Remote intelligent management and control system for intelligent hotspot acquisition equipment based on communication module

Abstract

The invention discloses a remote intelligent management and control system for intelligent hotspot acquisition equipment based on a communication module, and relates to the technical field of communication hotspot management and control. Comprising a data acquisition module, a data processing module, a communication module, a management and control decision module, a remote monitoring module, a log recording module, a user management module, a system updating module, a data analysis and prediction module and a safety protection module. The system can collect various types of data of equipment, process and analyze the data, transmit the data through communication, perform decision control according to rules, remotely monitor and record the data, and guarantee the system safety and can be updated and optimized. According to the invention, comprehensive data acquisition and analysis, stable and secure transmission, intelligent decision control equipment, remote monitoring and early warning, data recording, user management, system updating, analysis and prediction can be realized, and equipment management level and operation reliability can be improved in multiple dimensions.

Description

Technical Field

[0001] The present invention relates to the technical field of communication device management and control, and particularly to a remote intelligent management and control system for intelligent hot spot collection devices based on communication modules. Background Art

[0002] In today's digital age, intelligent hot spot collection devices play a crucial role in many fields, such as smart city construction, commercial data collection, industrial Internet of Things monitoring, etc. Traditional intelligent hot spot collection devices mostly operate independently and lack effective remote management and control means. Operators often need to visit the device site in person and perform operations such as parameter setting, status checking, and data reading through local interfaces. This not only consumes a large amount of human and time costs, but also makes it difficult to achieve efficient and unified management for widely distributed devices. For example, for intelligent hot spot collection devices used for traffic flow monitoring in a city, if the collection frequency needs to be adjusted or the device operation status needs to be checked, staff need to go to the device installation location one by one, with low work efficiency and being easily affected by factors such as geographical environment and traffic conditions.

[0003] With the development of communication technology, some early attempts at remote management and control have emerged, but there are many limitations. These systems usually only support simple data transmission and cannot comprehensively collect rich operation status data, environmental data, and business data of the devices. Moreover, the communication stability is poor, and data transmission is prone to interruption or error in weak signal or complex electromagnetic environments. For example, some remote management and control systems using 2G or 3G communication technologies often experience data delay or loss due to poor signal in remote areas or urban areas with high-rise buildings, seriously affecting the remote management effect of the devices. At the same time, these systems lack intelligent management and control decision-making capabilities and cannot make timely and reasonable adjustments according to the actual operation conditions of the devices and environmental changes. They mostly rely on manual experience judgment and are difficult to meet the requirements of complex and changeable application scenarios.

[0004] Existing remote management and control systems for intelligent hot spot collection devices also have obvious deficiencies in security protection. Network attack means are becoming increasingly diverse and complex, and traditional systems are difficult to effectively resist the risks of external intrusion and data theft. For example, some criminals obtain sensitive device information through network vulnerabilities, interfere with the normal operation of the devices, and cause serious losses to related businesses. In addition, existing systems are weak in functions such as collaborative work between devices, energy consumption management, and fault diagnosis. They cannot achieve efficient cooperation between multiple devices, cannot effectively monitor and optimize the energy consumption of devices, and fault diagnosis is mostly after-the-fact processing, lacking forward-looking warnings, resulting in high device maintenance costs and low operation reliability. Therefore, it is extremely urgent to develop a remote intelligent management and control system for intelligent hot spot collection devices based on communication modules with complete functions, high intelligence, and security and reliability. Summary of the Invention

[0005] The remote intelligent management and control system for intelligent hotspot acquisition devices based on communication modules proposed by the present invention aims to solve the problems mentioned in the above prior art.

[0006] To achieve the above object, the present invention adopts the following technical solutions: A remote intelligent management and control system for intelligent hotspot acquisition devices based on communication modules, comprising: Data acquisition module: Collects the operating status data, environmental data, and business data of the hotspot acquisition device through sensors and data interfaces; the operating status data includes the voltage, current, temperature, and humidity of the device, the environmental data covers the light intensity and air quality at the location where the device is located, and the business data includes the number of hotspot information collected and the data transmission rate. The collected data is transmitted to the data processing module through the data interface; Data processing module: Preprocesses and analyzes the collected data. First, data cleaning is performed to remove noise data and outliers; the 3σ criterion based on statistical analysis is adopted, and data points exceeding the mean ± 3 times the standard deviation are determined as outliers. The formula is: , where is the data mean, is the data standard deviation. For outliers, linear interpolation is used for repair. The formula is: , where and are known data points, and x is the interpolation point to be interpolated; then feature extraction and classification of the data are performed, and machine learning algorithms are used to classify the data according to its characteristics into different categories to provide a basis for subsequent management and control decisions; Communication module: Implements data transmission between the hotspot acquisition device and the remote management and control center using communication technologies; the communication module is equipped with an automatic communication mode switching function to select the communication mode according to the network signal strength and communication cost; the communication module supports encrypted data transmission and uses the AES encryption algorithm to encrypt the transmitted data. The formula is: , where C is the ciphertext, K is the encryption key, and P is the plaintext; Management and control decision module: Formulates management and control decisions based on the analysis results of the data processing module, in combination with preset management and control rules and strategies; the management and control rules and strategies include the startup, stop, and parameter adjustment of the device; a fuzzy control algorithm is used to dynamically adjust the parameters of the device according to the operating status and environmental data of the device; Remote monitoring module: Builds a monitoring platform in the remote management and control center to display the operating status, data acquisition situation, and management and control decision execution situation of the hotspot acquisition device in real time; the monitoring platform uses a visual interface to display data in the form of charts and reports, facilitating monitoring and analysis by management personnel; at the same time, the monitoring platform is equipped with an alarm function to send alarm messages when the device operating status is abnormal or the data exceeds the preset threshold; Logging Module: Records the operation data, control decisions, and alarm information of the hotspot collection device; The logging is stored in a database, and the log records include time, event type, and event details information, providing historical data support for the maintenance and management of the device; User Management Module: Manages the users who use the remote control system; User management includes user registration, login, and permission allocation functions, and different operation permissions are assigned according to the roles and responsibilities of the users; System Update Module: Periodically updates and upgrades the remote control system; System updates include software version updates, control rules and policy updates; The system update adopts the method of automatic download and installation, and at the same time, the system update is equipped with a rollback function to restore to the previous stable version when problems occur during the update; Data Analysis and Prediction Module: Analyzes and mines historical data, uses data mining algorithms to discover the relationships and patterns between data; At the same time, machine learning algorithms are used to predict the operation status and business data of the device, providing decision-making support for the maintenance and management of the device. The prediction results are displayed in the form of reports and visual charts; Security Protection Module: Protects the remote control system from security threats, preventing the system from being attacked by the network and data leakage; Security protection measures include firewall settings, intrusion detection, and data backup. The firewall uses a stateful inspection firewall to monitor and filter network traffic in real time. The intrusion detection system uses rule-based and machine learning-based detection methods, and data backup adopts a combination of regular backup and real-time backup.

[0007] Furthermore, it also includes: Device Location Module: Adopts GPS or Beidou positioning technology to obtain the geographical location information of the hotspot collection device in real time; The geographical location information is transmitted to the remote control center through the communication module and displayed on the monitoring platform in the form of a map; At the same time, the device location module is equipped with an electronic fence function to send an alarm message to notify the management personnel for handling when the device exceeds the preset geographical location range.

[0008] Energy Consumption Management Module: Monitors and manages the energy consumption of the hotspot collection device in real time; By installing energy consumption sensors, the energy consumption data of the device is collected, and energy consumption analysis algorithms are used to analyze the energy consumption situation of the device, and energy consumption optimization strategies are formulated according to the analysis results.

[0009] Fault diagnosis module: Adopt fault diagnosis algorithms to conduct real-time diagnosis and early warning of the faults of the hotspot acquisition devices; the fault diagnosis algorithms combine the operation status data, historical fault data, and expert knowledge base of the devices, and judge whether there are faults, the types and locations of the faults in the devices through pattern recognition and reasoning; when a fault is diagnosed in the device, an alarm message is sent and fault handling suggestions are provided; at the same time, the fault diagnosis module is equipped with a fault prediction function, using machine learning algorithms to predict the probability of device faults, providing early warning for the maintenance and management of the devices.

[0010] Device collaboration module: Realize the collaborative work and resource sharing among the hotspot acquisition devices, and conduct data exchange and information sharing among the devices through the communication module; according to the operation status and task requirements of the devices, adopt collaborative optimization algorithms to allocate and schedule the work tasks of the device group to achieve the overall work efficiency and performance of the devices.

[0011] Furthermore, it also includes: Configuration module: Allow managers to configure the hotspot acquisition devices through the remote control center. The managers select preset configuration templates or customize configuration parameters according to the types, uses, and working environments of the devices; the configuration parameters include the acquisition frequency of the sensors, the working modes of the communication modules, control rules, and strategies; the configuration module sends the configuration parameters to the devices through the communication module to achieve the configuration and deployment of the devices.

[0012] Environment adaptation module: Automatically adjust the working parameters and operation modes of the devices according to the environmental conditions where the hotspot acquisition devices are located. The environmental conditions include temperature, humidity, and light intensity; use environmental perception sensors to collect environmental data in real time, and dynamically adjust the working parameters of the devices according to the environmental data using fuzzy control algorithms to enable the devices to operate normally under different environmental conditions.

[0013] Data visualization module: Display the collected data and analysis results to managers in a visual way. The data visualization methods include line charts, bar charts, pie charts, and maps; select the visualization method for display according to the types and characteristics of the data; the data visualization module is equipped with an interaction function, and managers can understand the data information by clicking on the charts and filtering the data.

[0014] Emergency handling module: Quickly take emergency handling measures in case of emergencies. The emergency handling measures include the emergency stop of the devices, data backup and recovery, and communication mode switching; the emergency handling module is equipped with an emergency plan library, and automatically calls the corresponding emergency plan for handling according to different emergencies; at the same time, the emergency handling module sends emergency handling information to managers.

[0015] Cloud service integration module: Through the integration of the remote management and control system and the cloud service platform, data storage, analysis and sharing can be realized; the cloud service platform provides computing power and storage space to process equipment operation data and business data; through the cloud service integration module, managers can access the remote management and control system through the Internet at any time and any place to conduct equipment monitoring, management and control decisions and data analysis operations.

[0016] Compared with the prior art, the present invention has the following beneficial effects: In terms of data collection and processing, it can comprehensively and accurately collect various types of equipment operation data, environmental data and business data, and use advanced algorithms to efficiently clean, analyze and classify them, providing detailed and reliable basis for subsequent management and control decisions, helping to timely discover potential equipment problems and optimize business processes.

[0017] The communication module greatly improves the data transmission efficiency. It supports multiple communication technologies such as 4G, 5G, WiFi, etc. and can switch automatically to ensure stable and efficient data transmission. At the same time, it uses encryption algorithms to ensure data security, effectively preventing data from being stolen or tampered with during transmission, and improving the overall security of the system.

[0018] The control decision module uses intelligent algorithms such as fuzzy control to accurately formulate and execute control decisions based on the actual operating status of the equipment and environmental changes. For example, it can automatically adjust the equipment's operating parameters to deal with situations such as overtemperature and overload, ensuring that the equipment is always in the best operating state, reducing equipment failures and extending equipment life.

[0019] The remote monitoring module uses a visual interface to enable managers to understand the equipment operation status, data collection, and execution of management and control decisions in real time and intuitively. Combined with timely alarm functions, it is easy to quickly discover and handle abnormalities and improve management efficiency.

[0020] The log recording module records the key information of equipment operation in detail, providing complete historical data support for equipment maintenance, troubleshooting and performance optimization, making it easier to trace the root cause of the problem and summarize lessons learned.

[0021] The user management module accurately allocates permissions based on user roles to ensure safe and standardized system operations and prevent unauthorized operations from damaging devices and data. The system update module regularly updates the system, continuously optimizes functions, and has a rollback function to ensure that the update process is stable and reliable.

[0022] The data analysis and prediction module mines the value of historical data, predicts the operation trend of the device, provides scientific predictions for device maintenance and business planning, and prevents potential problems in advance. The security protection module adopts multiple protection measures, such as firewalls and intrusion detection, to effectively resist network attacks and ensure system and data security. New modules such as device positioning, energy consumption management, and fault diagnosis improve the device management level from multiple dimensions, achieving precise device positioning, energy consumption optimization, fault warning, and rapid diagnosis and repair, comprehensively enhancing the reliability of device operation and the degree of management intelligence. Brief Description of the Drawings

[0023] Figure 1 It is a schematic block diagram of a remote intelligent control system for an intelligent hotspot acquisition device based on a communication module proposed by the present invention. Detailed Embodiment

[0024] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0025] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be understood as a limitation of the present invention.

[0026] In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more, unless otherwise specifically defined. In addition, the terms "installation", "connection", and "connection" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected, or indirectly connected through an intermediate medium, and it may be the internal communication of two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The present invention will be further described in detail below with reference to the drawings.

[0027] Refer to Figure 1 : Specific implementation of a remote intelligent control system for an intelligent hotspot acquisition device based on a communication module I. Data acquisition module Inside and around the intelligent hotspot acquisition device, various sensors are reasonably deployed. For operation status monitoring, high-precision voltage and current sensors are selected, which can accurately measure the voltage and current of the device's power supply, with a measurement accuracy of up to ±0.01V and ±0.01A. The temperature sensor uses the DS18B20 model, with a measurement accuracy of ±0.1°C, and the internal and surrounding environment temperature is collected every 5 minutes. The humidity sensor selects the HIH-4000, with a measurement accuracy of ±2%RH, and humidity data is also collected every 5 minutes. For environmental data acquisition, the light intensity sensor selects the BH1750, which can accurately measure the light intensity of 0 - 65535lx, and is collected every 10 minutes. The air quality sensor uses the MQ-135, which can monitor air quality indicators such as the concentration of harmful gases in real time, and the collection frequency is once every 10 minutes. In terms of business data, through the data statistics interface inside the device, the number of hotspot information collected and the data transmission rate are obtained every 10 minutes. All data collected by the sensors is transmitted to the data processing module through the data interfaces adapted by SPI, I2C, etc. with a stable communication protocol according to their types.

[0028] II. Data processing module After receiving the acquisition data, the data processing module first performs data cleaning. Taking the temperature data as an example, assuming the temperature data sequence collected within a period of time is , first calculate the mean of this sequence, and then calculate the standard deviation . According to the 3σ criterion, if a certain temperature value satisfies or , then it is determined that is an outlier. For outliers, the linear interpolation method is used for repair. For example, if is an outlier, its two adjacent normal data points are and , and the corresponding time points are , , , then the repaired temperature value . The cleaned data is subjected to feature extraction and classification. Taking the decision tree algorithm as an example, for the device operation status data, features such as voltage, current, temperature, and humidity are used as the input nodes of the decision tree, and the results of normal or abnormal operation of the device in the historical data are used as the output labels to construct a decision tree model. Through this model, the newly collected data is classified to determine whether the current operation status of the device is normal.

[0029] Data processing stage Proportion of outliers Repair accuracy rate Classification accuracy rate Before cleaning Approximately 8% - - After cleaning Approximately 1% Approximately 95% Approximately 90% As can be seen from the table data, the proportion of outliers before cleaning is relatively high. After being processed by the 3σ criterion and the linear interpolation method, the proportion of outliers has been significantly reduced, and the repair accuracy is high. The decision tree algorithm has an accuracy rate of 90% for data classification, indicating that the data processing module can effectively improve the data quality and provide a reliable data basis for subsequent control decisions.

[0030] III. Communication Module The communication module selects a commercial module that supports multiple communication technologies such as 4G, 5G, and WiFi, such as the EC200U-CN of Quectel Wireless Solutions Co., Ltd. (supporting 5G). A signal strength monitoring program is set inside the module to monitor the signal strengths of 4G, 5G, and WiFi in real time. When the 4G signal strength is lower than -100 dBm, it automatically detects the signal strengths of 5G and WiFi. If the 5G signal strength is higher than -90 dBm and the WiFi signal strength is higher than -70 dBm, it preferentially switches to the 5G mode; if the 5G signal is poor while the WiFi signal is good, it switches to the WiFi mode. In terms of data transmission security, the AES encryption algorithm is adopted. At the data sending end, the data to be transmitted (set as plaintext P) and the 128-bit encryption key K are used as the inputs of the AES encryption function E, that is, \(C = E(K, P)\), and the ciphertext C is generated and then transmitted. At the receiving end, the same key K is used to decrypt the ciphertext C through the decryption function to restore the plaintext P.

[0031] Communication mode Signal strength range (dBm) Average transmission rate (Mbps) Number of data transmission security incidents after encryption 4G -80--100 Approximately 10 0 5G -60--90 Approximately 100 0 WiFi -50--70 Approximately 50 0 As can be seen from the table, different communication modes have stable transmission rates within the corresponding signal strength ranges, and no data transmission security accidents have occurred after AES encryption, ensuring the efficiency and security of data transmission.

[0032] IV. Control Decision Module In the server of the remote control center, a large amount of historical data on the operating status of devices and corresponding control strategies is pre-stored to build a fuzzy control rule base. For example, for the fuzzy control of device temperature and working power. The fuzzy linguistic variables of temperature are set as "low", "medium", and "high", and the fuzzy linguistic variables of working power are set as "low power", "medium power", and "high power". When the temperature sensor feeds back that the device temperature is in the "high" state, according to the fuzzy control rule base, fuzzy reasoning is used to obtain that the device working power should be reduced to the "low power" state.

[0033] In specific implementation, the control decision module receives the device status classification result transmitted by the data processing module, and combines it with the fuzzy control algorithm to generate a control instruction. For example, if it is determined that the device temperature is too high, an instruction to reduce the working power is sent to the intelligent hotspot acquisition device through the communication module, and the device automatically adjusts the working power after receiving the instruction.

[0034] Device status Parameters before adjustment Parameters after adjustment Change in device performance Excessive temperature High working power Low working power Temperature decreases and the device runs stably Low data transmission rate Standard configuration Optimized configuration Transmission rate improvement As can be seen from the table, the adjustments made by the control decision-making module based on the device status effectively improve the device performance and ensure the stable and efficient operation of the device.

[0035] V. Remote Monitoring Module In the remote control center, a monitoring platform is built using Web development technology. The front-end interface is written in HTML, CSS, and JavaScript, and data is presented in an intuitive chart form. For example, line charts are used to show the changes in device voltage and current over time, bar charts are used to present the statistical quantity of hotspot information, and maps are used to mark the geographical locations of devices. The back-end uses the Flask framework of Python, which is responsible for obtaining real-time device data from the database and transmitting the data to the front-end for display.

[0036] The monitoring platform sets alarm thresholds, such as when the device temperature exceeds 60°C or the voltage exceeds the normal range by ±5%. When the data exceeds the threshold, an alarm message is sent to the manager's mobile phone through a SMS interface (such as Alibaba Cloud SMS Service), and at the same time, the alarm information is displayed in a prominent red warning box on the monitoring platform interface.

[0037] Monitoring content Data update frequency Alarm response time User operation convenience score (out of 10) Device operation status 1 minute Approximately 5 seconds 8 points Data collection situation 5 minutes Approximately 5 seconds 8 points As can be seen from the table, the monitoring platform has a high data update frequency, a rapid alarm response, and a high score for the convenience of user operation, providing an efficient monitoring means for managers.

[0038] VI. Log Record Module The MySQL database is selected to build a log storage system. Multiple tables are created in the database to record device operation logs, control decision logs, and alarm logs respectively. The device operation log table records operation data such as time, device ID, voltage, current, temperature, and humidity; the control decision log table records time, device ID, and the content of the issued control instructions; the alarm log table records time, device ID, alarm type, and alarm details.

[0039] Each time new data is generated or an event occurs, the pymysql library of Python is used to connect to the MySQL database, and the relevant information is inserted into the corresponding table. For example, when an abnormal temperature alarm occurs for a device, information such as the alarm time, device ID, "temperature abnormal" alarm type, and specific temperature value is inserted into the alarm log table.

[0040] Log type Number of log records (per day) Query response time (seconds) Data integrity Device operation log Approximately 1000 Approximately 0.5 100% Management decision log Approximately 100 Approximately 0.3 100% Alarm log Approximately 50 Approximately 0.2 100% As can be seen from the table, the log record module can record a large amount of information every day, has a rapid query response, and the data integrity reaches 100%, providing detailed and reliable historical data for device maintenance management.

[0041] VII. User Management Module Deploy the user management system on the remote control center server. When users register, they are required to enter information such as username, password, email, and their assigned role (administrator or ordinary user). The password is encrypted and stored using the SHA-256 encryption algorithm to ensure the security of user information.

[0042] When users log in, the system verifies whether the entered username and encrypted password match the information stored in the database. For administrator users, all operation permissions such as system settings, user management, and device parameter adjustment are granted; ordinary users can only view device operation data and receive alarm information. Through the user management system, it is ensured that only authorized users can perform corresponding operations on the system.

[0043] User role Number of operation permissions Login verification accuracy rate Number of system operation security incidents Administrator 10 100% 0 Ordinary user 3 100% 0 As can be seen from the table, the user management module can accurately allocate permissions, has a high accuracy rate for login verification, and no system operation security incidents have occurred due to improper permission management.

[0044] VIII. System Update Module Set up a system update server in the remote control center to regularly download the latest system software versions, control rules, and policy update files from the official website of the software developer. After the update files are downloaded, the update packages are pushed to the servers where each intelligent hotspot collection device and the remote monitoring platform are located through the internal network.

[0045] During the update process, key data in the devices and servers is first backed up. After the update is completed, functional tests are automatically performed. If problems are found during the tests, rollback operations are executed using the backup data to restore to the previous stable version. For example, when the control rules are updated, various operating states of the device are simulated to verify whether the control decisions are accurate. If decision-making errors occur, the update is rolled back.

[0046] Update cycle Number of system function optimizations Update success rate Rollback operation success rate Once a month Approximately 3 Approximately 95% Approximately 100% As can be seen from the table, the system update module is updated once a month, can effectively optimize the system functions, has a high update success rate, and the rollback operation success rate reaches 100%, ensuring the stability and reliability of the system update process.

[0047] IX. Data Analysis and Prediction Module Use libraries such as pandas, numpy, and scikit-learn in Python for data analysis and prediction. For historical device operation data, the Apriori algorithm for association rule mining is used to find potential associations between different operating parameters. For example, it is found that when the device voltage continuously drops below a certain threshold and the current is higher than another threshold, the probability of device failure increases significantly.

[0048] In terms of prediction, the time series analysis algorithm ARIMA is adopted. Taking the equipment temperature prediction as an example, based on the historical temperature data series, the parameters p, d, q of the ARIMA model are determined through the autocorrelation function (ACF) and partial autocorrelation function (PACF), and the ARIMA(p, d, q) model is constructed to predict the equipment temperature change in the future period. The prediction results are presented in the form of a report, and at the same time, a line chart is used to show the comparison between the predicted temperature and the actual temperature, which is convenient for managers to analyze.

[0049] Analysis and prediction type Number of association rules discovered Prediction accuracy rate Association rule mining Approximately 5 per month - Time series prediction Approximately 85% - As can be seen from the table, the data analysis and prediction module can mine multiple association rules every month, and the accuracy rate of time series prediction reaches 85%, providing valuable reference for equipment maintenance management.

[0050] X. Security Protection Module A stateful inspection firewall is deployed at the network entrance of the remote control center, such as the Deep Security AF series firewall. The firewall monitors network traffic in real time, deeply inspects each data packet, and filters out illegal access requests according to the preset security policies. For example, unauthorized access from the external network to the equipment management port is prohibited.

[0051] At the same time, an intrusion detection system (IDS) is deployed, such as Snort IDS. The IDS adopts detection methods based on rules and machine learning. On the one hand, it matches network traffic according to the known attack feature rule library, and on the other hand, it uses machine learning algorithms to learn the normal network traffic patterns, and issues an alarm in a timely manner when abnormal traffic appears.

[0052] In terms of data backup, a combination of regular full backup and real-time incremental backup is adopted. A full backup is performed every night, and the database files are backed up to an external storage device; real-time incremental backup uses the built-in log function of the database to back up the newly generated data changes to another storage location in real time.

[0053] Security protection measures Number of attack interceptions (per month) Intrusion detection accuracy rate Data recovery success rate Firewall Approximately 20 - - Intrusion detection system Approximately 15 Approximately 90% - Data backup and recovery - - Approximately 100% As can be seen from the table, the firewall and intrusion detection system effectively intercept attacks, the intrusion detection accuracy rate is high, and the data backup and recovery success rate reaches 100%, ensuring the security of the system and data.

[0054] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. A remote intelligent control system for intelligent hotspot collection equipment based on a communication module, characterized in that: include: Data acquisition module: collects the operating status data, environmental data and business data of the hotspot acquisition equipment through sensors and data interfaces; the operating status data includes the voltage, current, temperature and humidity of the equipment; the environmental data includes the light intensity and air quality of the location of the equipment; the business data includes the number of hotspot information collected and the data transmission rate; the collected data is transmitted to the data processing module through the data interface; Data processing module: pre-process and analyze the collected data. First, perform data cleaning to remove noise data and outliers. Use the 3σ criterion based on statistical analysis to determine data points that exceed the mean ±3 times the standard deviation as outliers. The formula is: ,in is the data mean, is the data standard deviation. For outliers, linear interpolation is used to repair them. The formula is: ,in and is a known data point, and x is a point to be interpolated. Then, the data is feature extracted and classified, and a machine learning algorithm is used to classify the data into different categories according to the characteristics of the data to provide a basis for management and control decisions. Communication module: Communication technology is used to realize data transmission between hotspot collection equipment and remote control center; the communication module is equipped with automatic switching communication mode function, and the communication mode is selected according to the network signal strength and communication cost; The communication module supports data encryption transmission and uses the AES encryption algorithm to encrypt the transmitted data. The formula is: , where C is the ciphertext, K is the encryption key, and P is the plaintext; Management and control decision module: Make management and control decisions based on the analysis results of the data processing module and combined with preset management and control rules and strategies; management and control rules and strategies include equipment start, stop, and parameter adjustment; use fuzzy control algorithms to dynamically adjust equipment parameters based on the equipment's operating status and environmental data.

2. According to claim 1, the remote intelligent management and control system of intelligent hotspot acquisition equipment based on the communication module is characterized in that: Also includes: Remote monitoring module: A monitoring platform is built in the remote control center to display the operating status of hotspot collection equipment, data collection status, and execution of control decisions in real time; the monitoring platform uses a visual interface to display data in the form of charts and reports, which is convenient for managers to monitor and analyze; at the same time, the monitoring platform is equipped with an alarm function, which will issue an alarm message when the equipment operating status is abnormal or the data exceeds the preset threshold; Log recording module: logs the operation data, management and control decisions and alarm information of hotspot collection equipment; log records are stored in a database and include time, event type, and event details, providing historical data support for equipment maintenance and management; User management module: manages users who use the remote control system; user management includes user registration, login, and permission allocation functions, and allocates different operation permissions according to the user's role and responsibilities; System update module: regularly update and upgrade the remote control system; system updates include software version updates, control rules and policy updates; system updates are automatically downloaded and installed, and the system updates are equipped with a rollback function to restore to the previous stable version when problems occur during the update; Data analysis and prediction module: Analyze and mine historical data, use data mining algorithms to discover the relationships and patterns between data; use machine learning algorithms to predict the operating status and business data of equipment, and provide decision support for equipment maintenance and management; the prediction results are displayed in the form of reports and visual charts; Security protection module: Provide security protection for the remote control system to prevent the system from network attacks and data leakage; security protection measures include firewall settings, intrusion detection, and data backup. The firewall uses a stateful detection firewall to monitor and filter network traffic in real time. The intrusion detection system uses a detection method based on rules and machine learning. Data backup uses a combination of regular backup and real-time backup. Equipment positioning module: using GPS or Beidou positioning technology to obtain the geographical location information of hotspot collection equipment in real time; The geographic location information is transmitted to the remote control center through the communication module, and the location of the equipment is displayed in the form of a map on the monitoring platform; at the same time, the equipment positioning module is equipped with an electronic fence function. When the equipment exceeds the preset geographic location range, an alarm message is issued to notify the management personnel for processing.

3. According to claim 1, the remote intelligent management and control system of intelligent hotspot acquisition equipment based on the communication module is characterized in that: Also includes: Energy consumption management module: real-time monitoring and management of energy consumption of hotspot collection equipment; By installing energy consumption sensors, the energy consumption data of the equipment is collected, and the energy consumption of the equipment is analyzed using energy consumption analysis algorithms. Energy consumption optimization strategies are formulated based on the analysis results.

4. According to claim 1, the remote intelligent management and control system of intelligent hotspot acquisition equipment based on the communication module is characterized in that: Also includes: Fault diagnosis module: Use fault diagnosis algorithm to perform real-time diagnosis and early warning of faults in hotspot acquisition equipment; The fault diagnosis algorithm combines the equipment's operating status data, historical fault data and expert knowledge base, and determines whether the equipment has a fault and the type and location of the fault through pattern recognition and reasoning. When a fault is diagnosed in the equipment, an alarm message is issued and fault handling suggestions are provided. At the same time, the fault diagnosis module is equipped with a fault prediction function, which uses machine learning algorithms to predict the probability of equipment failure and provide early warning for equipment maintenance and management.

5. According to claim 1, the remote intelligent management and control system of intelligent hotspot acquisition equipment based on the communication module is characterized in that: Also includes: Equipment collaboration module: realizes collaborative work and resource sharing between hotspot collection devices, and exchanges data and shares information between devices through communication modules; according to the operating status and task requirements of the equipment, a collaborative optimization algorithm is used to allocate and schedule the work tasks of the equipment group to achieve the overall work efficiency and performance of the equipment.

6. The remote intelligent management and control system for intelligent hotspot collection equipment based on a communication module according to claim 1 is characterized in that: Also includes: Configuration module: allows managers to configure hotspot collection devices through the remote control center. Managers select preset configuration templates or customize configuration parameters based on the type, purpose and working environment of the equipment; configuration parameters include the collection frequency of the sensor, the working mode of the communication module, and control rules and policies; the configuration module sends the configuration parameters to the device through the communication module to realize the configuration and deployment of the device.

7. The remote intelligent management and control system for intelligent hotspot collection equipment based on a communication module according to claim 1, characterized in that: Also includes: Environmental Adaptation Module: Automatically adjusts the working parameters and operation mode of the equipment according to the environmental conditions of the hotspot collection equipment, including temperature, humidity, and light intensity; uses environmental perception sensors to collect environmental data in real time, and uses fuzzy control algorithms to dynamically adjust the working parameters of the equipment based on the environmental data, so as to achieve normal operation of the equipment under different environmental conditions.

8. The remote intelligent management and control system for intelligent hotspot collection equipment based on a communication module according to claim 1, characterized in that: Also includes: Data visualization module: The collected data and analysis results are displayed to managers in a visual way. Data visualization methods include line graphs, bar graphs, pie charts, and maps. The visualization method is selected according to the type and characteristics of the data. The data visualization module is equipped with interactive functions, and managers can understand data information by clicking on charts and filtering data.

9. The remote intelligent management and control system for intelligent hotspot acquisition equipment based on a communication module according to claim 1, characterized in that: Also includes: Emergency handling module: Take emergency handling measures quickly when encountering emergencies. Emergency handling measures include emergency stop of equipment, backup and recovery of data, and switching of communication modes. The emergency handling module is equipped with an emergency plan library, which automatically calls emergency plans for handling according to different emergencies. At the same time, the emergency handling module sends emergency handling information to management personnel.

10. The remote intelligent management and control system for intelligent hotspot collection equipment based on communication module according to claim 1, characterized in that: Also includes: Cloud service integration module: integrates the remote management and control system with the cloud service platform to achieve data storage, analysis and sharing; The cloud service platform provides computing power and storage space to process equipment operation data and business data; through the cloud service integration module, managers can access the remote management and control system through the Internet to perform equipment monitoring, management and control decisions, and data analysis operations.

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