detection module determines that a fault occurs in the data transmission process, the fault detection module is matched with the fault detection module in the data acquisition unit. And the transmission data is backed up at the first time to ensure that important data cannot be lost.

Description

Technical Field

[0001] The present invention relates to the field of carbon emission technology, and in particular to a carbon emission sensing system based on power data. Background Art

[0002] Carbon emissions is a general term or abbreviation for greenhouse gas emissions, mainly referring to the greenhouse gas emissions generated during the production, transportation, use and recycling of a product. The most important gas is carbon dioxide. The basic principle of carbon emissions calculation is based on the amount of greenhouse gases emitted by a certain activity per unit space or per unit time. Greenhouse gases refer to gases that affect the earth's thermal balance and climate change, such as carbon dioxide, methane, freon, trifluoromethane, etc.

[0003] The existing carbon emission perception system based on electricity data usually needs to read the energy consumption data from smart meters, flow meters, sensor networks and other devices. Since the existing carbon emission perception system based on electricity data lacks a backup mechanism, when the data collection unit fails, there is no automatic backup mechanism, which may cause the loss of key data. Once the data is lost, it may not be restored through other means, affecting subsequent data analysis and decision-making;

[0004] At the same time, since the existing carbon emission perception system based on electricity data cannot send information to the staff in the first time when a fault occurs, manual discovery and processing of the fault is required, which increases the response time and recovery time. In addition, during the failure of the data acquisition unit, the data may be inconsistent, affecting the accuracy and reliability of the system. Therefore, the existing carbon emission perception system based on electricity data needs to be improved. Summary of the invention

[0005] The purpose of the present invention is to provide a carbon emission perception system based on electricity data to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a carbon emission perception system based on power data, the system comprising:

[0007] A data collection unit, used to obtain power consumption data and other relevant data, determine the energy consumption type of the government and the enterprise based on the registered information of the government and the enterprise, read the energy consumption data and energy consumption efficiency, and calculate the energy carbon emissions based on the energy consumption data and energy consumption efficiency of the government and the enterprise;

[0008] The data transmission unit is used to transmit the collected data to the central processing system. Based on the wired or wireless connection method and communication protocol, it ensures that the data collection equipment can establish a stable connection with the central system and ensures seamless communication and data exchange between different devices and systems;

[0009] The system further comprises a data preprocessing unit for removing noise and inconsistent data, the data preprocessing unit comprising:

[0010] Data cleaning module, which is used to read data from various data sources and load it into memory or data frame;

[0011] Data conversion module, used to convert non-numeric data into numeric data, convert date and time fields into standard formats, and extract useful features;

[0012] Feature engineering module, used to perform mathematical transformations on features;

[0013] Data partitioning module, which divides the data set into training set, validation set and test set;

[0014] The system also includes a data storage unit for storing a large amount of historical data and real-time data;

[0015] A data analysis unit, used to explore, model and interpret the data, view basic statistical information of the data based on the data analysis unit, and predict future data trends based on the viewed data;

[0016] The result display unit is used to display the analysis results to the user in the form of charts, reports, etc., and the result display unit is updated regularly based on time units.

[0017] Preferably, the data acquisition unit comprises:

[0018] The data transmission monitoring module is used to monitor the status of data transmission in real time to ensure the continuity and stability of data transmission;

[0019] A fault detection module, based on the transmission data of the monitoring data transmission module, obtains and detects errors in the data transmission process and takes measures to recover;

[0020] The automatic backup module automatically starts a backup mechanism based on the transmission data of the monitoring data transmission module and the data of the fault detection module after detecting a fault, and backs up the data to local or remote storage.

[0021] The data acquisition unit comprises:

[0022] A warning module, when the fault detection module detects a fault during data transmission, promptly issues a warning and notifies relevant personnel to handle the problem;

[0023] The recording module notifies relevant personnel to handle the problem based on the warning module and obtains data processed by relevant personnel. The recording module is used to record the detailed processing process and results after the relevant personnel solve the problem.

[0024] Preferably, the data cleaning module includes:

[0025] A data loading module, used to load data from various data sources and view basic information of the data based on the data collected by the data collection unit;

[0026] The missing value processing module is used to detect and process missing values ​​in the data based on the basic information of the data viewed by the data loading module.

[0027] Preferably, the data cleaning module includes:

[0028] An outlier processing module, based on the data processed by the missing value processing module, is used to delete outliers, correct outliers to reasonable values, retain outliers, and mark them;

[0029] A duplicate data processing module, based on the data processed by the abnormal value processing module, uses a unique identifier or a combination of multiple fields to detect duplicate records, delete duplicate records based on the duplicate records detected by the duplicate data processing module, and retain one record;

[0030] The data consistency checking module is based on the basic information of the data checked by the data loading module.

[0031] Preferably, the data conversion module includes:

[0032] A data type conversion module, based on the basic information of the data viewed by the data loading module, is used to convert non-numeric data into numeric data;

[0033] The encoding processing module is used to convert categorical variables into numerical representation;

[0034] The data normalization module is used to scale the data to a specific interval based on the data processed by the outlier processing module to ensure that the normalization maintains the relative relationship between the data, and is suitable for scenarios where relative proportions need to be maintained.

[0035] Preferably, the feature engineering module includes:

[0036] Feature engineering selection module, which is used to evaluate the importance of features and select the most relevant features;

[0037] The feature creation module creates new features based on the data characteristics transmitted by the data acquisition unit to increase the expressive power of the model.

[0038] The feature exchange module is used to perform mathematical transformation on features, improve data distribution, determine and improve data distribution, and reduce skew.

[0039] Preferably, the result display unit includes:

[0040] Display module, adopting modern UI / UX design principles;

[0041] Data visualization module, used to create dynamic charts and dashboards using data visualization tools;

[0042] The real-time update module is used to implement real-time update of data to ensure that users can obtain the latest information.

[0043] Preferably, the result display unit includes:

[0044] Multi-terminal support module, adopting responsiveness, using cross-platform framework to develop mobile applications;

[0045] The data encryption module adopts the HTTPS protocol to transmit data and uses encrypted storage and access control mechanisms to strengthen data security and privacy protection measures.

[0046] Compared with the prior art, the beneficial effects of the present invention are: the carbon emission perception system based on power data;

[0047] 1. Through the fault detection module in the data acquisition unit, errors in the data transmission process are detected and measures are taken to recover. In cooperation with the fault detection module in the data acquisition unit, when the fault detection module determines that a fault occurs during the data transmission process, the transmission data is backed up as soon as possible to ensure that important data will not be lost. At the same time, through the warning module, fault alarm information is sent to the staff as soon as possible to facilitate the staff to repair the system. Then, through the recording module, the relevant personnel can record the detailed processing process and results after solving the problem, so as to facilitate subsequent audits, analysis and improvements, thereby reducing the probability of the same problem occurring again in the subsequent system;

[0048] 2. The data conversion module in the data preprocessing unit converts data of different formats and standards into a unified format standard, which solves the problem that the data processing of the existing carbon emission perception system based on power data is too complicated and reduces the workload of subsequent data cleaning. At the same time, the data cleaning module in the data preprocessing unit removes or corrects invalid, erroneous or inconsistent data, thereby ensuring the uniqueness of the data and improving the authenticity of subsequent carbon emission data and the accuracy of the model;

[0049] 3. By setting up the display module in the result display unit, the user interface design is optimized to make it more intuitive. A good user interface can improve user satisfaction and participation. In conjunction with the data visualization module and the real-time update module, it ensures that users can understand complex carbon emission data more intuitively while obtaining the latest information in real time. Through the multi-terminal support module and the data encryption module, users can view carbon emission data at any time while protecting the security and privacy of user data, which can further increase user trust. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a structural block diagram of the carbon emission perception system based on power data;

[0051] Figure 2 It is a structural block diagram of the data acquisition unit in the carbon emission perception system based on power data;

[0052] Figure 3 This is a structural block diagram of the data preprocessing unit in the carbon emission perception system based on power data;

[0053] Figure 4 It is a structural block diagram of the data cleaning module in the data preprocessing unit;

[0054] Figure 5 It is a structural block diagram of the data conversion module in the data preprocessing unit;

[0055] Figure 6 This is a structural diagram of the feature engineering module in the data preprocessing unit;

[0056] Figure 7 This is a structural block diagram of the composition of the result display unit in the carbon emission perception system based on electricity data. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] See also Figure 1-2 The present invention provides a technical solution: a carbon emission perception system based on power data, wherein the system 1 comprises:

[0059] The data collection unit 11 is used to obtain power consumption data and other related data, determine the main energy consumption types of the government and enterprises, such as electricity, natural gas, coal, etc., based on the registered information of the government and enterprises; read the energy consumption data in the smart meters, flow meters, sensor networks and other equipment, and calculate the energy carbon emissions based on the energy consumption data and energy consumption efficiency of the government and enterprises, wherein the smart meters, flow meters, sensor networks and other equipment are updated regularly based on time units;

[0060] The data transmission unit 12 is used to transmit the collected data to the central processing system, and ensure that the data collection device can establish a stable connection with the central system based on wired connection and wireless connection, and ensure that the format and protocol of data transmission are consistent based on communication protocols such as Modbus, MQTT, etc., and ensure that different devices and systems can communicate and exchange data seamlessly based on transmission methods and communication protocols;

[0061] The system 1 further includes a data preprocessing unit 13 for removing noise and inconsistent data. The accuracy and reliability of the data are ensured based on the data preprocessing unit 13. The data preprocessing unit includes:

[0062] A data cleaning module 131 is used to read data from various data sources such as CSV files, databases, APIs, etc., and load it into memory or a data frame;

[0063] The data conversion module 132 is used to convert non-numeric data into numeric data, such as converting a string into an integer or a floating point number, converting a date and time field into a standard format, and extracting useful features such as year, month, day, hour, etc.;

[0064] A feature engineering module 133 is used to perform mathematical transformations on features to improve data distribution;

[0065] The data partitioning module 134 divides the data set into a training set, a validation set and a test set. The training set is used to train the model, the validation set is used to adjust the model parameters, and the test set is used to evaluate the final performance of the model.

[0066] The system 1 also includes a data storage unit 14 for storing a large amount of historical data and real-time data to ensure the security and integrity of the data. Based on the persistent storage medium such as a hard disk and SSD used by the data storage unit 14, it is ensured that the data can still be restored after a power outage;

[0067] Data analysis unit 15 is used to explore, model and interpret data to extract valuable information and insights. Based on data analysis unit 15, basic statistical information of data, such as mean, median, standard deviation, etc., is viewed, and based on the viewed data, future data trends are predicted;

[0068] The result display unit 16 is used to display the analysis results to the user in the form of charts, reports, etc. Based on the display method of the result display unit 16, the complex carbon emission data is displayed in an intuitive manner, wherein the result display unit 16 is updated regularly based on time units.

[0069] The data acquisition unit 11 includes:

[0070] The data transmission monitoring module 111 is used to monitor the status of data transmission in real time to ensure the continuity and stability of data transmission;

[0071] The fault detection module 112 detects errors in the data transmission process based on the transmission data of the monitoring data transmission module 111 and takes measures to recover;

[0072] The automatic backup module 113 automatically starts a backup mechanism based on the transmission data of the monitoring data transmission module 111 and the data detected by the fault detection module 112 to back up the data to local or remote storage;

[0073] The data acquisition unit 11 includes:

[0074] The warning module 114, when the fault detection module 112 detects a fault during data transmission, promptly issues a warning and notifies relevant personnel to handle the problem, thereby ensuring the stability and reliability of the system;

[0075] The recording module 115 notifies relevant personnel to handle the problem based on the warning module 114 and obtains the data processed by the relevant personnel. The recording module 115 is used for relevant personnel to record the detailed processing process and results after solving the problem, so as to facilitate subsequent audit, analysis and improvement.

[0076] The specific implementation method is as follows: through the fault detection module in the data acquisition unit, errors in the data transmission process are detected and measures are taken to recover. In cooperation with the fault detection module in the data acquisition unit, when the fault detection module determines that a fault occurs during data transmission, the transmission data is backed up as soon as possible to ensure that important data is not lost. At the same time, through the warning module, fault alarm information is sent to the staff as soon as possible to facilitate the staff to repair the system. Then, through the recording module, the relevant personnel can record the detailed processing process and results after solving the problem, so as to facilitate subsequent audits, analysis and improvements, thereby reducing the probability of the same problem occurring again in the subsequent system.

[0077] See also Figure 1-6 The present invention provides a technical solution: a carbon emission perception system based on power data, wherein the data cleaning module 121 includes:

[0078] The data loading module 1211 is used to load data from various data sources such as CSV files, databases, APIs, etc., and to view basic information of the data such as data shape, column name, data type, etc. based on the data collected by the data collection unit 11;

[0079] A missing value processing module 1212 is used to detect and process missing values ​​in the data based on the basic information of the data viewed by the data loading module 1211;

[0080] The data cleaning module 121 includes:

[0081] An outlier processing module 1213 is used to delete outliers, correct outliers to reasonable values, or retain outliers but mark them in the data based on the data processed by the missing value processing module 1212;

[0082] The duplicate data processing module 1214 detects duplicate records using a unique identifier or a combination of multiple fields based on the data processed by the outlier processing module 1213, and deletes duplicate records based on the duplicate records detected by the duplicate data processing module 1214, and retains one record;

[0083] The data consistency check module 1215 is used to ensure the correctness of the data type and the rationality of the data logic based on the basic information of the data checked by the data loading module 1211, for example, the date field should be of date type;

[0084] The data conversion module 122 includes:

[0085] The data type conversion module 1221 is used to convert non-numeric data into numeric data based on the basic information of the data checked by the data loading module 1211, such as converting a string into an integer or a floating point number;

[0086] The encoding processing module 1222 is used to convert the categorical variables into numerical representations;

[0087] The data normalization module 1223 is used to scale the data to a specific interval, such as [0, 1], based on the data processed by the outlier processing module 1213, to ensure that the normalization maintains the relative relationship between the data, which is suitable for scenarios where relative proportions need to be maintained;

[0088] The feature engineering module 123 includes:

[0089] A feature engineering selection module 1231 is used to evaluate the importance of features and select the most relevant features to ensure that the feature dimension is reduced and the training efficiency of the model is improved;

[0090] The feature creation module 1232 creates new features based on the data characteristics transmitted by the data acquisition unit 11, so as to increase the expression ability of the model and improve the prediction accuracy.

[0091] The feature exchange module 1233 is used to perform mathematical transformations on features to improve data distribution, determine improved data distribution, reduce skew, and make data more suitable for the assumptions of certain models.

[0092] The specific implementation method is as follows: data of different formats and standards are converted into a unified format standard through the data conversion module in the data preprocessing unit, which solves the problem that the data processing of the existing carbon emission perception system based on electricity data is too complicated and reduces the workload of subsequent data cleaning. At the same time, the data cleaning module in the data preprocessing unit is used to remove or correct invalid, erroneous or inconsistent data, thereby ensuring the uniqueness of the data and improving the authenticity of subsequent carbon emission data and the accuracy of the model.

[0093] See also Figure 1-7 The present invention provides a technical solution: a carbon emission perception system based on power data, wherein the result display unit 16 includes:

[0094] Display module 161 adopts modern UI / UX design principles, using clear layout, consistent color scheme and concise icons to ensure users can understand and operate quickly;

[0095] Data visualization module 162, used to create dynamic charts and dashboards using data visualization tools such as Tableau, Power BI, and D3.js, supporting multiple views and interaction methods, ensuring enhanced data visualization capabilities, and displaying data using charts, graphics, and animations;

[0096] A real-time update module 163 is used to implement real-time update of data to ensure that users can obtain the latest information;

[0097] The result display unit 16 includes:

[0098] The multi-terminal support module 164 adopts responsive design to ensure good performance of the interface on different devices and uses cross-platform frameworks such as React Native and Flutter to develop mobile applications;

[0099] The data encryption module 165 adopts the HTTPS protocol to transmit data and uses encrypted storage and access control mechanisms to strengthen data security and privacy protection measures.

[0100] The specific implementation method is as follows: By setting up the display module in the result display unit, the user interface design is optimized to make it more intuitive. A good user interface can improve user satisfaction and participation. In conjunction with the data visualization module and the real-time update module, it can ensure that users can understand complex carbon emission data more intuitively while obtaining the latest information in real time. Through the multi-terminal support module and the data encryption module, users can view carbon emission data at any time while protecting the security and privacy of user data, which can further increase user trust.

[0101] Working principle: When using the carbon emission perception system based on power data, firstly, the data acquisition unit 11 is used to obtain power consumption data and other related data, and cooperates with reading energy consumption data in smart meters, flow meters, sensor networks and other equipment, and calculates energy carbon emissions based on the energy consumption data and energy consumption efficiency of the government and enterprises. Then, the calculated carbon emission data is transmitted to the central processing system through the data transmission unit 12. During the data transmission process, the data transmission status is monitored in real time by monitoring the data transmission module 111. When the transmission data is transmitted to the fault detection module 112, the fault detection module 112 detects errors in the data transmission process and takes measures to recover;

[0102] At the same time, when the fault detection module 112 detects the faulty data, the automatic backup module 113 automatically starts the backup mechanism to back up the data to local or remote storage. Then, when the fault detection module 112 detects a fault during the data transmission process, the warning module 114 promptly issues a warning to notify relevant personnel to handle the problem, thereby ensuring the stability and reliability of the system. After the relevant personnel have completed the processing, the recording module 115 is used to record the detailed processing process and results after the relevant personnel have solved the problem, so as to facilitate subsequent auditing, analysis and improvement, thereby solving the problem of key data loss in the carbon emission perception system based on power data during the data transmission process.

[0103] When the data of the data acquisition unit 11 is accurately transmitted to the central processing system through the data transmission unit 12, the data passes through the data preprocessing unit 13 to remove noise and inconsistent data, and cooperates with the data cleaning module 131, the data conversion module 132, the feature engineering module 133, and the data partitioning module 134 to convert data of different formats and standards into a unified format standard, thereby solving the problem that the data processing of the existing carbon emission perception system based on power data is too complicated, reducing the workload of subsequent data cleaning, and at the same time, through the data cleaning module in the data preprocessing unit, removing or correcting invalid, erroneous or inconsistent data, thereby ensuring the uniqueness of the data and improving the authenticity of the subsequent carbon emission data and the accuracy of the model;

[0104] The data transmission unit 12 after the final processing checks the basic statistical information of the data, such as mean, median, standard deviation, etc., through the data storage unit 14 and the data analysis unit 15 in turn, and uses it to predict future data trends based on the checked data. Then, the predicted future carbon emission data is displayed to the user in the form of charts, reports, etc. through the display module 161 and the data visualization module 162 in the result display unit 16. The multi-terminal support module 164 and the data encryption module 165 in the result display unit 16 facilitate users to check the carbon emission data at any time, while protecting the security and privacy of user data, which can further increase the user's sense of trust.

[0105] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Carbon emission perception system based on power data, characterized by: The system (1) comprises: A data collection unit (11) is used to obtain power consumption data and other related data, determine the energy consumption type of the government and the enterprise based on the registered information of the government and the enterprise, read the energy consumption data and energy consumption efficiency, and calculate the energy carbon emissions based on the energy consumption data and energy consumption efficiency of the government and the enterprise; A data transmission unit (12) is used to transmit the collected data to the central processing system, based on a wired connection or a wireless connection and a communication protocol, to ensure that the data collection device can establish a stable connection with the central system, and to ensure that different devices and systems can communicate and exchange data seamlessly; The system (1) further comprises a data preprocessing unit (13) for removing noise and inconsistent data, the data preprocessing unit comprising: A data cleaning module (131) is used to read data from various data sources and load it into a memory or a data frame; A data conversion module (132), used to convert non-numeric data into numeric data, convert date and time fields into a standard format, and extract useful features; A feature engineering module (133) for performing mathematical transformations on features; A data partitioning module (134) divides the data set into a training set, a validation set and a test set; The system (1) further comprises a data storage unit (14) for storing a large amount of historical data and real-time data; A data analysis unit (15) is used to explore, model and interpret the data, and based on the data analysis unit (15), to view basic statistical information of the data, and to predict future data trends based on the viewed data; A result display unit (16) is used to display the analysis results to the user in the form of charts, reports, etc., and the result display unit (16) is updated regularly based on time units.

2. The carbon emission perception system based on power data according to claim 1 is characterized in that: The data acquisition unit (11) comprises: A data transmission monitoring module (111) is used to monitor the state of data transmission in real time to ensure the continuity and stability of data transmission; A fault detection module (112) is configured to detect errors in the data transmission process based on the transmission data of the monitoring data transmission module (111) and take measures to recover the errors; The automatic backup module (113) automatically starts a backup mechanism based on the transmission data of the monitoring data transmission module (111) and the data of the fault detection module (112) when the fault is detected, and backs up the data to local or remote storage.

3. The carbon emission perception system based on power data according to claim 2 is characterized in that: The data acquisition unit (11) comprises: A warning module (114) is configured to promptly issue a warning and notify relevant personnel to handle the problem when the fault detection module (112) detects a fault during data transmission; The recording module (115) notifies relevant personnel to handle the problem based on the warning module (114) and obtains data processed by the relevant personnel. The recording module (115) is used for the relevant personnel to record the detailed processing process and results after solving the problem.

4. The carbon emission perception system based on power data according to claim 1 is characterized in that: The data cleaning module (121) comprises: A data loading module (1211) is used to load data from various data sources and check basic information of the data based on the data collected by the data collection unit (11); The missing value processing module (1212) is used to detect and process missing values ​​in the data based on the basic information of the data viewed by the data loading module (1211).

5. The carbon emission perception system based on power data according to claim 4 is characterized in that: The data cleaning module (121) comprises: An outlier processing module (1213), based on the data processed by the missing value processing module (1212), is used to delete outliers, correct outliers to reasonable values, retain outliers, and mark them; A duplicate data processing module (1214) detects duplicate records based on the data processed by the abnormal value processing module (1213) using a unique identifier or a combination of multiple fields, and deletes duplicate records based on the duplicate records detected by the duplicate data processing module (1214) to retain one record; A data consistency checking module (1215) is based on the basic information of the data checked by the data loading module (1211).

6. The carbon emission perception system based on power data according to claim 1 is characterized in that: The data conversion module (122) comprises: A data type conversion module (1221), based on the basic information of the data viewed by the data loading module (1211), is used to convert non-numeric data into numeric data; An encoding processing module (1222) for converting categorical variables into numerical representations; The data normalization module (1223) is used to scale the data to a specific interval based on the data processed by the outlier processing module (1213), ensuring that the normalization maintains the relative relationship between the data, and is suitable for scenarios where relative proportions need to be maintained.

7. The carbon emission perception system based on power data according to claim 1 is characterized in that: The feature engineering module (123) comprises: A feature engineering selection module (1231) for evaluating the importance of features and selecting the most relevant features; The feature creation module (1232) creates new features based on the data characteristics transmitted by the data acquisition unit (11) to increase the expression ability of the model. The feature exchange module (1233) is used to perform mathematical transformation on the features to improve the data distribution, determine the improved data distribution, and reduce skew.

8. The carbon emission perception system based on power data according to claim 1 is characterized in that: The result display unit (16) comprises: Display module (161), using modern UI / UX design principles; A data visualization module (162) for creating dynamic charts and dashboards using data visualization tools; The real-time update module (163) is used to implement real-time update of data to ensure that users can obtain the latest information.

9. The carbon emission perception system based on power data according to claim 8 is characterized in that: The result display unit (16) comprises: The multi-terminal support module (164) adopts responsiveness and uses a cross-platform framework to develop mobile applications; The data encryption module (165) adopts the HTTPS protocol to transmit data and uses encrypted storage and access control mechanisms to strengthen data security and privacy protection measures.

Images