Tunnel environment real-time monitoring and evaluating system

Abstract

The invention relates to the technical field of tunnel environment monitoring, in particular to a tunnel environment real-time monitoring and evaluation system which comprises an environment monitoring module, a video monitoring module, a data transmission module, a data processing module, a ventilation adjusting module, a traffic signal control module, an information board issuing module and a user interaction module. The environment monitoring module collects tunnel environment data in real time, the video monitoring module obtains tunnel video data, the data transmission module transmits the data to the data processing module, and the data processing module processes the received data and evaluates the environment safety condition in the tunnel. The ventilation adjusting module automatically adjusts a ventilation system in the tunnel according to an evaluation result, the traffic signal control module automatically controls traffic lights, the information board issuing module issues early warning information through an electronic information board, and the user interaction module provides a visual interface; according to the invention, comprehensive, real-time and intelligent monitoring and adjustment of the environment in the tunnel can be realized, and the safety management level and the operation efficiency of the tunnel are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel environment monitoring, and in particular to a tunnel environment real-time monitoring and evaluation system. Background Art

[0002] Tunnels are an important part of modern transportation. Changes in their internal environment directly affect the safety of tunnels and the efficiency of vehicle traffic. In tunnels, real-time monitoring and evaluation of environmental factors such as gas composition, temperature, humidity and dust concentration are crucial. These environmental data are not only related to the long-term stability of the tunnel structure, but also have a direct impact on the safety of vehicles and personnel traveling in the tunnel. In order to ensure the safety and comfort of the tunnel environment, various environmental parameters inside the tunnel must be monitored in real time, and corresponding adjustment measures must be taken according to actual conditions.

[0003] In the prior art, tunnel environment monitoring mainly relies on regular manual detection and traditional fixed sensor monitoring, which has many shortcomings. First, the regular manual detection method is inefficient and cannot achieve real-time collection and analysis of environmental data, making it difficult to timely detect and handle emergencies such as gas leaks, fires, and abnormal humidity changes. Secondly, although the traditional fixed sensor monitoring system can provide certain automated monitoring functions, its data transmission and processing capabilities are limited and cannot fully cope with the complex environmental changes in the tunnel. In addition, these systems lack intelligent analysis and decision-making capabilities and cannot automatically adjust the ventilation system and traffic lights based on real-time data. Therefore, the prior art has obvious deficiencies in real-time, automation, and intelligence, and there is an urgent need for a system solution that can comprehensively, real-time, and intelligently monitor and adjust the tunnel environment. Summary of the invention

[0004] Based on the above objectives, the present invention provides a real-time monitoring and evaluation system for tunnel environment.

[0005] The tunnel environment real-time monitoring and evaluation system includes an environment monitoring module, a video monitoring module, a data transmission module, a data processing module, a ventilation adjustment module, a traffic signal control module, an information board publishing module and a user interaction module, among which;

[0006] The environmental monitoring module is installed at multiple locations in the tunnel to collect real-time environmental data in the tunnel, including gas composition, temperature, humidity and dust concentration;

[0007] The video monitoring module is used to monitor the environment in the tunnel and obtain video data;

[0008] The data transmission module uses a combination of wired and wireless methods to transmit the data collected by the environment monitoring module and the video monitoring module to the data processing module in real time, ensuring the timeliness and reliability of the data;

[0009] The data processing module includes a data preprocessing unit and an analysis and evaluation unit. The data preprocessing unit cleans, filters and formats the received environmental data and video data. The analysis and evaluation unit performs real-time analysis based on the processed data to evaluate the environmental safety status in the tunnel.

[0010] The ventilation adjustment module is connected to the data processing module and automatically adjusts the ventilation system in the tunnel according to the evaluation results of the analysis and evaluation unit, including a fan control unit and a vent control unit;

[0011] The traffic signal control module is connected to the data processing module, and automatically controls the traffic lights in the tunnel according to the environmental data in the tunnel and the video monitoring results to ensure the safe passage of vehicles;

[0012] The information board release module includes an electronic information board for releasing early warning information based on environmental monitoring and video surveillance data to remind drivers to pay attention to environmental changes in the tunnel;

[0013] The user interaction module provides a visual interface, displays real-time environmental data and video surveillance images in the tunnel, and provides system settings and data query functions.

[0014] Optionally, the environment monitoring module specifically includes:

[0015] Gas sensor: used to detect the gas composition in the tunnel, including carbon dioxide, carbon monoxide, methane and oxygen concentration;

[0016] Temperature sensor: used to monitor temperature changes in the tunnel;

[0017] Humidity sensor: used to monitor the humidity level in the tunnel;

[0018] Dust sensor: used to monitor the dust concentration in the tunnel.

[0019] Optionally, the video monitoring module includes:

[0020] Camera: used to capture real-time video images inside the tunnel;

[0021] Video storage device: used to store video data acquired by the camera, using high-capacity hard disk or cloud storage technology to ensure long-term preservation and quick access to video data.

[0022] Optionally, the data transmission module specifically includes:

[0023] Wired transmission: Optical fibers or cables are laid inside the tunnel to transmit the environmental data collected by the environmental monitoring module and the video data collected by the video monitoring module to the data processing module through a wired network;

[0024] Wireless transmission: Wi-Fi access points or 5G base stations are deployed inside the tunnel to cover the entire tunnel area. When wired transmission fails, the environmental data collected by the environmental monitoring module and the video data collected by the video monitoring module are transmitted to the data processing module through the wireless network. The wireless transmission part is mainly used to supplement the deficiencies of wired transmission to ensure that the data of all monitoring devices can be transmitted in real time.

[0025] Optionally, the data preprocessing unit specifically includes:

[0026] Data cleaning: interpolation method is used to fill the missing values ​​in the environmental data, and Gaussian filtering is used to perform image denoising on the video data;

[0027] Data filtering: Filter environmental data and video data to remove irrelevant or redundant data;

[0028] Data formatting: Convert data into a unified format for subsequent processing and analysis, including timestamp synchronization, data standardization, and data structuring.

[0029] Optionally, the analysis and evaluation unit specifically includes:

[0030] Time Series Analysis: Perform time series analysis on environmental data to detect trends and anomalies;

[0031] Video analysis: Use background subtraction and convolutional neural networks to analyze video data in real time to detect moving objects and anomalies;

[0032] Comprehensive assessment: Combine the analysis results of environmental data and video data to conduct an overall environmental safety assessment;

[0033] Risk prediction: Use linear regression models to model and predict historical data and real-time data to predict future environmental risks;

[0034] Warning generation: Generate warning information based on comprehensive assessment results and warning thresholds, and trigger corresponding safety measures.

[0035] Optionally, the ventilation adjustment module specifically includes:

[0036] Obtain analysis and evaluation results: The ventilation control module obtains the evaluation results of the analysis and evaluation unit in real time through the data interface, including the current and predicted values ​​of gas concentration, temperature, humidity and dust concentration;

[0037] Application of decision-making algorithm: The ventilation adjustment module applies the preset ventilation strategy decision algorithm based on the evaluation results to determine the control strategy of the fan and vents;

[0038] Fan control: according to the control strategy, send control signals to the fan control unit to start or stop the fan and adjust the fan speed;

[0039] Vent control: According to the control strategy, send control signals to the vent control unit to adjust the opening and closing status and position of the vent.

[0040] Optionally, the traffic signal control module specifically includes:

[0041] Obtain real-time data: The traffic signal control module obtains data from the environmental monitoring module and the video monitoring module in real time, including gas concentration, temperature, humidity, dust concentration, traffic flow, vehicle speed and video monitoring results;

[0042] Data analysis and decision-making: Use preset algorithms to analyze real-time environmental data and video surveillance results to assess the safety and traffic conditions in the tunnel;

[0043] Traffic light control: Based on the analysis results and decision rules, a control signal is sent to the traffic light control unit to adjust the status of the traffic light to ensure safe passage of vehicles.

[0044] Optionally, the information board publishing module specifically includes:

[0045] Acquisition of real-time data: The information board publishing module acquires environmental data and video data in real time;

[0046] Data analysis and decision-making: Use preset algorithms to analyze real-time environmental data and video surveillance results, evaluate the safety and traffic conditions in the tunnel, detect anomalies in environmental data and traffic flow, and generate warning information and traffic guidance information;

[0047] Information generation and release: The generated warning information and traffic guidance information are sent to the electronic information board for display, reminding drivers to pay attention to environmental changes and traffic conditions in the tunnel.

[0048] Optionally, the user interaction module specifically includes:

[0049] Obtain real-time data and video streams: The user interaction module obtains environmental data and video data in real time and ensures synchronous update of data and video;

[0050] Data visualization: Use charts and graphs to dynamically display real-time environmental data. For example, a line chart can be used to show the changing trend of gas concentration, and a bar chart can show the real-time values ​​of temperature and humidity.

[0051] Video display: embed a video player in the visual interface to display the monitoring images in the tunnel in real time, ensuring the clarity and smoothness of the video stream;

[0052] System settings interface: Provides a user interface that allows users to configure system parameters. Users can set gas concentration thresholds, temperature thresholds, alarm levels, etc. through elements such as input boxes, drop-down menus, and buttons;

[0053] Data query function: Provides a query interface that allows users to query historical data. Users can enter query conditions such as date range, specific sensor data, etc.

[0054] Beneficial effects of the present invention:

[0055] The present invention realizes the real-time collection and monitoring of environmental data such as gas composition, temperature, humidity and dust concentration in the tunnel through the comprehensive application of the environmental monitoring module and the video monitoring module. The system can automatically adjust the ventilation system in the tunnel, including the control of the fan and the vent, according to the evaluation results of the analysis and evaluation unit, to ensure air quality and environmental safety. In addition, the traffic signal control module can automatically adjust the traffic lights in the tunnel according to the environmental data and video monitoring results to ensure that vehicles can pass safely when the environment is abnormal or traffic is congested. This real-time monitoring and automatic adjustment function greatly improves the safety management level of the tunnel, reduces the need for manual intervention, and improves the response speed and efficiency of the system.

[0056] In the present invention, the information board release module in the system releases early warning information and traffic guidance information in real time through the electronic information board, reminding the driver to pay attention to the environmental changes in the tunnel. Through the comprehensive analysis of environmental monitoring data and video surveillance data, the system can generate early warning information in time, such as "gas leakage in the tunnel, please drive carefully", "fire in the tunnel ahead, please evacuate immediately", "high dust concentration in the tunnel, please close the car window", etc., to ensure that the driver can take timely response measures. In addition, the system can also provide traffic guidance information, such as "the tunnel ahead is congested, please slow down", "the speed limit in the tunnel is 40 kilometers", etc., which improves the safety and orderliness of the traffic in the tunnel. This comprehensive early warning and information release function significantly enhances the security guarantee capability and traffic management level in the tunnel.

[0057] In the present invention, the user interaction module provides an intuitive visual interface, displays real-time environmental data and video surveillance images in the tunnel, and provides system settings and data query functions. Users can view real-time data such as gas concentration, temperature, humidity and dust concentration through the interface, watch the surveillance video in the tunnel, and understand the actual situation in the tunnel. At the same time, users can adjust system parameters such as gas concentration threshold, temperature threshold, alarm level, etc. through the setting interface to meet the needs of different situations. This user-friendly and intelligent interactive design improves the ease of use and operability of the system, allowing tunnel managers to monitor and manage more efficiently. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0059] Figure 1 A schematic diagram of a system flow of an embodiment of the present invention;

[0060] Figure 2 The figure is a flowchart of a data processing module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0061] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0062] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0063] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0064] like Figure 1-Figure 2 As shown, the tunnel environment real-time monitoring and evaluation system includes an environment monitoring module, a video monitoring module, a data transmission module, a data processing module, a ventilation adjustment module, a traffic signal control module, an information board publishing module and a user interaction module, wherein;

[0065] The environmental monitoring module is installed at multiple locations in the tunnel to collect real-time environmental data in the tunnel, including gas composition, temperature, humidity and dust concentration;

[0066] The video monitoring module is used to monitor the environment in the tunnel and obtain video data;

[0067] The data transmission module uses a combination of wired and wireless methods to transmit the data collected by the environment monitoring module and the video monitoring module to the data processing module in real time, ensuring the timeliness and reliability of the data;

[0068] The data processing module includes a data preprocessing unit and an analysis and evaluation unit. The data preprocessing unit cleans, filters and formats the received environmental data and video data. The analysis and evaluation unit performs real-time analysis based on the processed data to evaluate the environmental safety status in the tunnel.

[0069] The ventilation adjustment module is connected to the data processing module and automatically adjusts the ventilation system in the tunnel according to the evaluation results of the analysis and evaluation unit, including a fan control unit and a vent control unit;

[0070] The traffic signal control module is connected to the data processing module, and automatically controls the traffic lights in the tunnel according to the environmental data in the tunnel and the video monitoring results to ensure the safe passage of vehicles;

[0071] The information board release module includes an electronic information board for releasing early warning information based on environmental monitoring and video surveillance data to remind drivers to pay attention to environmental changes in the tunnel;

[0072] The user interaction module provides a visual interface, displays real-time environmental data and video surveillance images in the tunnel, and provides system settings and data query functions.

[0073] Optionally, the environment monitoring module specifically includes:

[0074] Gas sensor: used to detect gas composition in the tunnel, including carbon dioxide, carbon monoxide, methane and oxygen concentrations. By installing multiple gas sensors at different locations in the tunnel, especially in areas with poor air flow and easy accumulation of harmful gases, the gas composition and concentration can be measured in real time.

[0075] Temperature sensor: used to monitor temperature changes in the tunnel. Temperature sensors are installed at multiple locations in the tunnel to ensure comprehensive coverage of temperature data.

[0076] Humidity sensor: used to monitor the humidity level in the tunnel. Humidity sensors are installed at multiple locations in the tunnel together with temperature sensors to measure the ambient humidity in real time.

[0077] Dust sensor: used to monitor the dust concentration in the tunnel. Dust sensors are installed at multiple key locations in the tunnel to measure the concentration of dust particles in the air in real time.

[0078] Optionally, the video monitoring module includes:

[0079] Camera: used to capture real-time video images inside the tunnel. Multiple high-definition cameras are installed at key locations in the tunnel (such as entrances, exits, turns, and the middle of the tunnel). The cameras are equipped with night vision capabilities to ensure that clear video images can be obtained even in low-light conditions.

[0080] Video storage device: used to store video data acquired by the camera, using high-capacity hard disk or cloud storage technology to ensure long-term preservation and quick access to video data.

[0081] Optionally, the data transmission module specifically includes:

[0082] Wired transmission: Optical fibers or cables are laid inside the tunnel to transmit the environmental data collected by the environmental monitoring module and the video data collected by the video monitoring module to the data processing module through the wired network. The wired transmission part is mainly responsible for high-bandwidth, low-latency data transmission, and is particularly suitable for the transmission of large-volume data such as video data;

[0083] Wireless transmission: Wi-Fi access points or 5G base stations are deployed inside the tunnel to cover the entire tunnel area. When wired transmission fails, the environmental data collected by the environmental monitoring module and the video data collected by the video monitoring module are transmitted to the data processing module through the wireless network. The wireless transmission part is mainly used to supplement the deficiencies of wired transmission to ensure that the data of all monitoring devices can be transmitted in real time.

[0084] Optionally, the data preprocessing unit specifically includes:

[0085] Data cleaning: interpolation method is used to fill the missing values ​​in the environmental data, and Gaussian filtering is used to perform image denoising on the video data;

[0086] (1) Filling missing values: For time series data, linear interpolation is used to fill missing values, expressed as:

[0087]

[0088] Where t1 and t2 are the time points before and after the missing value, and x(t1) and x(t2) are the corresponding values;

[0089] (2) Gaussian filtering: Use a Gaussian filter to smooth the image and reduce noise, expressed as:

[0090]

[0091] Among them, G(x,y) is the Gaussian kernel function, σ is the standard deviation;

[0092] Data filtering: Filter environmental data and video data to remove irrelevant or redundant data, as follows:

[0093] Environmental data filtering: Filter out invalid data from environmental sensor data based on the set threshold range, for example, only retain temperature, humidity, and gas concentration data within a reasonable range;

[0094] Video data filtering: Use background subtraction or image segmentation technology to filter out irrelevant background information in the video and highlight environmental changes or abnormal situations;

[0095] Data formatting: converting data into a unified format for subsequent processing and analysis, including timestamp synchronization, data standardization, and data structuring, among which;

[0096] Timestamp synchronization: add a unified timestamp to all data to ensure the time synchronization of data;

[0097] Data standardization: convert environmental data and video data into standardized formats, such as temperature data into degrees Celsius, gas concentration data into ppm, etc.

[0098] Data structuring: Organize data into structured formats, such as JSON, CSV, or database tables, to facilitate subsequent processing and storage.

[0099] Optionally, the analysis and evaluation unit specifically includes:

[0100] Time Series Analysis: Perform time series analysis on environmental data to detect trends and anomalies, as shown below:

[0101] (1) Trend detection: Detect the long-term trend and seasonal changes of data through moving average, difference method and seasonal decomposition method, among which;

[0102] Moving average method: By calculating the moving average of the data, smoothing the data, and detecting long-term trends, it is expressed as:

[0103]

[0104] Among them, MA t is the moving average at time point t, X t is the original data at time point t, n is the moving average window size;

[0105] Difference method: By calculating the difference of data, the trend and seasonality of the data are eliminated and a stationary series is obtained, which is expressed as:

[0106] ΔX t =X t -X t-1 ;

[0107] Where ΔX t is the difference value at time point t, X t is the original data at time point t;

[0108] Seasonal decomposition: Decompose the time series into three parts: trend, seasonality and residual, expressed as:

[0109] X t =T t +S t +R t ;

[0110] Among them, X t is the original data at time point t, T t is the trend part at time point t, S t is the seasonal part at time point t, R t is the residual part at time point t;

[0111] (2) Anomaly detection: Identify outliers in the data through statistical methods;

[0112] Anomaly detection based on statistical methods: Use mean and standard deviation to detect outliers, expressed as:

[0113] if|X t -μ|>kσthen X t is an anomaly;

[0114] Among them, μ is the data mean, σ is the standard deviation, and k is the detection threshold (usually 2 or 3);

[0115] Video Analysis: Use background subtraction and convolutional neural networks to analyze video data in real time to detect moving objects and anomalies, including;

[0116] (1) Background subtraction: used to detect moving targets in videos, such as smoke and flames, expressed as:

[0117] D(x,y)=|I t (x,y)-B(x,y)|;

[0118] Where D(x,y) is the difference image, I t (x,y) is the current frame, B(x,y) is the background model;

[0119] (2) Convolutional neural network: used for object detection in video images, expressed as:

[0120] f(x) = ReLU(W*x+b);

[0121] Where f(x) is the feature map, W is the convolution kernel, * represents the convolution operation, b is the bias, and ReLU is the activation function;

[0122] Comprehensive assessment: Combine the analysis results of environmental data and video data to conduct an overall environmental safety assessment, expressed as:

[0123] S=w1S env +w2S video ;

[0124] Among them, S is the comprehensive evaluation score, S env is the environmental data assessment score, S video is the video data evaluation score, w1 and w2 are weights;

[0125] Risk prediction: Use linear regression models to model and predict historical data and real-time data to predict future environmental risks. The specific steps are as follows:

[0126] (1) Data collection: Collect historical and real-time environmental data in the tunnel, such as gas composition, temperature, humidity, and dust concentration;

[0127] (2) Data processing: processing the collected data, including data cleaning and data standardization;

[0128] (3) Feature selection: Select features that have an important impact on environmental risk prediction, such as gas concentration, temperature, humidity, and historical trend data;

[0129] (4) Create feature vectors: Convert historical data and real-time data into feature vectors for training and prediction of regression models;

[0130] (5) Model construction: Construct a linear regression model. The model formula is expressed as:

[0131]

[0132] in, is the predicted value, x i is the characteristic variable, β i is the regression coefficient, and the least squares method is used to fit the model parameters, which is expressed as:

[0133]

[0134] Among them, y i is the actual value, is the predicted value, m is the number of samples;

[0135] (6) Model training and evaluation: Divide the data into training set and test set for model training and evaluation. Use the training set data to train the linear regression model and determine the model parameters. Use the test set data to evaluate the model performance.

[0136] (7) Real-time prediction: Collect environmental data in the tunnel in real time, generate real-time feature vectors, input the real-time feature vectors into the trained linear regression model, and predict future environmental risks;

[0137] Warning generation: Generate warning information based on comprehensive evaluation results and warning thresholds, and trigger corresponding safety measures, expressed as:

[0138] if S>T then trigger alert;

[0139] Among them, S is the comprehensive evaluation score, and T is the warning threshold;

[0140] The analysis and evaluation unit can efficiently and accurately process and analyze the environmental data and video data in the tunnel, evaluate the environmental safety status in the tunnel in real time, and generate early warning information in a timely manner.

[0141] Optionally, the ventilation adjustment module specifically includes:

[0142] Obtain analysis and evaluation results: The ventilation control module obtains the evaluation results of the analysis and evaluation unit in real time through the data interface, including the current and predicted values ​​of gas concentration, temperature, humidity and dust concentration;

[0143] Application of decision-making algorithm: The ventilation adjustment module applies the preset ventilation strategy decision algorithm based on the evaluation results to determine the control strategy of the fan and vents;

[0144] Examples of ventilation strategies:

[0145] When excessive gas concentration is detected, increase the fan speed or open more vents;

[0146] When the temperature is too high, increase ventilation to reduce the temperature;

[0147] When dust concentrations are high, adjust vent locations and air speeds to optimize air circulation;

[0148] Fan control: according to the control strategy, send control signals to the fan control unit to start or stop the fan and adjust the fan speed;

[0149] The fan start and stop control is expressed as:

[0150]

[0151] Among them, C gas is the current gas concentration, T gas is the gas concentration threshold, T temp is the current temperature, is the temperature threshold;

[0152] Wind speed regulation is expressed as:

[0153]

[0154] Among them, v fan is the wind speed of the fan, k1 and k2 are the adjustment coefficients;

[0155] Vent control: According to the control strategy, a control signal is sent to the vent control unit to adjust the opening and closing state and position of the vent, which is expressed as:

[0156] iC dust >T dust then open the vent;

[0157] Among them, C dust is the current dust concentration, T dust is the dust concentration threshold;

[0158] The ventilation adjustment module can automatically adjust the ventilation system in the tunnel according to the evaluation results of the analysis and evaluation unit, including the control of fans and vents, to ensure environmental safety and air quality in the tunnel.

[0159] Optionally, the traffic signal control module specifically includes:

[0160] Obtain real-time data: The traffic signal control module obtains data from the environmental monitoring module and the video monitoring module in real time, including gas concentration, temperature, humidity, dust concentration, traffic flow, vehicle speed and video monitoring results;

[0161] Data analysis and decision-making: Use preset algorithms to analyze real-time environmental data and video surveillance results to assess the safety and traffic conditions in the tunnel, including:

[0162] (1) Anomaly detection: Detecting anomalies in environmental data, such as gas leaks, fire risks, or high dust concentrations, expressed as:

[0163]

[0164] Among them, C gas is the current gas concentration, T gas is the gas concentration threshold, T temp is the current temperature, is the temperature threshold, C dust is the current dust concentration, T dust is the dust concentration threshold;

[0165] (2) Traffic flow analysis: Analyze traffic flow and vehicle speed in video surveillance data to detect traffic congestion or accidents;

[0166] Traffic flow detection: Use computer vision algorithms to analyze video data and detect traffic flow and vehicle speed, expressed as:

[0167] Among them, Q is the traffic flow (the number of vehicles passing a certain point per unit time), N is the number of vehicles passing during the detection period, and T is the detection period;

[0168] Traffic congestion detection is expressed as: If V <V threshold then set signal to red;

[0169] Where V is the vehicle speed, V threshold is the speed threshold;

[0170] Traffic light control: Based on the analysis results and decision rules, a control signal is sent to the traffic light control unit to adjust the status of the traffic light to ensure safe passage of vehicles;

[0171] The traffic signal control module can automatically control the traffic lights in the tunnel according to the environmental data and video surveillance results in the tunnel to ensure the safe passage of vehicles.

[0172] Optionally, the information board publishing module specifically includes:

[0173] Acquisition of real-time data: The information board publishing module acquires environmental data and video data in real time;

[0174] Data analysis and decision-making: Use preset algorithms to analyze real-time environmental data and video surveillance results, evaluate the safety and traffic conditions in the tunnel, detect anomalies in environmental data and traffic flow, and generate warning information and traffic guidance information;

[0175] Warning information: such as "Gas leakage in the tunnel, please drive carefully", "Fire in the tunnel ahead, please evacuate immediately", "Dust concentration in the tunnel is high, please close the car windows", etc.;

[0176] Traffic guidance: such as "The tunnel ahead is congested, please slow down", "The speed limit in the tunnel is 40 kilometers", etc.;

[0177] Information generation and release: The generated warning information and traffic guidance information are sent to the electronic information board for display, reminding drivers to pay attention to environmental changes and traffic conditions in the tunnel.

[0178] Optionally, the user interaction module specifically includes:

[0179] Obtain real-time data and video streams: The user interaction module obtains environmental data and video data in real time and ensures synchronous update of data and video;

[0180] Data visualization: Use charts and graphs to dynamically display real-time environmental data. For example, a line chart can be used to show the changing trend of gas concentration, and a bar chart can show the real-time values ​​of temperature and humidity.

[0181] Video display: embed a video player in the visual interface to display the monitoring images in the tunnel in real time, ensuring the clarity and smoothness of the video stream;

[0182] System settings interface: Provides a user interface that allows users to configure system parameters. Users can set gas concentration thresholds, temperature thresholds, alarm levels, etc. through elements such as input boxes, drop-down menus, and buttons;

[0183] Data query function: Provides a query interface that allows users to query historical data. Users can enter query conditions such as date range, specific sensor data, etc.

[0184] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0185] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. Tunnel environment real-time monitoring and evaluation system, characterized by: It includes environment monitoring module, video monitoring module, data transmission module, data processing module, ventilation adjustment module, traffic signal control module, information board publishing module and user interaction module, among which; The environmental monitoring module is used to collect environmental data in the tunnel in real time, and the environmental data includes gas composition, temperature, humidity and dust concentration; The video monitoring module is used to monitor the environment in the tunnel and obtain video data; The data transmission module uses a combination of wired and wireless methods to transmit the data collected by the environment monitoring module and the video monitoring module to the data processing module in real time; The data processing module includes a data preprocessing unit and an analysis and evaluation unit. The data preprocessing unit cleans, filters and formats the received environmental data and video data. The analysis and evaluation unit performs real-time analysis based on the processed data to evaluate the environmental safety status in the tunnel. The ventilation adjustment module is connected to the data processing module and automatically adjusts the ventilation system in the tunnel according to the evaluation results of the analysis and evaluation unit, including a fan control unit and a vent control unit; The traffic signal control module is connected to the data processing module and automatically controls the traffic lights in the tunnel according to the environmental data in the tunnel and the video monitoring results; The information board release module includes an electronic information board for releasing early warning information based on environmental monitoring and video surveillance data to remind drivers to pay attention to environmental changes in the tunnel; The user interaction module provides a visual interface, displays real-time environmental data and video surveillance images in the tunnel, and provides system settings and data query functions.

2. The tunnel environment real-time monitoring and evaluation system according to claim 1 is characterized in that: The environmental monitoring module specifically includes: Gas sensor: used to detect the gas composition in the tunnel, including carbon dioxide, carbon monoxide, methane and oxygen concentration; Temperature sensor: used to monitor temperature changes in the tunnel; Humidity sensor: used to monitor the humidity level in the tunnel; Dust sensor: used to monitor the dust concentration in the tunnel.

3. The tunnel environment real-time monitoring and evaluation system according to claim 1 is characterized in that: The video monitoring module comprises: Camera: used to capture real-time video images inside the tunnel; Video storage device: used to store video data acquired by the camera.

4. The tunnel environment real-time monitoring and evaluation system according to claim 1 is characterized in that: The data transmission module specifically includes: Wired transmission: Optical fibers or cables are laid inside the tunnel to transmit the environmental data collected by the environmental monitoring module and the video data collected by the video monitoring module to the data processing module through a wired network; Wireless transmission: Wi-Fi access points or 5G base stations are deployed inside the tunnel to cover the entire tunnel area. When wired transmission fails, the environmental data collected by the environmental monitoring module and the video data collected by the video monitoring module are transmitted to the data processing module through the wireless network.

5. The tunnel environment real-time monitoring and evaluation system according to claim 1 is characterized in that: The data preprocessing unit specifically includes: Data cleaning: interpolation method is used to fill the missing values ​​in the environmental data, and Gaussian filtering is used to perform image denoising on the video data; Data filtering: Filter environmental data and video data to remove irrelevant or redundant data; Data formatting: Convert data into a unified format for subsequent processing and analysis, including timestamp synchronization, data standardization, and data structuring.

6. The tunnel environment real-time monitoring and evaluation system according to claim 5 is characterized in that: The analysis and evaluation unit specifically includes: Time Series Analysis: Perform time series analysis on environmental data to detect trends and anomalies; Video analysis: Use background subtraction and convolutional neural networks to analyze video data in real time to detect moving objects and anomalies; Comprehensive assessment: Combine the analysis results of environmental data and video data to conduct an overall environmental safety assessment; Risk prediction: Use linear regression models to model and predict historical data and real-time data to predict future environmental risks; Warning generation: Generate warning information based on comprehensive assessment results and warning thresholds, and trigger corresponding safety measures.

7. The tunnel environment real-time monitoring and evaluation system according to claim 6 is characterized in that: The ventilation adjustment module specifically includes: Obtain analysis and evaluation results: The ventilation control module obtains the evaluation results of the analysis and evaluation unit in real time through the data interface, including the current and predicted values ​​of gas concentration, temperature, humidity and dust concentration; Application of decision-making algorithm: The ventilation adjustment module applies the preset ventilation strategy decision algorithm based on the evaluation results to determine the control strategy of the fan and vents; Fan control: according to the control strategy, send control signals to the fan control unit to start or stop the fan and adjust the fan speed; Vent control: According to the control strategy, send control signals to the vent control unit to adjust the opening and closing status and position of the vent.

8. The tunnel environment real-time monitoring and evaluation system according to claim 6 is characterized in that: The traffic signal control module specifically includes: Obtain real-time data: The traffic signal control module obtains data from the environmental monitoring module and the video monitoring module in real time, including gas concentration, temperature, humidity, dust concentration, traffic flow, vehicle speed and video monitoring results; Data analysis and decision-making: Use preset algorithms to analyze real-time environmental data and video surveillance results to assess the safety and traffic conditions in the tunnel; Traffic light control: Based on the analysis results and decision rules, a control signal is sent to the traffic light control unit to adjust the status of the traffic light.

9. The tunnel environment real-time monitoring and evaluation system according to claim 1, characterized in that: The information board publishing module specifically includes: Acquisition of real-time data: The information board publishing module acquires environmental data and video data in real time; Data analysis and decision-making: Use preset algorithms to analyze real-time environmental data and video surveillance results, evaluate the safety and traffic conditions in the tunnel, detect anomalies in environmental data and traffic flow, and generate warning information and traffic guidance information; Information generation and release: The generated warning information and traffic guidance information are sent to the electronic information board for display, reminding drivers to pay attention to environmental changes and traffic conditions in the tunnel.

10. The tunnel environment real-time monitoring and evaluation system according to claim 1, characterized in that: The user interaction module specifically includes: Obtain real-time data and video streams: The user interaction module obtains environmental data and video data in real time and ensures synchronous update of data and video; Data visualization: Use charts and graphs to dynamically display real-time environmental data; Video display: embed a video player in the visual interface to display the monitoring images in the tunnel in real time; System settings interface: provides a user interface that allows users to configure system parameters; Data query function: provides a query interface that allows users to query historical data.

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