Internet of Things equipment integrated management system and method for road construction

Abstract

The invention relates to the technical field of Internet of Things, in particular to an Internet of Things equipment integrated management system and method for road construction, and the system comprises an equipment access module, a data collection module, a monitoring and diagnosis module, a remote control module and a safety management module. The equipment access module is used for accessing various types of equipment on a construction site to the Internet of Things to realize networking and unified management of the construction equipment; the data acquisition module is used for acquiring data of construction equipment in real time and transmitting the data to the cloud server; the monitoring and diagnosis module is used for analyzing the collected data, monitoring the operation state of the construction equipment in real time, identifying and diagnosing equipment faults and providing preventive maintenance suggestions; the remote control module supports remote operation and control of construction equipment and realizes control of the construction equipment; and the security management module guarantees the transmission and storage security of the data through encryption and access control technologies.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to an Internet of Things equipment integrated management system and method thereof for highway construction. Background Art

[0002] In the field of highway construction, traditional equipment management methods usually rely on manual inspections and manual records, which is not only inefficient but also prone to omissions or errors. At the same time, most of the existing highway construction equipment operates independently and lacks effective networking and data sharing functions, making real-time monitoring and management of equipment difficult. At the same time, due to the complex and changeable highway construction environment, equipment failures, construction safety accidents and other problems frequently occur, and there is an urgent need for a system that can monitor and intelligently manage construction equipment in real time to improve the safety and management efficiency of the construction site.

[0003] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0004] The purpose of the present invention is to provide an Internet of Things equipment integrated management system and method for highway construction to solve the technical problems existing in the prior art.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] In the first aspect, the present invention provides an Internet of Things equipment integrated management system for highway construction, which includes an equipment access module, a data acquisition module, a monitoring and diagnosis module, a remote control module and a security management module; the equipment access module is used to connect various types of equipment at the construction site to the Internet of Things to realize the networking and unified management of construction equipment; the data acquisition module is used to collect data of construction equipment in real time and transmit the data to a cloud server; the monitoring and diagnosis module is used to analyze the collected data, monitor the operating status of construction equipment in real time, identify equipment failures and diagnose them, and provide preventive maintenance suggestions; the remote control module supports remote operation and control of construction equipment to realize control of construction equipment; the security management module ensures the transmission and storage security of data through encryption and access control technology.

[0007] Preferably, the device access module includes: a device communication module and a device identification and registration module; the device communication module is arranged on the construction equipment, and the device communication module supports the MQTT protocol so that the construction equipment can be stably connected to the system network; the device identification and registration module generates a unique device identifier for each construction equipment, which is used for the identification and management of the construction equipment; after the construction equipment is connected to the system through the device communication module, the basic information of the construction equipment will be entered into the system database to ensure the classified management of the construction equipment.

[0008] Preferably, the data acquisition module includes: a sensor component, a data transmission module, and a data compression module; the sensor component is installed on the corresponding construction equipment, collects parameter data of the construction equipment, and feeds it back to the data transmission module; the data transmission module first transmits the data collected by the sensor component to the local gateway, and finally transmits it to the cloud server after preprocessing; the data compression module uses the Deflate data compression algorithm to compress data during data transmission.

[0009] Preferably, the monitoring and diagnosis module receives data transmitted from the local gateway through the cloud server, parses the data and stores it in a distributed database. The data is processed by the big data platform and real-time anomaly detection is performed through the SVM algorithm. The SVM model uses the historical data and real-time data of the equipment to establish an equipment health model and identify potential faults in the operation of construction equipment.

[0010] Preferably, the steps of the SVM algorithm in the monitoring and diagnosis module include:

[0011] Feature extraction and selection: Extract important features from preprocessed cloud data, including time domain and frequency domain features; use correlation analysis and principal component analysis to select features that have a high contribution to anomaly detection;

[0012] Model training: Use historical data for training and select RBF kernel function for classification;

[0013] Real-time anomaly detection: real-time data is input into the SVM model, anomalies are detected and results are output;

[0014] Abnormal handling and alarm: trigger alarm and notify maintenance personnel.

[0015] Preferably, the remote control module is used to enable managers to control on-site construction equipment through a web interface or mobile application. Managers who have passed two-factor authentication can view the equipment status in the system and perform equipment start and stop and parameter adjustment operations.

[0016] Preferably, the security management module is used to implement functions of data encryption and output encryption, access control and security monitoring.

[0017] In a second aspect, the present invention provides an integrated management method for Internet of Things devices for highway construction, which uses the Internet of Things device integrated management system for highway construction to uniformly manage highway construction equipment.

[0018] By adopting the above technical solution, the present invention has the following beneficial effects:

[0019] The present invention provides an Internet of Things equipment integrated management system and method for highway construction, which realizes unified management and monitoring of highway construction equipment through the Internet of Things technology, thereby improving the safety of equipment use and construction efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 A schematic diagram of the overall architecture of an Internet of Things device integrated management system for highway construction provided by an embodiment of the present invention;

[0022] Figure 2 A flow chart of abnormal diagnosis of the SVM algorithm provided by an embodiment of the present invention;

[0023] Figure 3 A schematic diagram of a token mechanism provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. 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.

[0025] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0026] Embodiment 1

[0027] like Figures 1 to 3As shown, this embodiment 1 provides an integrated management system of Internet of Things equipment for highway construction, which includes an equipment access module, a data acquisition module, a monitoring and diagnosis module, a remote control module and a security management module; the equipment access module is used to connect various types of equipment at the construction site to the Internet of Things to realize the networking and unified management of construction equipment; the data acquisition module is used to collect data of construction equipment in real time and transmit the data to a cloud server; the monitoring and diagnosis module is used to analyze the collected data, monitor the operating status of construction equipment in real time, identify equipment failures and diagnose them, and provide preventive maintenance suggestions; the remote control module supports remote operation and control of construction equipment to realize control of construction equipment; the security management module uses encryption and access control technology to ensure the security of data transmission and storage.

[0028] In this embodiment, preferably, the device access module includes: a device communication module and a device identification and registration module; the device communication module is arranged on the construction equipment, and the device communication module supports the MQTT protocol so that the construction equipment can be stably connected to the system network; the device identification and registration module generates a unique device identifier for each construction equipment, which is used for the identification and management of the construction equipment; after the construction equipment is connected to the system through the device communication module, the basic information of the construction equipment will be entered into the system database to ensure the classified management of the construction equipment.

[0029] Specifically, the functions of each module are as follows:

[0030] The device access module: The device access module connects the construction site equipment to the system through a standardized Internet of Things communication protocol.

[0031] 1. Equipment communication module: Each construction equipment is equipped with an IoT communication module that supports the MQTT protocol to ensure that the equipment can be stably connected to the system network. The MQTT (Message Queuing Telemetry Transport) protocol is a lightweight message transmission protocol designed for low-bandwidth and unstable network environments. It is based on the publish / subscribe model and supports message broadcasting and multicasting. It is one of the widely used protocols in IoT applications. The MQTT protocol has the characteristics of low overhead, low latency, and high efficiency. It is suitable for the complex network environment of the construction site and is very suitable for data communication between IoT devices. The use of the MQTT protocol realizes real-time data communication and remote control of equipment on the construction site, ensures the reliability and efficiency of data transmission, and provides strong technical support for equipment management in highway construction.

[0032] 2. Device identification and registration module: The system generates a unique device identifier (UUID) for each device for device identification and management. After accessing the system, the basic information of the device (including device type, model, manufacturer, etc.) will be entered into the system database to ensure the classification management of the device.

[0033] Specific implementation process:

[0034] (1) Generation of a device unique identifier (UUID);

[0035] UUID (Universally Unique Identifier) ​​is a standardized identifier used to identify devices, ensuring global uniqueness. The following steps are used to generate UUID:

[0036] Generation method:

[0037] Automatically generate using the uuid standard library in Python.

[0038] The generated UUID format is xxxxxxxx-xxxx-Mxxx-Nxxx-xxxxxxxxxxxx, which contains 32 hexadecimal numbers separated by 4 dashes. M and N are specific version and variant flags.

[0039] Generate example:

[0040] Example Code (Python): device_uuid = uuid.uuid4()

[0041] Generate result example: 550e8400-e29b-41d4-a716-446655440000

[0042] (2) Input basic equipment information

[0043] When a device is connected to the system, its basic information needs to be entered into the system database for easy management and tracking. This information includes device type, model, manufacturer, UUID, etc.

[0044] Database Design:

[0045] Database type: Use the relational database MySQL to manage device information.

[0046] Data table design: Create a device information table (Device_Info) with fields including Device_ID, Device_Type, Model, Manufacturer, UUID, Date_Added, etc.

[0047] Database operation instructions:

[0048] Insert new device information:

[0049] INSERT INTO Device_Info (Device_Type, Model, Manufacturer, UUID,Date_Added)

[0050] VALUES ('Sensor', 'XYZ123', 'ABC Corp', '550e8400-e29b-41d4-a716-446655440000', NOW());

[0051] Query device information:

[0052] SELECT * FROM Device_Info WHERE UUID = '550e8400-e29b-41d4-a716-446655440000';

[0053] (3) Device connection establishment:

[0054] After the device is started, the IoT communication module connects to the system's MQTT broker server (Broker) through the MQTT protocol. The connection request includes the device's unique identifier (UUID) and security authentication information.

[0055] The Broker verifies the device identity and allows the device to connect after passing security authentication.

[0056] (4) Topic subscription:

[0057] After successfully connecting, the device subscribes to relevant topics from the Broker, such as device status updates, remote control commands, etc.

[0058] The design of topics follows a hierarchical structure, such as / device / type / ID / status, to facilitate management and filtering of messages.

[0059] (5) News release:

[0060] The device periodically encapsulates the collected data (such as temperature, vibration, location, etc.) into MQTT messages and publishes them to the specified topic.

[0061] The message contains information such as timestamp, device ID, data content, etc. The message format uses JSON format to ensure data structuring and readability.

[0062] (6) Message transmission and reception:

[0063] The messages published by the device are managed and forwarded by the Broker. All system components (such as monitoring and diagnosis modules) that have subscribed to the corresponding topics can receive the messages in real time.

[0064] The reliable delivery of messages is guaranteed through the "QoS" (Quality of Service) mechanism of the MQTT protocol. The system uses QoS level 1 to ensure that messages are delivered at least once.

[0065] (7) Connection maintenance:

[0066] In the connection between the device and the Broker, a "heartbeat" packet (PINGREQ) is sent periodically to keep the connection active.

[0067] When the network is interrupted or the device is offline, the Broker will automatically detect and resume the session after the connection is restored.

[0068] (8) Disconnect:

[0069] When the device is turned off or enters sleep mode, it safely terminates the connection with the Broker by sending a disconnect request (DISCONNECT).

[0070] The broker clears the session information of the device and releases related resources.

[0071] In this embodiment, preferably, the data acquisition module includes: a sensor component, a data transmission module, and a data compression module; the sensor component is installed on the corresponding construction equipment, collects parameter data of the construction equipment, and feeds it back to the data transmission module; the data transmission module first transmits the data collected by the sensor component to the local gateway, and finally transmits it to the cloud server after preprocessing; the data compression module uses the Deflate data compression algorithm to compress data during data transmission.

[0072] Specifically, the functions of each module are as follows:

[0073] The data acquisition module is responsible for collecting operation data from the equipment in real time. The implementation steps are as follows:

[0074] 1. Sensor installation and data collection: Temperature sensors, vibration sensors and GPS modules are installed on each device to monitor the working status of the device. These sensors continuously collect key parameters such as device operating temperature, vibration amplitude, geographic location and operating time.

[0075] Specific implementation process:

[0076] (1) Sensor type

[0077] At the highway construction site, various types of sensors are installed to achieve comprehensive monitoring of the environment and equipment. These sensors include but are not limited to:

[0078] Temperature Sensor:

[0079] Purpose: To monitor the ambient temperature at the construction site to ensure that the equipment operates within a safe temperature range. Installation location: Distributed around key equipment that is susceptible to temperature, such as power equipment, hydraulic systems, etc.

[0080] Vibration Sensor:

[0081] Application: Detect the vibration status of the equipment during operation, identify abnormal vibration of the equipment, and help diagnose faults. Installation location: Installed in key parts of large mechanical equipment, such as engines, hydraulic pumps, etc.

[0082] Position Sensors:

[0083] Purpose: Track the real-time location of construction equipment to ensure that the equipment moves as planned and prevent the equipment from being lost. Installation location: Usually installed on construction vehicles and large equipment, and positioning is achieved through GPS or RFID technology.

[0084] Humidity Sensor:

[0085] Purpose: Monitor humidity conditions at construction sites to help predict possible geological changes or equipment corrosion risks. Installation location: Distributed in areas where humidity needs to be monitored, such as near the soil or in equipment storage areas.

[0086] Pressure Sensor:

[0087] Application: To detect the pressure status of hydraulic equipment and pneumatic equipment, and ensure that the equipment works within the safe pressure range. Installation location: Mainly installed in hydraulic pipelines and pneumatic systems.

[0088] (2) Data collection process

[0089] Sensor data collection is the basis of system operation, and the process includes the following steps:

[0090] Sensor Calibration: Perform an initial calibration of the sensor before installation to ensure its measurements are accurate and consistent. Recalibrate periodically, especially after the sensor is moved or replaced.

[0091] Data collection frequency setting: Different collection frequencies can be set according to the sensor type and monitoring requirements. For example, a vibration sensor can be set to collect data once per second, while a temperature sensor can be set to collect data once per minute.

[0092] 2. Data transmission:

[0093] The system first transmits the data collected by the sensors to the local gateway, and finally transmits it to the cloud server after preprocessing.

[0094] 2.1. Data transmission to local gateway:

[0095] In the integrated management system of IoT devices, sensors transmit the collected environmental data to the local gateway wirelessly through the LoRa protocol to ensure stable data transmission and low power consumption. LoRa (Long Range) is a low-power wide area network (LPWAN) communication protocol designed for long-distance wireless transmission. It uses spread spectrum technology to achieve data transmission within a range of several kilometers or even more than ten kilometers, and has strong anti-interference ability and low power consumption.

[0096] 2.2. Data packaging and sending:

[0097] The sensor packages the collected data, which contains the sensor ID, timestamp, measurement value and related metadata. After the data is packaged, the sensor sends the data packet wirelessly through the built-in LoRa communication module.

[0098] 2.3.LoRa data transmission:

[0099] During data transmission, the LoRa protocol manages wireless communications of data, modulating and demodulating signals using its spread spectrum technology to ensure that data can be transmitted reliably over long distances. The LoRa network optimizes data transmission efficiency and coverage by selecting appropriate channels and modulation rates.

[0100] 2.4. Data reception and processing:

[0101] The local gateway is the core node of the LoRa network and is responsible for receiving data packets sent by sensors. The gateway receives wireless signals through the antenna and uses LoRa demodulation technology to restore the signals to data packets. The received data packets are initially processed at the gateway, including parsing the data content and confirming the data integrity.

[0102] 2.5. Data preprocessing:

[0103] After arriving at the local gateway, the data undergoes preliminary processing, including outlier filtering and formatting, to reduce noise and ensure data consistency. In the IoT device integrated management system, data preprocessing is an important part of ensuring data quality. After the data collected by the sensor arrives at the local gateway, it needs to be initially processed, including outlier filtering and formatting, to reduce noise and ensure data consistency, so as to provide reliable input for subsequent data analysis and decision-making. The following is the detailed process of data preprocessing:

[0104] Data parsing: After the local gateway receives the data packet transmitted by the sensor, it first parses the data packet to extract valid data information, including sensor ID, timestamp, measurement value and other related metadata.

[0105] Outlier filtering: Define outlier criteria: Based on historical data and the technical specifications of the sensor, set a reasonable threshold range to determine whether the measurement value is abnormal. For example, for a temperature sensor, the reasonable temperature range may be -20℃ to 50℃.

[0106] Filtering process: Each measured value is tested. If the data is found to exceed the preset threshold range, it is determined to be an outlier and removed. Filtering of outliers can effectively reduce the interference of noise on data analysis.

[0107] Data formatting: Format the parsed data into the standard format required by the system, such as JSON or CSV format, to facilitate subsequent data transmission and processing. Data formatting includes standardization of timestamps to ensure the time series consistency of the data.

[0108] Data completion and smoothing: For missing values ​​or incomplete data records, interpolation technology is used to fill in to ensure data integrity. Use algorithms such as moving average filtering to smooth the data to reduce random fluctuations in measurement and improve data stability.

[0109] Data consistency check: Ensure that data from different batches of the same sensor have consistent structure and unit system, eliminating data deviations caused by device failure or configuration errors.

[0110] Data labeling and storage: Label the processed data and record the time and steps of data processing for easy traceability. Temporarily store the processed data in the local database to prepare for subsequent cloud transmission and analysis.

[0111] 2.6. Data transmission to cloud server

[0112] After data preprocessing is completed, the system needs to transfer the processed data from the local gateway to the cloud server for further analysis, storage and utilization. This process ensures that the data maintains integrity, security and real-time during transmission.

[0113] Data preparation

[0114] Data Packaging: The preprocessed data is packaged into standardized data packets that contain key information such as timestamps, device IDs, sensor readings, and metadata. The data is packaged in JSON format to ensure data structure and readability.

[0115] Data encryption: Before transmission, the data packet is encrypted using the AES-256 encryption algorithm to ensure that the data cannot be intercepted or tampered with during transmission. A random 256-bit session key is generated to encrypt the data packet. The initialization vector (IV) is used in conjunction with the key for encryption operations to improve the security of encryption.

[0116] 2.6.2. Network transmission

[0117] Connection establishment: The local gateway establishes a stable communication connection with the cloud server through the Internet. The TLS protocol is used during the connection process to provide an encrypted channel to protect the security of data transmission.

[0118] Use MQTT protocol for data transmission: Connection establishment: The gateway establishes a connection with the cloud MQTT broker server (Broker) through the MQTT client. The connection request contains the gateway's identifier and authentication information. Message publishing: As an MQTT client, the gateway publishes the data packet to the specified topic. Topics are designed in a hierarchical structure, such as / device / type / ID / data, to facilitate message management and classification. The data packet is encapsulated in the MQTT message format to ensure the structure and readability of the message. Usually, the data content is represented in JSON format. Message transmission quality control: Use MQTT's "QoS" (quality of service) mechanism to ensure the reliability of message transmission. The system usually uses QoS level 1 to ensure that the message is delivered at least once.

[0119] Cloud data reception and processing: The cloud MQTT proxy server receives the data packet and forwards it to the application components that subscribe to the corresponding topic, such as the monitoring and diagnosis module. The server uses the same session key as the client to decrypt the data packet and restore it to plain text data. The monitoring and diagnosis module processes the received data in real time and performs tasks such as real-time analysis and fault diagnosis. The analysis results and raw data are stored in the cloud database to support subsequent business decisions and historical data tracing.

[0120] Data backup and security: Data is regularly backed up to secure storage media to prevent data loss. The system ensures the security and traceability of data access through access control and logging.

[0121] (3) Data compression:

[0122] Data transmission is a key link in the integrated management system of IoT devices. In order to reduce the transmission delay of data from the local gateway to the cloud and improve the transmission reliability, the system uses the Deflate data compression algorithm for data compression. Deflate is a lossless data compression algorithm that combines the LZ77 algorithm and Huffman coding, which can effectively reduce the data volume without losing any information. Its main features include:

[0123] Lossless compression: The compressed data can be completely restored to the original data when decompressed, ensuring data integrity.

[0124] High compression rate: By removing data redundancy, the data size is significantly reduced, which is particularly suitable for large amounts of time series data transmitted by IoT devices.

[0125] Fast decompression: After the data reaches the cloud, it can be quickly decompressed to facilitate real-time data processing and analysis.

[0126] The following is a detailed description of the data compression process:

[0127] 3.1. Data preparation after preprocessing:

[0128] After preprocessing steps such as outlier filtering, formatting, and consistency checking, the data is organized into a standard structured format (such as JSON or CSV).

[0129] For further compression, data packets are chunked according to specific application requirements to optimize bandwidth utilization when transmitted over the network.

[0130] 3.2. Compression process:

[0131] LZ77 algorithm application: Identify repeated strings in the data stream and replace them with references to reduce data redundancy. For example, if multiple repeated sensor IDs appear in the data stream, the ID will be replaced with a reference to the first occurrence when it appears later.

[0132] Huffman coding: Huffman coding algorithm is used to represent common symbols in the data stream with shorter bit codes, and less common symbols with longer bit codes, thereby reducing the overall code length.

[0133] 3.3. Data packaging and transmission:

[0134] The compressed data packets are packaged into a transmission format and the necessary metadata (such as packet sequence number, checksum, etc.) are attached to ensure the correctness and integrity of the transmission.

[0135] Data is encrypted using the TLS security protocol to protect data privacy and prevent tampering.

[0136] 3.4. Data decompression and verification:

[0137] After the data reaches the cloud server, the Deflate decompression algorithm is used to restore the data.

[0138] Perform data integrity verification to ensure that the decompressed data is consistent with the original data.

[0139] (4) Data transmission to cloud server:

[0140] In the IoT device integrated management system, the data collected and pre-processed by the local gateway is transmitted to the cloud server for further analysis and long-term storage.

[0141] 4.1. Data preparation:

[0142] At the local gateway, the data is initially processed, compressed, and packaged into structured data packets, which contain key information such as timestamp, device ID, sensor readings, and necessary verification information.

[0143] 4.2. Gateway and cloud connection: The local gateway connects to the cloud server via the Internet to establish a stable communication channel. The connection process is encrypted using a security protocol (such as TLS) to protect the security of data transmission.

[0144] 4.3. Using MQTT protocol for data transmission:

[0145] Connection establishment: The gateway establishes a connection with the cloud MQTT broker server (Broker) through the MQTT client. The connection request contains the gateway's identifier and authentication information.

[0146] Message publishing: As an MQTT client, the gateway publishes data packets to the specified topic. Topics are designed in a hierarchical structure, such as / device / type / ID / data, to facilitate message management and classification. Data packets are encapsulated in the MQTT message format to ensure the structure and readability of the message. Usually, the data content is expressed in JSON format.

[0147] Message transmission quality control: Use MQTT's "QoS" (Quality of Service) mechanism to ensure the reliability of message transmission. The system usually uses QoS level 1 to ensure that the message is delivered at least once.

[0148] 4.4. Cloud data reception and processing: The cloud MQTT proxy server receives data packets and forwards them to application components that subscribe to the corresponding topics, such as the monitoring and diagnosis module. The monitoring and diagnosis module processes the received data in real time and performs tasks such as real-time analysis and fault diagnosis. The analysis results and raw data are stored in the cloud database to support subsequent business decisions and historical data tracing.

[0149] In this embodiment, preferably, the monitoring and diagnosis module receives data transmitted from the local gateway through the cloud server, parses the data and stores it in a distributed database. The data is processed by the big data platform and real-time anomaly detection is performed through the SVM algorithm. The SVM model uses the historical data and real-time data of the equipment to establish an equipment health model to identify potential faults in the operation of construction equipment.

[0150] Specifically, the functions of each module are as follows:

[0151] The monitoring and diagnosis module runs on the cloud server and its function is to perform real-time analysis and fault diagnosis of equipment data. The system processes the real-time transmitted data through big data technology and uses a machine learning algorithm based on support vector machine (SVM) for anomaly detection. The SVM algorithm can effectively identify equipment operation anomalies and generate accurate diagnostic results.

[0152] The specific implementation is as follows:

[0153] Data reception and preparation: The cloud server receives data packets transmitted from the local gateway, which contain key information such as the device's sensor readings, timestamps, device IDs, etc. The data is parsed and stored in a distributed database for batch processing and historical analysis.

[0154] Big data technology processing: Use the big data platform Spark to perform batch and stream processing on massive data. The real-time processing module extracts key features from the data stream and generates data summaries to support rapid analysis. Data cleaning and organization: Remove noise data and redundant information through cleaning and organization steps to ensure the accuracy and consistency of analytical data.

[0155] Support Vector Machine (SVM) algorithm: Support Vector Machine (SVM) is a supervised learning model for classification and regression. Its goal is to separate different categories of data by finding an optimal hyperplane. SVM is particularly suitable for classification tasks of complex data sets and has good generalization ability and robustness. The following is an introduction to the SVM model structure:

[0156] Basic Concepts

[0157] Support vectors: Support vectors are those sample points that are closest to the decision boundary in the feature space. These points have an important influence on the definition of the hyperplane.

[0158] Hyperplane: A hyperplane is a decision boundary used to separate different classes. In two-dimensional space, a hyperplane is a straight line, while in three-dimensional space, it is a plane. In high-dimensional space, a hyperplane is an n-1-dimensional plane.

[0159] Margin: Margin refers to the distance from the support vector to the hyperplane. SVM finds the best hyperplane by maximizing the margin. The larger the margin, the stronger the generalization ability of the model.

[0160] Linearly Separable SVM

[0161] For linearly separable data sets, SVM tries to find a hyperplane that completely separates the data set so that the points on both sides of the hyperplane belong to different categories.

[0162] Decision function:

[0163]

[0164] in, is the weight vector, is the input feature vector, is the bias term. The goal of the model is to find and , so that the interval is maximized.

[0165] Linearly inseparable SVM

[0166] For linearly inseparable data sets, SVM introduces soft margins and penalty parameters (C) to allow some data points to be on the wrong side, but the error tolerance is controlled by the penalty parameter.

[0167] Objective function:

[0168]

[0169]

[0170] Among them, C is the penalty parameter, is a slack variable that allows data points to be on the wrong side of the separation.

[0171] Kernel Function

[0172] In order to process nonlinearly separable data, SVM uses a kernel function to map the data into a high-dimensional space so that the data is linearly separable in this space.

[0173] Commonly used kernel functions:

[0174] Linear kernel:

[0175] Gaussian kernel (RBF kernel):

[0176] Sigmoid kernel:

[0177] The choice of kernel function affects the complexity of the model and the classification effect. By choosing a suitable kernel function, complex nonlinear data can be effectively processed.

[0178] Model training and optimization

[0179] The training process of SVM is achieved by solving the quadratic optimization problem, that is, finding the optimal and Maximize the margin of the decision boundary.

[0180] The Lagrange dual method is usually used to solve optimization problems. The original problem is converted into a dual problem by introducing Lagrange multipliers, thereby simplifying the computational complexity.

[0181] On large-scale datasets, commonly used optimization algorithms include gradient descent, coordinate descent, and sequential minimization optimization (SMO).

[0182] Model Evaluation

[0183] After training, the SVM model was evaluated using metrics such as cross validation, confusion matrix, precision, recall, and F1 score to ensure the performance and generalization ability of the model.

[0184] Based on the evaluation results, the penalty parameters can be adjusted and kernel function parameters, such as To optimize the model.

[0185] The following is the specific implementation process of the SVM algorithm in the monitoring and diagnosis module:

[0186] SVM algorithm abnormal diagnosis:

[0187] 1. Feature extraction and selection

[0188] Feature extraction: Extract important features from preprocessed cloud data, including time domain and frequency domain features, to better describe the operating status of the device.

[0189] Feature selection: Use correlation analysis and principal component analysis (PCA) to select features that have a higher contribution to anomaly detection and reduce the dimension to improve model efficiency.

[0190] 2. Model training

[0191] Preparation of training data set: Use historical data and normal and abnormal data annotated by experts to build training data set to ensure the diversity and representativeness of the data set.

[0192] Select kernel function: According to the nonlinearity of the data, select RBF kernel function to improve the classification ability of the model.

[0193] Model training: The model is trained through the SVM algorithm to find the optimal decision boundary and maximize the classification interval. The optimization problem can be expressed as:

[0194]

[0195]

[0196] Where C is the penalty parameter, is a slack variable.

[0197] 3. Real-time anomaly detection:

[0198] Data input: Collect data from the device in real time and input it into the preprocessing module for cleaning and standardization.

[0199] Feature calculation: Extract features from real-time data and generate feature vectors consistent with those in the training phase.

[0200] Anomaly detection: Input the feature vector into the trained SVM model for prediction and output the classification result (normal or abnormal). Through the decision function:

[0201]

[0202] If f(x)=1, it indicates a normal state, and if f(x)=-1, it indicates an abnormal state.

[0203] 4. Exception handling and alarm

[0204] Abnormality identification: When an abnormality is detected, the alarm mechanism is triggered to notify the relevant maintenance personnel.

[0205] Recording and analysis: Record abnormal data and test results for subsequent analysis and model optimization.

[0206] Feedback adjustment: Optimize and adjust model parameters based on test results and equipment operating status to improve the accuracy and adaptability of the model.

[0207] Model update and maintenance

[0208] Continuous learning: The SVM model is regularly retrained through feedback and learning from new data to ensure that it maintains efficient and accurate detection capabilities in a changing environment.

[0209] Adaptive adjustment: Dynamically adjust feature weights and model parameters according to changes in the device operating environment to improve the sensitivity and specificity of anomaly detection.

[0210] In this embodiment, preferably, the remote control module is used to enable management personnel to control on-site construction equipment through a web interface or a mobile application. Management personnel who have passed two-factor authentication can view the equipment status in the system and perform equipment start and stop and parameter adjustment operations.

[0211] Specifically, the functions of each module are as follows: In the IoT device integrated management system, the design of remote operation permissions enables managers to efficiently control on-site devices through the Web interface or mobile applications. The following is a detailed implementation process of remote operation permissions:

[0212] 1. User login:

[0213] Web interface or mobile app access: Administrators access the device management platform through the system's web interface or mobile app. During the login process, users need to enter a unique username and password. The front-end interface is built using the JavaScript framework React to provide an interactive user experience.

[0214] Username and Password Entry: The user enters the unique username and password assigned to the individual on the login page. When entering, the username and password are transmitted using the TLS encryption protocol to ensure the security of the login credentials.

[0215] 2. Two-factor authentication:

[0216] The system uses two-factor authentication (2FA). After entering the password, the user is required to provide a dynamic verification code sent via SMS or email to further confirm the identity.

[0217] 2FA Overview: Two-factor authentication enhances system security by requiring users to provide two different types of verification information ("something you know" and "something you have").

[0218] Dynamic verification code generation: After the user successfully enters the password, the system automatically generates a temporary dynamic verification code. The verification code is sent to the user through a secure channel (such as SMS or email) to ensure the confidentiality and accuracy of the message.

[0219] Verification code verification: After receiving the verification code, the user enters it into the system for verification within a specified time. The verification code is valid once and becomes invalid after use or timeout, ensuring the timeliness and security of the verification code.

[0220] 3. Permission verification:

[0221] The system checks the user's identity and permissions to confirm whether they have the right to access and operate specific equipment. Permissions are allocated based on user roles and responsibilities.

[0222] Identity confirmation: The system first confirms whether the user's identity is legitimate, and compares the input credentials with the information stored in the MySQL database through the backend service (based on Spring Boot).

[0223] Permission check: The system checks whether the user has the permission to access and operate specific equipment based on the user's role and scope of responsibility. Roles include administrator, operator, viewer, etc., and each role has different access rights.

[0224] Dynamic permission management: Administrators can adjust user permissions in real time through the background management interface, increase or decrease user operation capabilities, and ensure the flexibility and accuracy of permission allocation.

[0225] 4. Token mechanism:

[0226] The system generates a security token for each successfully authenticated user, which is used as an authentication identifier during the user session and is attached to each operation request.

[0227] Token generation: After the user successfully passes the authentication, the system generates a unique security token, which is encrypted using the OAuth 2.0 protocol and the JWT (JSON Web Token) standard. The token contains encrypted user identity information and session information.

[0228] OAuth 2.0 Protocol

[0229] OAuth 2.0 Overview: OAuth 2.0 is an open authorization protocol that allows third-party applications to access user resources with the user's permission. The protocol performs authorization through tokens without the user revealing their login credentials.

[0230] Authorization process: After the user successfully logs in, the system applies for an access token from the authentication server according to the authorization code mode of the OAuth 2.0 protocol. After the authentication server verifies the user's identity, it issues an access token.

[0231] 4.2. JWT (JSON Web Token) Standard

[0232] JWT Overview: JSON Web Token is a token based on the JSON format, which consists of three parts: Header, Payload, and Signature.

[0233] Header: contains the token type and signature algorithm, such as {"alg": "HS256", "typ": "JWT"}.

[0234] Payload: Contains user identity information and session information, such as user ID, role, permissions, and token expiration time.

[0235] Signature: Used to verify the authenticity and integrity of the token. Use the algorithm specified in the Header to encrypt and sign the Header and Payload.

[0236] The following is the detailed implementation flow of token generation:

[0237] 1. User authentication is successful:

[0238] After the user passes the system's login authentication, the system confirms the legitimacy of his or her identity.

[0239] The system generates a JWT token for authorization.

[0240] 2. Build the JWT token:

[0241] Header construction: The system selects the SHA256 encryption algorithm to construct the Header part of the JWT.

[0242] Payload construction: The system adds user information (such as user ID, role), session information (such as token issuance time and expiration time) to the Payload, and can add custom claims.

[0243] Signature generation: Use the encryption algorithm specified in the Header and the system key to encrypt the Header and Payload to generate a Signature.

[0244] 4.3. Token Content Structure

[0245] Header:

[0246] {

[0247] "alg": "HS256",

[0248] "typ": "JWT"

[0249] }

[0250] Payload:

[0251] {

[0252] "user_id": "12345",

[0253] "role": "admin",

[0254] "iat": 1622547800, / / Issuance time (Unix timestamp)

[0255] "exp": 1622583800, / / expiration time (Unix timestamp)

[0256] "permissions": ["read", "write", "delete"]

[0257] }

[0258] Signature: HMACSHA256(base64UrlEncode(header) + "." + base64UrlEncode(payload), secret)

[0259] Token issuance:

[0260] Generate a token: After the user is successfully authenticated, the server generates a security token using the OAuth 2.0 protocol and the JWT standard.

[0261] Token delivery: The server sends the generated JWT to the user's device via an HTTP response.

[0262] Storing tokens: After receiving the token, the user device (such as a web browser or mobile app) stores it securely in local storage (such as localStorage, sessionStorage, or secure mobile device storage) to ensure that it can be accessed at any time during the session.

[0263] 4.5. Token Usage:

[0264] In each operation request, the token is used as the user's identity authentication identifier and is attached to the request header and passed to the server. The server verifies the validity of the token and then performs the corresponding operation.

[0265] Request construction: Whenever a user initiates an operation request to the system, the client retrieves the JWT from the storage and attaches it in the HTTP request header.

[0266] Request header format:

[0267] Makefile

[0268] Authorization: Bearer <token>

[0269] Example:

[0270] http

[0271] GET / api / devices / status HTTP / 1.1

[0272] Host: api.example.com

[0273] Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VyX2lkIjoiMTIzNDUiLCJyb2xlIjoiYWRtaW4iLCJpY XQiOjE2MjI1NDc4MDAsImV4cCI6MTYyMjU4MzgwMH0.Vt6wV9h3ZTcn2aU8nd03TfhZI7l8v4u-yex8-EyMtmA

[0274] Server Authentication:

[0275] Receiving a request: After receiving a request, the server checks whether the request header contains a valid Authorization field.

[0276] Token parsing: The server uses a pre-shared secret key to decode and verify the token.

[0277] Validity check: Verify the integrity (Signature verification), timeliness (check the iat and exp fields), and user identity and permissions of the token.

[0278] Authorization to execute:

[0279] Verification passed: If the token verification succeeds, the server identifies the user based on the information in the token and checks whether the user's permissions are sufficient to perform the requested operation.

[0280] Execute operation: The server performs corresponding operations based on the request content and user permissions, and returns the results.

[0281] Error handling:

[0282] Invalid or expired token: If token validation fails, the server returns HTTP status code 401 (Unauthorized) and requires the user to log in again to obtain a new token.

[0283] 4.6. Token Lifecycle Management

[0284] The token is time-sensitive and will become invalid after the session ends or times out. Users need to re-authenticate to obtain a new token to ensure session security.

[0285] Encryption and Signature: Use the secure SHA256 encryption algorithm to ensure the integrity and authenticity of the JWT and prevent the token from being tampered with.

[0286] Timeliness control: The life cycle of the token is controlled through the iat (issuance time) and exp (expiration time) fields to prevent long-term valid tokens from being used maliciously.

[0287] Secure storage and transmission: Clients should store JWT securely (such as in the browser's localStorage or sessionStorage) and transmit it over HTTPS to prevent man-in-the-middle attacks.

[0288] The system adopts the OAuth 2.0 protocol and JWT standard, which can generate a secure, short-term access token for each user, ensuring the security and controllability of user sessions, while facilitating the management and monitoring of user operation behaviors.

[0289] In this embodiment, preferably, the security management module is used to implement functions of data encryption and output encryption, access control and security monitoring.

[0290] Specifically, the functions of each module are as follows:

[0291] In the integrated management system of IoT devices, data encryption, access control and security monitoring are key links to ensure system security and data integrity. The following are the detailed technical implementation and implementation process of these measures:

[0292] 1. Data encryption

[0293] 1.1.AES-256 encryption algorithm

[0294] AES-256 (Advanced Encryption Standard 256-bit) is a symmetric encryption algorithm that is widely used in various secure communication protocols to ensure the confidentiality and integrity of data transmission. The following is the specific process of the AES-256 encryption algorithm implemented in the present invention:

[0295] 1.1.1 Encryption process: During data transmission, the system uses AES-256 to encrypt data. AES (Advanced Encryption Standard) is a symmetric encryption algorithm with high efficiency and security.

[0296] (1) Key generation:

[0297] Generate key: The system dynamically generates a 256-bit encryption key for each session. This key is used to encrypt and decrypt data to ensure session uniqueness and data security.

[0298] Key distribution: After the key is generated, it is distributed to both communicating parties through a secure key exchange protocol to ensure that the key will not be intercepted during transmission.

[0299] (2) Data encryption:

[0300] Plaintext processing: Before data transmission, the plaintext data to be transmitted is divided into blocks of a fixed size of 128 bits.

[0301] Encryption algorithm: Use the AES-256 algorithm to encrypt each data block and generate ciphertext. The encryption process includes several rounds of substitution and permutation operations, making the output ciphertext difficult to crack.

[0302] Initialization Vector (IV): For added security, the system uses an initialization vector in conjunction with the key for encryption. The IV is unique in each session to prevent the same plaintext block from producing the same ciphertext.

[0303] The following are the specific steps of each round of encryption operation:

[0304] Initial key addition (AddRoundKey):

[0305] Before the first round, the data block is bitwise XORed with the generated round key, which is used to introduce the key into the encryption process to ensure that it cannot be decrypted without the key.

[0306] Byte substitution (SubBytes):

[0307] Each byte in a data block is replaced by another byte. This substitution is based on a fixed S-box (Substitution box), which is a nonlinear substitution table to increase the nonlinear characteristics of encryption and prevent linear attacks.

[0308] ShiftRows:

[0309] The rows in the data block are circularly shifted. The number of bits shifted for each row is different. The first row remains unchanged, the second row is shifted left by one, the third row is shifted left by two, and the fourth row is shifted left by three. This destroys the linear relationship between rows and increases the diffusion characteristics of encryption.

[0310] MixColumns (not used in the final round):

[0311] Treat each column of a data block as a polynomial and perform multiplication with it through a fixed polynomial over a finite field to mix the bytes within the column. This can enhance the diffusion between bytes in each column and increase the complexity of the ciphertext.

[0312] Round key addition (AddRoundKey):

[0313] At the end of each round, the data block is again bitwise XORed with the current round key. The influence of the key can be combined to make the output of each round of encryption related to the key.

[0314] 1.1.2 Decryption process:

[0315] 1. Ciphertext reception:

[0316] The receiver obtains the ciphertext data from the encrypted channel and prepares to perform decryption operations.

[0317] 2. Decryption algorithm:

[0318] Key usage: Decrypt the ciphertext using the 256-bit key and the same initialization vector shared in the session. Restore plaintext: Convert the ciphertext back to the original plaintext data through the inverse operation of the AES-256 algorithm.

[0319] 3. Integrity Verification:

[0320] The decrypted data is integrity checked to ensure that the data has not been tampered with during transmission.

[0321] 4.TLS protocol:

[0322] In the present invention, the TLS (Transport Layer Security) protocol is used to ensure confidentiality, integrity and identity authentication during data transmission. The following is a detailed description of the specific implementation of the TLS protocol in the system:

[0323] 1. Communication channel establishment

[0324] TLS handshake protocol:

[0325] The main purpose of the TLS handshake protocol is to establish a secure communication channel between the client and the server. Through the handshake process, the two parties can negotiate the encryption algorithm and generate a symmetric session key for subsequent data encryption.

[0326] Handshake process:

[0327] Client Hello: The client sends a "Hello" message, which contains the supported TLS version, a list of cipher suites, a random number, and a session ID (if it is a reconnection).

[0328] Server Hello: The server selects the TLS version and cipher suite, generates and sends the server's random number, and attaches the server certificate.

[0329] Certificate authentication: The client receives the server certificate and verifies its legitimacy and authenticity. This includes checking whether the issuer of the certificate is trustworthy (using CA authentication), whether the certificate is within the validity period, and whether the certificate matches the server domain name.

[0330] Key exchange: Both parties exchange key materials through the RSA asymmetric encryption algorithm to generate symmetric session keys. The client generates a pre-master secret, encrypts it with the server's public key, and sends it to the server.

[0331] Generate session key: Both parties use the pre-master key and the previously generated random number to calculate the session key, which is used to symmetrically encrypt subsequent communication data.

[0332] 2. Data encryption and transmission

[0333] Data encryption: Data is encrypted using a negotiated symmetric session key before transmission. The present invention uses the AES-256 encryption algorithm. Encryption ensures that data remains confidential during transmission and is prevented from being stolen or viewed by unauthorized third parties.

[0334] Data integrity: TLS uses a message authentication code (MAC) to ensure data integrity. MAC is a verification mechanism that can detect whether the data has been tampered with during transmission.

[0335] When sending data, the system generates a MAC and appends it to the data. The receiver can verify the MAC using the session key to ensure that the data has not been modified.

[0336] 3. Certificate Authentication

[0337] Certificate verification: During the TLS handshake process, the server provides its digital certificate, and the client verifies the authenticity of the certificate by checking the issuing authority (CA), validity period, and server information. If the server certificate verification is successful, the client can trust the server's identity and establish a secure connection.

[0338] Preventing man-in-the-middle attacks: Through certificate verification, TLS can effectively prevent man-in-the-middle attacks, ensuring that the client is connected to the real server, not a fake server impersonated by the attacker.

[0339] 2. Access Control

[0340] In this invention, a role-based access control (RBAC) mechanism is used to manage user permissions to ensure system security and data integrity. The following are the specific implementation details of RBAC in this system:

[0341] 1. Role Definition

[0342] Role settings:

[0343] The system defines multiple user roles to meet different operational needs and security requirements. Common roles include:

[0344] Administrator: Has the highest authority and can access and manage all functions of the system, including user management, system settings, and data auditing.

[0345] Operator: Responsible for day-to-day system operation and maintenance, with access to most functions of the system but unable to make critical configuration changes.

[0346] Visitors: can only view public data information and cannot perform any data modification or system setting operations.

[0347] 2. Permission allocation

[0348] Permission strategy:

[0349] The system assigns corresponding permissions based on user roles to ensure that users can only access functions and data within their scope of responsibility.

[0350] Each role corresponds to a specific set of permissions, which determine the operations that the user can perform, such as view, edit, delete, and add.

[0351] Permission boundaries:

[0352] Administrators have full permissions, including system settings and user management permissions.

[0353] Operators can perform data processing and equipment operations, but cannot change system configuration or manage other users.

[0354] Visitors can only view data and cannot make any modifications.

[0355] 3. Access Logging

[0356] Logging mechanism:

[0357] The system records all user access operations in real time, including the following information:

[0358] Timestamp: records the specific time when the operation occurs.

[0359] Operation Type: records the type of operation performed by the user (such as view, edit, delete).

[0360] User identity: records the identity information of the user who performs the operation.

[0361] Log audit:

[0362] The system regularly audits access logs to detect potential security threats or abnormal operations.

[0363] The audit process includes checking for unusual login attempts, unauthorized access, and other behaviors that could affect system security.

[0364] Through auditing, the system can promptly identify and respond to potential security risks and maintain the security and stability of the system.

[0365] 3. Safety monitoring

[0366] In this invention, in order to ensure the security and stability of the system, a comprehensive security monitoring mechanism is implemented, covering security vulnerability scanning and patch updates, security log recording and analysis, etc. The following are the detailed implementation details of each part:

[0367] 1. Security vulnerability scanning and patch updates

[0368] Regular Scan

[0369] Automated tools: The system integrates the Nessus automated security scanning tool to perform comprehensive security vulnerability scans on the system on a regular basis.

[0370] Scan frequency: Set the scan task to be executed once a week or immediately after important system updates to ensure that potential security threats are discovered in a timely manner.

[0371] Scan scope: covers all components that may have vulnerabilities, such as operating systems, application software, and network devices.

[0372] Patch Management

[0373] Vulnerability repair process:

[0374] Scan result evaluation: The technical team evaluates the scan results and develops a remediation plan based on the severity and priority of the vulnerabilities.

[0375] Patch application: Use the WSUS automated patch management tool to deploy security patches provided by vendors and fix known vulnerabilities.

[0376] Verification test: Functional and security verification tests are performed after the patch is applied to ensure the effectiveness of the repair measures and do not affect the normal operation of the system.

[0377] 2. Security log and analysis

[0378] Logging

[0379] Operation log: records all users’ login, operation, modification, deletion and other activities to ensure that every operation is recorded.

[0380] Security events: Records system anomalies, unauthorized access attempts, configuration changes, and other events that may affect security.

[0381] Abnormal behavior: Monitor and record abnormal behavior in the system, such as abnormal traffic, data leakage attempts, etc.

[0382] Log analysis tools: Use the ELK (Elasticsearch, Logstash, Kibana) stack for real-time log analysis and visualization.

[0383] Security reports and alerts

[0384] Report generation: The system generates security reports regularly, summarizing security status and potential risks.

[0385] Alarm notification: When a major security threat is detected, the system automatically sends an alarm notification to security personnel.

[0386] Response measures: The security team formulates and implements response measures based on reports and alarm information to respond to security incidents in a timely manner and reduce risks.

[0387] In summary, the present invention has the following beneficial effects:

[0388] 1. Efficient data collection and transmission technology:

[0389] The present invention adopts the LoRa protocol to realize long-distance wireless data transmission between the construction site sensor and the local gateway. Compared with the traditional wired or short-distance wireless transmission mode, it has lower power consumption and higher transmission stability. Combined with the MQTT protocol, reliable data transmission from the gateway to the cloud is realized, ensuring the real-time and integrity of the data, and solving the problems of data delay and loss in the prior art.

[0390] 2. Intelligent anomaly detection and fault diagnosis capabilities:

[0391] The introduction of the support vector machine (SVM) algorithm can perform real-time analysis and anomaly detection on the equipment operation status. Compared with the traditional regular inspection and manual monitoring methods, it can more quickly and accurately identify potential equipment failures and provide maintenance suggestions. This intelligent diagnosis function significantly reduces the unexpected downtime and maintenance time of the equipment, and improves the utilization rate of the equipment and construction efficiency.

[0392] 3. Integration of remote control and management functions:

[0393] The system provides remote equipment control functions through the web interface and mobile applications. Managers can adjust the operating status of the equipment in real time from any location, avoiding the limitation of traditional technology that requires on-site manual operation. This flexible control method not only improves management efficiency, but also greatly reduces labor costs.

[0394] 4. Secure data encryption and access control measures:

[0395] The AES-256 encryption algorithm and TLS protocol are used to ensure the security of data transmission, and the role-based access control (RBAC) mechanism is adopted to ensure that only authorized users can access and operate system resources. Compared with the common problems of data leakage and improper permission management in the prior art, the present invention has achieved significant improvements in security and reliability.

[0396] 5. Scalable system architecture design:

[0397] The system design takes into account the need for future expansion. Through modular design, it can easily integrate more types of sensors and functional modules to meet the needs of different construction scenarios. This high scalability and flexibility enables the system to maintain its practicality and advancement in the face of ever-changing technical environments and construction requirements.

[0398] Embodiment 2

[0399] like Figures 1 to 3 As shown, this embodiment 2 provides an integrated management method for Internet of Things devices for highway construction based on the embodiment 1. This embodiment 2 includes the technical content disclosed in the embodiment 1. The technical content of this embodiment 2 that is the same as that of the embodiment 1 is not repeated here. The difference between this embodiment 2 and the embodiment 1 is described below. The present invention provides an integrated management method for Internet of Things devices for highway construction, which uses the Internet of Things device integrated management system for highway construction to uniformly manage highway construction equipment. The unified management and monitoring of highway construction equipment is achieved through the Internet of Things technology, thereby improving the safety of equipment use and construction efficiency.

[0400] This method is deployed in actual highway construction projects, covering functions such as equipment access, data collection, monitoring and diagnosis, remote control and safety management. The following describes its specific application in highway construction in detail.

[0401] 1. Device access

[0402] At highway construction sites, construction equipment such as rollers, pavers and drills are all equipped with IoT communication modules. After startup, each device connects to the system's MQTT broker server (Broker) through the MQTT protocol. During the connection process, the device sends its unique identifier (UUID) and security authentication information. After verification, the Broker allows the connection and subscribes to corresponding topics, such as device status updates and control instructions.

[0403] 2. Data collection and transmission

[0404] In the data collection phase, sensors equipped on construction equipment collect real-time data on equipment operation status, including temperature, vibration, location, working hours, etc. These data are transmitted to the local gateway on site via the LoRa wireless network.

[0405] Sensor installation and data collection:

[0406] Temperature sensor: Installed near the hydraulic system to monitor the operating temperature of the equipment to ensure it operates within a safe range.

[0407] Vibration sensor: installed at key parts of the equipment to monitor vibration frequency and intensity and identify abnormal vibration status of the equipment.

[0408] GPS module: used to record the geographical location of the equipment to ensure that the equipment is constructed according to the planned location.

[0409] Data transmission:

[0410] The collected data is wirelessly transmitted to the local gateway via the LoRa protocol. The LoRa protocol has the advantages of low power consumption and long-distance transmission, which is suitable for the construction site environment.

[0411] At the local gateway, the data is preprocessed, including outlier filtering and formatting. The preprocessed data is compressed using the Deflate algorithm and transmitted to the cloud server via the MQTT protocol.

[0412] 3. Data Processing and Analysis

[0413] On the cloud server, the data is processed by a big data platform (such as Apache Spark) and real-time anomaly detection is performed using the support vector machine (SVM) algorithm. The SVM model uses the historical and real-time data of the device to build a device health model and identify potential failures in device operation.

[0414] Anomaly detection and fault diagnosis:

[0415] Data analysis: The SVM model analyzes the vibration and temperature data of the equipment and triggers a fault alarm when an abnormal pattern is detected.

[0416] Fault report: The system automatically generates a fault report, including abnormal indicators of the equipment, possible causes of the fault and recommended maintenance measures. The report is sent to the on-site management personnel through the system interface.

[0417] 4. Remote control and management

[0418] The system supports remote control of devices through the web interface or mobile application. Managers who have passed the two-factor authentication can view the device status in the system and perform operations such as starting and stopping the device and adjusting parameters.

[0419] Control Flow:

[0420] After the administrator selects the device operation on the system interface, the command is sent to the device through an encrypted channel (TLS protocol).

[0421] After the device executes the instruction, it will feedback the execution result and current status through the encrypted channel, and the system interface will update the device information in real time.

[0422] 5. Security Management

[0423] The system implements comprehensive security management measures to ensure the security of data transmission and access.

[0424] Data encryption: All transmitted data is encrypted using the AES-256 algorithm to ensure that it cannot be intercepted or tampered with during transmission.

[0425] Access Control: The system uses a role-based access control (RBAC) mechanism to ensure that only authorized users can access specific functions and data.

[0426] Security monitoring: The system regularly scans for security vulnerabilities and logs and analyzes all user operations to ensure the security and stability of the system.

[0427] Implementation effect: The application of this system in actual highway construction projects can significantly improve the management efficiency and safety of construction equipment. Through real-time data collection and analysis, the equipment failure rate is reduced and the construction efficiency is improved. Managers can remotely monitor and control equipment, reducing the complexity of on-site operations. At the same time, through advanced safety management measures, the overall safety of the system is also effectively guaranteed.

[0428] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.< / token>

Claims

1. An integrated management system for Internet of Things equipment for highway construction, characterized in that: It includes an equipment access module, a data acquisition module, a monitoring and diagnosis module, a remote control module and a security management module; the equipment access module is used to connect various types of equipment at the construction site to the Internet of Things to realize the networking and unified management of construction equipment; the data acquisition module is used to collect data from construction equipment in real time and transmit the data to a cloud server; the monitoring and diagnosis module is used to analyze the collected data, monitor the operating status of construction equipment in real time, identify equipment failures and diagnose them, and provide preventive maintenance suggestions; the remote control module supports remote operation and control of construction equipment to realize control of construction equipment; the security management module ensures the security of data transmission and storage through encryption and access control technology.

2. The Internet of Things equipment integrated management system for highway construction according to claim 1 is characterized in that: The equipment access module includes: an equipment communication module and an equipment identification and registration module; the equipment communication module is arranged on the construction equipment, and the equipment communication module supports the MQTT protocol so that the construction equipment can be stably connected to the system network; the equipment identification and registration module generates a unique equipment identifier for each construction equipment, which is used for the identification and management of the construction equipment; after the construction equipment is connected to the system through the equipment communication module, the basic information of the construction equipment will be entered into the system database to ensure the classified management of the construction equipment.

3. The Internet of Things equipment integrated management system for highway construction according to claim 1 is characterized in that: The data acquisition module includes: a sensor component, a data transmission module, and a data compression module; the sensor component is installed on the corresponding construction equipment to collect parameter data of the construction equipment and feed it back to the data transmission module; the data transmission module first transmits the data collected by the sensor component to the local gateway, and finally transmits it to the cloud server after preprocessing; the data compression module uses the Deflate data compression algorithm to compress data during data transmission.

4. The Internet of Things equipment integrated management system for highway construction according to claim 1 is characterized in that: The monitoring and diagnosis module receives data transmitted from the local gateway through the cloud server, parses the data and stores it in a distributed database. The data is processed by the big data platform and real-time anomaly detection is performed through the SVM algorithm. The SVM model uses the historical data and real-time data of the equipment to establish an equipment health model and identify potential faults in the operation of construction equipment.

5. The Internet of Things equipment integrated management system for highway construction according to claim 4 is characterized in that: The steps of the SVM algorithm in the monitoring and diagnosis module include: Feature extraction and selection: Extract important features from preprocessed cloud data, including time domain and frequency domain features; use correlation analysis and principal component analysis to select features that have a high contribution to anomaly detection; Model training: Use historical data for training and select RBF kernel function for classification; Real-time anomaly detection: real-time data is input into the SVM model, anomalies are detected and results are output; Abnormal handling and alarm: trigger alarm and notify maintenance personnel.

6. The Internet of Things equipment integrated management system for highway construction according to claim 1 is characterized in that: The remote control module is used to enable managers to control on-site construction equipment through a web interface or mobile application. Managers who have passed two-factor authentication can view the equipment status in the system and perform operations such as starting and stopping the equipment and adjusting parameters.

7. The integrated management system of Internet of Things equipment for highway construction according to claim 1 is characterized in that: The security management module is used to implement the functions of data encryption and output encryption, access control and security monitoring.

8. An integrated management method for Internet of Things devices for highway construction, characterized in that: The highway construction equipment is uniformly managed by using the integrated management system for Internet of Things equipment for highway construction as described in any one of claims 1 to 7.

Images