Tunnel event management platform

Abstract

The present invention relates to the field of intelligent tunnel management and control, and in particular to technical fields such as tunnel event detection, linkage control, and emergency response plans, and discloses a tunnel event management and control platform, including an intelligent control module, an intelligent perception module, an intelligent interconnection module, and an inspection and maintenance APP. The platform is provided with a dual-active information synchronization and coordination framework through the intelligent control module, and the dual-active information synchronization and coordination framework includes an L0 controller, an L2 edge computing device, and a variety of tunnel devices. The L0 controller and the L2 edge computing device perform data synchronization and coordination through a soft bus, which ensures safe operation in the tunnel, reduces the system construction and maintenance costs, has low network construction costs, can perceive abnormal events in tunnel traffic with high precision, has a fast response speed for comprehensive monitoring perception, and the inspection and maintenance APP synchronously obtains the operation and maintenance information inside the tunnel, and has a flexible backup system architecture and stable communication quality.

Description

Technical Field

[0001] The present invention relates to the field of intelligent tunnel management and control, and in particular to technical fields such as tunnel event detection, linkage control and emergency response plans, and specifically to a tunnel event management and control platform. Background Art

[0002] With the rapid development of the transportation sector, tunnels, as one of the important transportation infrastructures, are particularly important in terms of management and operation. Traditional tunnel management systems usually use sensors and control devices based on wired networks, which have a series of problems such as closed-source electromechanical equipment operating systems, communication isolation, and network instability. These problems have led to low tunnel operation efficiency and high management costs.

[0003] For tunnel management systems, traditional technical solutions have the following main problems and shortcomings:

[0004] 1. High cost: The traditional tunnel management system has high construction costs, including equipment procurement, installation and maintenance costs, which limits its promotion and application in more tunnels.

[0005] 2. Insufficient monitoring support: Traditional systems have limited monitoring capabilities for traffic targets in tunnels and cannot achieve comprehensive and real-time monitoring of tunnels, making it difficult for operators to be informed of abnormal situations in a timely manner.

[0006] 3. Inflexible backup strategy: The data backup strategy of traditional systems is usually simple, lacking flexibility and intelligence. Once a failure or data loss occurs, the efficiency of restoring backup data is low.

[0007] 4. Unstable network structure: The communication network structure used by traditional systems is relatively simple and easily affected by external interference or its own failures, resulting in frequent communication problems or interruptions. Summary of the invention

[0008] 1. Technical issues to be resolved

[0009] In view of the shortcomings of the prior art, the present invention provides a tunnel event management and control platform, which has the advantages of low network construction cost, fast comprehensive monitoring perception response speed, stable flexible backup system architecture, more stable and reliable communication quality, etc. It solves the problems of high cost, insufficient monitoring support, inflexible backup strategy and unstable network structure of traditional tunnel management systems.

[0010] (II) Technical solution

[0011] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: the tunnel event management and control platform includes a smart control module, a smart perception module, a smart interconnection module and an inspection and maintenance APP, and the inspection and maintenance APP is interconnected with the smart control module and the smart interconnection module through a network;

[0012] The intelligent control module is provided with a dual-active information synchronization and coordination framework, which includes an L0 controller, an L2 edge computing device, a tunnel safety device, a tunnel monitoring device, a tunnel electromechanical device and a tunnel sensing device. The L0 controller and the L2 edge computing device perform data synchronization and coordination through a soft bus. The L0 controller is interconnected with the tunnel safety device and the inspection and maintenance APP through a network. The L0 controller collects a safety data set through a network connection with the tunnel safety device. The safety data set includes the operating power of the fan device, the illumination of the lighting device and the volume of carbon monoxide gas. The L2 edge computing device is provided with an edge gateway. The edge gateway is interconnected with the tunnel monitoring device, the tunnel electromechanical device and the tunnel sensing device through a network. The L2 edge computing device collects an intelligence data set through the edge gateway. The intelligence data set includes the monitoring data of all sections in the tunnel, the intelligence board data of all exits of the tunnel and the sensing data in the tunnel. The L2 edge computing device calculates and generates a safety data set based on the safety data set. The L2 edge computing device generates an intelligence data set based on the intelligence data set. ;

[0013] The intelligent perception module is equipped with a radar-visual integrated machine and a video management platform. The radar-visual integrated machine collects monitoring data sets in real time and transmits them to the video management platform through the network. The monitoring data sets include the driving data of all vehicles in the tunnel. The video management platform performs event detection based on the monitoring data sets and screens and generates key events. and transmitted to the smart interconnection module through the network;

[0014] The smart interconnection module allows users to visually edit and use configuration tools to build mobile applications and web pages through the LoC display engine. The smart interconnection module is provided with an interconnection adaptation layer and an Internet of Things platform. The interconnection adaptation layer connects the eSight system, lighting system, fire alarm system, power monitoring system, fire pool system and emergency telephone broadcasting system, the Internet of Things platform and the smart perception module through the network. The interconnection adaptation layer processes all access data in the Kafka message queue through the API and transmits it to the Internet of Things platform through the network. The Internet of Things platform converts the processed access data into a physical model through the Internet of Things technology and transmits it to the L2 edge computing device through the network.

[0015] Preferably, the L0 controller is provided with an electromechanical APP, which includes an IoT SDK and an electromechanical SDK. The electromechanical SDK collects a safety data set through a network connection to tunnel safety equipment, which includes a fan device, a lighting device, and a COVI detector. The expression of the safety data set is: , Indicates the operating power of the fan equipment. Indicates the illumination of the lighting equipment. Indicates the volume of carbon monoxide gas in the tunnel detected by the COVI detector.

[0016] Preferably, the edge gateway is provided with an IoT Edge, which is interconnected with the tunnel monitoring equipment and collects monitoring data of all sections in the tunnel. The IoT Edge is connected to the tunnel electromechanical equipment through the network and collects information board data at all exits of the tunnel. The edge gateway is connected to the electromechanical adapter device through the network, and the electromechanical adapter device is connected to the tunnel sensor equipment through the network and collects sensor data inside the tunnel.

[0017] Preferably, the expression of the intelligence data set is , Indicates the monitoring data of all sections collected by tunnel monitoring equipment. Indicates the information board data of all exits collected by tunnel electromechanical equipment, Represents the vehicle flow sensor data collected by the tunnel sensor equipment.

[0018] Preferably, the expression of the monitoring data set is , to This corresponds to the driving data of each vehicle in the tunnel.

[0019] Preferably, the safety data set The calculation formula is as follows:

[0020] ;

[0021] In the formula, Denotes a safety data group, Indicates the wind pressure data in the tunnel. represents the ventilation efficiency in the tunnel, It represents the operating power of the tunnel fan equipment divided by the product of wind pressure and ventilation efficiency, and the tunnel ventilation volume is obtained. represents the surface area inside the tunnel, Indicates the total number of tunnel lighting equipment, It means the illumination of the tunnel lighting equipment multiplied by the total number to get the total lighting brightness of the tunnel lighting equipment. represents the surface area inside the tunnel, represents the average lighting brightness inside the tunnel, represents the total volume of the tunnel interior space, The carbon monoxide concentration in the tunnel is obtained by dividing the carbon monoxide gas volume of the tunnel COVI detector by the total volume of the tunnel's internal space. represents the fixed parameter defining the air quality in the SDS calculation formula, The ratio of the actual carbon monoxide concentration in the tunnel to the fixed parameters is the air quality index. The safety data set includes tunnel ventilation volume, average lighting brightness and air quality index.

[0022] Preferably, the intelligence data set The calculation formula is as follows:

[0023] ;

[0024] In the formula, represents the intelligence data group, It represents the comprehensive safety data group, key events, all road section monitoring data, all exit information board data and vehicle flow sensor data, and obtains the intelligence data group.

[0025] Preferably, the video management platform performs event detection based on the monitoring data set, and screens and generates key events , the calculation process is as follows:

[0026] According to the monitoring data set, the time points of all vehicles entering and exiting the tunnel are counted and recorded as ,in , Indicates the time when the vehicle enters the tunnel. Indicates the time when the vehicle exits the tunnel. to Corresponding to the time points when each vehicle enters and exits the tunnel;

[0027] ;

[0028] ;

[0029] In the formula, Indicates key events. Indicates the normal length of time it takes for a vehicle to enter and exit a tunnel. represents the tunnel length, Indicates the maximum speed limit for vehicles in the tunnel. It represents the length of the tunnel divided by the maximum driving speed, which gives the normal time it takes for a vehicle to enter and exit the tunnel. represents the time taken by the actual vehicles in the monitoring dataset to enter and exit the tunnel, Indicates the ratio of the actual time to the normal time. If the ratio is greater than 1, the vehicle is marked as a key vehicle. Indicates the time points at which all vehicles enter and exit the tunnel , filter out the key vehicles whose actual time exceeds the normal time, which are the key events.

[0030] Preferably, the L2 edge computing device is provided with a segmented grouping management framework and a control screen, wherein the segmented grouping management framework groups all access data in sequence, and the key events When there is data in the L2 edge computing device, it is output through the control screen first.

[0031] Preferably, the inspection and maintenance APP is interconnected with the L0 controller through a network, and the inspection and maintenance APP, L0 controller, L2 edge computing device, Internet of Things platform and interconnection adaptation layer form a network closed loop, and the inspection and maintenance APP synchronously obtains the security data set, intelligence data set, monitoring data set and security data set related to the operation and maintenance inside the tunnel. , Intelligence Data Group and key events .

[0032] Compared with the prior art, the present invention provides a tunnel event management and control platform, which has the following beneficial effects:

[0033] 1. The present invention sets up a smart control module, a smart perception module, a smart interconnection module and an inspection and maintenance APP through a tunnel event management and control platform. The smart control module is provided with a dual-active information synchronization and coordination framework. The dual-active information synchronization and coordination framework includes an L0 controller, an L2 edge computing device, a tunnel safety device, a tunnel monitoring device, a tunnel electromechanical device and a tunnel sensing device. The L0 controller and the L2 edge computing device perform data synchronization and coordination through a soft bus. The L0 controller collects a security data set through a network connection with the tunnel safety device. The L2 edge computing device calculates and generates a security data set based on the security data set. , while ensuring safe operation in the tunnel, a more economical and practical management solution can be adopted to reduce the cost of system construction and maintenance. It is also suitable for tunnel operation needs of different scales, and the network construction cost is low.

[0034] 2. The present invention is provided with an edge gateway through an L2 edge computing device, and the edge gateway is interconnected with the tunnel monitoring device, the tunnel electromechanical equipment and the tunnel sensing device through a network. The L2 edge computing device collects intelligence data sets through the edge gateway, and the L2 edge computing device calculates and generates intelligence data sets according to the intelligence data sets. , comprehensively collect multi-terminal data, realize the adaptation of electromechanical equipment of different types and brands, so that it can achieve effective data exchange and communication with the intelligent control module. The intelligent perception module collects monitoring data sets in real time through the integrated radar vision machine, performs event detection, and screens and generates key events , high-precision perception realizes comprehensive identification without blind spots, sensitively perceives abnormal events, and continuously tracks key vehicles, with comprehensive monitoring perception and fast response speed.

[0035] 3. The present invention can perform command control, information transmission, and status monitoring on the L0 controller through the L2 edge computing device. Secondly, the L2 edge computing device itself has the edge computing capability to execute local business applications, plan strategies, and temporarily take over the control of the devices under its jurisdiction. The L2 edge computing device has soft bus communication capability and can build a soft bus information communication link with multiple devices, providing a backup communication link for the management and communication of the overall electromechanical equipment, thereby improving the robustness and high availability of the overall system, eliminating communication bottlenecks, and ensuring the normal operation of tunnel services in the event of a core device interruption. The flexible backup system architecture is stable, thereby improving the fault tolerance and stability of the overall system.

[0036] 4. The present invention forms a network closed loop through the inspection and maintenance APP, L0 controller, L2 edge computing device, Internet of Things platform and interconnection adaptation layer, so that the information reported by the L0 controller is transparently transmitted to the Internet of Things platform through iot-edge, and the upper control message from the Internet of Things platform is sent to the L0 controller through iot-edge. The inspection and maintenance APP simultaneously obtains the operation and maintenance information inside the tunnel. Through intelligent perception and one-key linkage control, the tunnel operation management level and emergency response capability are improved, the processing efficiency of emergency events is accelerated, and the communication quality is more stable and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] See also Figure 1 The tunnel event management and control platform includes a smart control module, a smart perception module, a smart interconnection module and an inspection and maintenance APP. The inspection and maintenance APP is interconnected with the smart control module and the smart interconnection module through the network;

[0040] The intelligent control module is equipped with a dual-active information synchronization and coordination framework, which includes L0 controller, L2 edge computing device, tunnel safety equipment, tunnel monitoring equipment, tunnel electromechanical equipment and tunnel sensing equipment. The L0 controller and L2 edge computing device synchronize data through the soft bus. The L2 edge computing device can perform command control, information transparent transmission and status monitoring for the L0 controller. Secondly, the L2 edge computing device itself has the edge computing ability to execute local business applications, plan strategies, and temporarily take over the control of the equipment under its jurisdiction. The L2 edge computing device has the soft bus communication capability and can build a soft bus information communication link with multiple devices, providing a backup communication link for the management and communication of the overall electromechanical equipment, thereby improving the robustness and high availability of the overall system, eliminating communication bottlenecks, and ensuring the normal operation of tunnel business in the event of a core device interruption. The flexible backup system architecture is stable, which improves the fault tolerance and stability of the overall system.

[0041] The L0 controller is interconnected with the tunnel safety equipment and the inspection and maintenance APP through the network. The L0 controller collects the safety data set through the network connection with the tunnel safety equipment. The safety data set includes the operating power of the fan equipment, the illumination of the lighting equipment and the volume of carbon monoxide gas. The L0 controller is equipped with an electromechanical APP. The electromechanical APP includes the Internet of Things SDK and the electromechanical SDK. While realizing data exchange and communication between devices, it can accurately control the electromechanical equipment. The electromechanical SDK collects the safety data set through the network connection with the tunnel safety equipment. The tunnel safety equipment includes the fan equipment, the lighting equipment and the COVI detector. The expression of the safety data set is , Indicates the operating power of the fan equipment, which is convenient for subsequent calculation of the specific ventilation volume. Indicates the illumination of lighting equipment to ensure the safety of tunnel traffic. Indicates the volume of carbon monoxide gas in the tunnel detected by the COVI detector, monitors the air quality in the tunnel in real time, improves the safety of vehicles passing through the tunnel, remotely monitors and manages tunnel safety equipment, promptly detects equipment failures and abnormal conditions, and improves the efficiency and quality of operation and maintenance work;

[0042] The L2 edge computing device is provided with an edge gateway, which is interconnected with the tunnel monitoring device, tunnel electromechanical equipment and tunnel sensor equipment through the network. The L2 edge computing device collects intelligence data sets through the edge gateway. The intelligence data sets include monitoring data of all sections in the tunnel, information board data of all tunnel exits and sensor data in the tunnel. The edge gateway is provided with IoT Edge, which is interconnected with the tunnel monitoring device and collects monitoring data of all sections in the tunnel. IoT Edge is connected to the tunnel electromechanical equipment through the network and collects information board data of all tunnel exits. The edge gateway is connected to the electromechanical adapter through the network, and the electromechanical adapter is connected to the tunnel sensor equipment through the network and collects sensor data inside the tunnel. The expression of the intelligence data set is: , Indicates the monitoring data of all sections collected by tunnel monitoring equipment. Indicates the information board data of all exits collected by tunnel electromechanical equipment, It represents the traffic flow sensor data collected by the tunnel sensor equipment, comprehensively collects multi-terminal data, and adapts electromechanical equipment of different types and brands to enable effective data exchange and communication with the intelligent control module;

[0043] The L2 edge computing device generates a security data set based on the security data set. , and its calculation formula is as follows:

[0044] ;

[0045] In the formula, Denotes a safety data group, Indicates the wind pressure data in the tunnel. represents the ventilation efficiency in the tunnel, It represents the operating power of the tunnel fan equipment divided by the product of wind pressure and ventilation efficiency, and the tunnel ventilation volume is obtained. represents the surface area inside the tunnel, Indicates the total number of tunnel lighting equipment, It means the illumination of the tunnel lighting equipment multiplied by the total number to get the total lighting brightness of the tunnel lighting equipment. represents the surface area inside the tunnel, represents the average lighting brightness inside the tunnel, represents the total volume of the tunnel interior space, The carbon monoxide concentration in the tunnel is obtained by dividing the carbon monoxide gas volume of the tunnel COVI detector by the total volume of the tunnel's internal space. represents the fixed parameter defining the air quality in the SDS calculation formula, The ratio of the actual carbon monoxide concentration in the tunnel to the fixed parameter is the air quality index. The safety data set includes tunnel ventilation volume, average lighting brightness and air quality index. , while ensuring safe operation in the tunnel, a more economical and practical management solution can be adopted to reduce system construction and maintenance costs. It is also applicable to tunnel operation needs of different scales, and the network construction cost is low;

[0046] L2 edge computing devices calculate and generate intelligence data sets based on intelligence data sets , and its calculation formula is as follows:

[0047] ;

[0048] In the formula, represents the intelligence data group, Represents the comprehensive safety data group, key events, all road monitoring data, all exit information board data and traffic flow sensor data, and obtains the intelligence data group. , comprehensive monitoring perception and fast response speed, timely transmission of key information, and more stable and reliable communication quality;

[0049] The intelligent perception module is equipped with a radar-visual integrated machine and a video management platform. The radar-visual integrated machine collects monitoring data sets in real time and transmits them to the video management platform through the network. The monitoring data sets include the driving data of all vehicles in the tunnel. The expression of the monitoring data sets is , to The driving data of each vehicle in the tunnel is monitored in turn to achieve comprehensive monitoring of traffic targets in the tunnel. At the same time, it is equipped with intelligent abnormal situation response and processing functions to ensure timely processing of various abnormal situations. In the event of an emergency, such as a fire or traffic accident, the real-time monitoring data can be used to quickly understand the situation at the scene of the accident, guide the rescue forces to carry out effective emergency disposal, and improve the tunnel's emergency response capabilities;

[0050] The video management platform detects events based on the monitoring data set and screens and generates key events , and transmitted to the smart interconnection module through the network. The calculation process is as follows:

[0051] According to the monitoring data set, the time points of all vehicles entering and exiting the tunnel are counted and recorded as ,in , Indicates the time when the vehicle enters the tunnel. Indicates the time when the vehicle exits the tunnel. to Corresponding to the time points when each vehicle enters and exits the tunnel;

[0052] ;

[0053] ;

[0054] In the formula, Indicates key events. Indicates the normal length of time it takes for a vehicle to enter and exit a tunnel. represents the tunnel length, Indicates the maximum speed limit for vehicles in the tunnel. It represents the length of the tunnel divided by the maximum driving speed, which gives the normal time it takes for a vehicle to enter and exit the tunnel. represents the time taken by the actual vehicles in the monitoring dataset to enter and exit the tunnel, Indicates the ratio of the actual time to the normal time. If the ratio is greater than 1, the vehicle is marked as a key vehicle. Indicates the time points at which all vehicles enter and exit the tunnel , select the key vehicles whose actual time exceeds the normal time, which are the key events. , high-precision perception realizes comprehensive identification without blind spots, sensitively perceives abnormal events, and continuously tracks key vehicles;

[0055] The smart interconnection module allows users to visually edit and use configuration tools to build mobile applications and web pages through the LoC display engine. The smart interconnection module is equipped with an interconnection adaptation layer and an IoT platform. The interconnection adaptation layer connects the eSight system, lighting system, fire alarm system, power monitoring system, fire pool system and emergency telephone broadcasting system, IoT platform and smart perception module through the network. The interconnection adaptation layer processes all access data in the Kafka message queue through the API and transmits it to the IoT platform through the network. The IoT platform converts the processed access data into a physical model through the IoT technology and transmits it to the L2 edge computing device through the network to ensure autonomous control, achieve communication confidentiality and equipment security authentication, prevent illegal access of external devices, ensure information security, optimize the communication structure, ensure smooth communication, and provide intelligent network management and maintenance functions to improve the reliability and stability of the system. The L2 edge computing device is equipped with a segmented grouping management framework and a control screen. The segmented grouping management framework groups all access data in sequence, manages L0 controllers and various tunnel devices in segments, and quickly realizes the linkage control of various tunnel devices through hierarchical control. When data exists in the L2 edge computing device, it is output through the control screen first;

[0056] The inspection and maintenance APP is interconnected with the L0 controller through the network. The inspection and maintenance APP, L0 controller, L2 edge computing device, IoT platform and interconnection adaptation layer form a network closed loop, so that the information reported by the L0 controller is transparently transmitted to the IoT platform through iot-edge. The control message from the IoT platform is sent to the L0 controller through iot-edge. The inspection and maintenance APP simultaneously obtains the security data set, intelligence data set, monitoring data set and security data set related to the operation and maintenance inside the tunnel. , Intelligence Data Group and key events Through intelligent perception and one-button linkage control, the tunnel operation management level and emergency response capabilities can be improved, and the efficiency of handling emergency events can be accelerated.

[0057] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Tunnel event management and control platform, characterized by: It includes a smart control module, a smart sensing module, a smart interconnection module and an inspection and maintenance APP, wherein the inspection and maintenance APP is interconnected with the smart control module and the smart interconnection module through a network; The intelligent control module is provided with a dual-active information synchronization and coordination framework, which includes an L0 controller, an L2 edge computing device, a tunnel safety device, a tunnel monitoring device, a tunnel electromechanical device and a tunnel sensing device. The L0 controller and the L2 edge computing device perform data synchronization and coordination through a soft bus. The L0 controller is interconnected with the tunnel safety device and the inspection and maintenance APP through a network. The L0 controller collects a safety data set through a network connection with the tunnel safety device. The safety data set includes the operating power of the fan device, the illumination of the lighting device and the volume of carbon monoxide gas. The L2 edge computing device is provided with an edge gateway. The edge gateway is interconnected with the tunnel monitoring device, the tunnel electromechanical device and the tunnel sensing device through a network. The L2 edge computing device collects an intelligence data set through the edge gateway. The intelligence data set includes the monitoring data of all sections in the tunnel, the intelligence board data of all exits of the tunnel and the sensing data in the tunnel. The L2 edge computing device calculates and generates a safety data set based on the safety data set. The L2 edge computing device generates an intelligence data set based on the intelligence data set. ; The intelligent perception module is equipped with a radar-visual integrated machine and a video management platform. The radar-visual integrated machine collects monitoring data sets in real time and transmits them to the video management platform through the network. The monitoring data sets include the driving data of all vehicles in the tunnel. The video management platform performs event detection based on the monitoring data sets and screens and generates key events. and transmitted to the smart interconnection module through the network; According to the monitoring data set, the time points of all vehicles entering and exiting the tunnel are counted and recorded as ,in , Indicates the time when the vehicle enters the tunnel. Indicates the time when the vehicle exits the tunnel. to Corresponding to the time point when each vehicle enters and exits the tunnel; ； ； In the formula, Indicates key events. Indicates the normal length of time it takes for a vehicle to enter and exit a tunnel. represents the tunnel length, Indicates the maximum speed limit for vehicles in the tunnel. It represents the length of the tunnel divided by the maximum driving speed, which gives the normal time it takes for a vehicle to enter and exit the tunnel. represents the time taken by the actual vehicles in the monitoring dataset to enter and exit the tunnel, Indicates the ratio of the actual time to the normal time. If the ratio is greater than 1, the vehicle is marked as a key vehicle. Indicates the time points at which all vehicles enter and exit the tunnel , filter out the key vehicles whose actual time exceeds the normal time, which are the key events; The smart interconnection module allows users to visually edit and use configuration tools to build mobile applications and web pages through the LoC display engine. The smart interconnection module is provided with an interconnection adaptation layer and an Internet of Things platform. The interconnection adaptation layer connects the eSight system, lighting system, fire alarm system, power monitoring system, fire pool system and emergency telephone broadcasting system, the Internet of Things platform and the smart perception module through the network. The interconnection adaptation layer processes all access data in the Kafka message queue through the API and transmits it to the Internet of Things platform through the network. The Internet of Things platform converts the processed access data into a physical model through the Internet of Things technology and transmits it to the L2 edge computing device through the network.

2. The tunnel event management and control platform according to claim 1, characterized in that: The L0 controller is provided with an electromechanical APP, which includes an IoT SDK and an electromechanical SDK. The electromechanical SDK collects a safety data set through a network connection to tunnel safety equipment. The tunnel safety equipment includes a fan device, a lighting device, and a COVI detector. The expression of the safety data set is: , Indicates the operating power of the fan equipment. Indicates the illumination of the lighting equipment. Indicates the volume of carbon monoxide gas in the tunnel detected by the COVI detector.

3. The tunnel event management and control platform according to claim 2 is characterized in that: The edge gateway is provided with an IoT Edge, which is interconnected with the tunnel monitoring equipment and collects monitoring data of all sections in the tunnel. The IoT Edge is connected to the tunnel electromechanical equipment through the network and collects information board data at all exits of the tunnel. The edge gateway is connected to the electromechanical adapter through the network, and the electromechanical adapter is connected to the tunnel sensor equipment through the network and collects sensor data inside the tunnel.

4. The tunnel event management and control platform according to claim 3 is characterized in that: The expression of the intelligence data set is , Indicates the monitoring data of all road sections collected by tunnel monitoring equipment. Indicates the information board data of all exits collected by tunnel electromechanical equipment, Represents the vehicle flow sensor data collected by the tunnel sensor equipment.

5. The tunnel event management and control platform according to claim 4, characterized in that: The expression of the monitoring data set is: , to This corresponds to the driving data of each vehicle in the tunnel.

6. The tunnel event management and control platform according to claim 5, characterized in that: The Safety Data Set The calculation formula is as follows: ； In the formula, Denotes a safety data group, Indicates the wind pressure data in the tunnel. represents the ventilation efficiency in the tunnel, It represents the operating power of the tunnel fan equipment divided by the product of wind pressure and ventilation efficiency, and the tunnel ventilation volume is obtained. represents the surface area inside the tunnel, Indicates the total number of tunnel lighting equipment, It means the illumination of the tunnel lighting equipment multiplied by the total number to get the total lighting brightness of the tunnel lighting equipment. represents the average lighting brightness inside the tunnel, represents the total volume of the tunnel interior space, The carbon monoxide concentration in the tunnel is obtained by dividing the carbon monoxide gas volume of the tunnel COVI detector by the total volume of the tunnel's internal space. represents the fixed parameter defining the air quality in the SDS calculation formula, The ratio of the actual carbon monoxide concentration in the tunnel to the fixed parameters is the air quality index. The safety data set includes tunnel ventilation volume, average lighting brightness and air quality index.

7. The tunnel event management and control platform according to claim 6, characterized in that: The intelligence data set The calculation formula is as follows: ； In the formula, represents the intelligence data group, It represents the integrated safety data group, key events, and traffic flow sensor data to obtain the intelligence data group.

8. The tunnel event management and control platform according to claim 7, characterized in that: The L2 edge computing device is provided with a segmented grouping management framework and a control screen. The segmented grouping management framework groups all access data in sequence. When there is data in the L2 edge computing device, it is output through the control screen first.

9. The tunnel event management and control platform according to claim 8, characterized in that: The inspection and maintenance APP is interconnected with the L0 controller through the network. The inspection and maintenance APP, L0 controller, L2 edge computing device, Internet of Things platform and interconnection adaptation layer form a network closed loop. The inspection and maintenance APP simultaneously obtains the security data set, intelligence data set, monitoring data set and security data set related to the operation and maintenance inside the tunnel. , Intelligence Data Group and key events .

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