Safety early warning and monitoring system for extra-long highway tunnel

Abstract

The invention relates to the technical field of highway fire safety monitoring technologies, and particularly discloses an extra-long highway tunnel safety early warning monitoring system which comprises a tunnel safety early warning system. The tunnel safety early warning system comprises an environment information acquisition module, an image recognition module, an analysis and judgment module and an early warning module. The analysis and judgment module is used for analyzing and judging whether a current vehicle has a fire risk or not according to environment parameters and abnormal driving vehicle images and sending fire early warning information to the early warning module for early warning according to a judgment result. Meanwhile, the fire early warning information is sent to terminal equipment of a tunnel guarding person; and the early warning module comprises an information board and a loudspeaker, and the information board and the loudspeaker are respectively used for displaying and broadcasting fire early warning information. The objective of the invention is to solve the problems that an existing tunnel fire-fighting system lacks unified monitoring and early warning of fire-fighting facilities inside and outside a tunnel and cannot monitor and early warn vehicle fire risks.

Description

Technical Field

[0001] The invention relates to the technical field of highway fire safety monitoring systems, and in particular to a safety early warning monitoring system for extra-long highway tunnels. Background Art

[0002] Expressways are a modern road transport channel. Expressways have the characteristics of large traffic capacity and high driving efficiency, and play an increasingly important role in economic development. In recent years, my country's expressways have entered a large-scale construction. In expressway projects, tunnels are a very important component. With the development of construction technology, the length of tunnels has been repeatedly exceeded, posing a huge challenge to the fire safety inside the tunnels. There are many fire hazards in expressway tunnels. One is insufficient ventilation and smoke exhaust. There are fewer ventilation and smoke exhaust equipment in some extra-long tunnels. In the case of poor ventilation, the temperature in the tunnel rises quickly, and harmful gases are retained for a long time, which endangers human health. Once they encounter high temperatures or open flames, fires or even explosions may occur, causing huge economic losses.

[0003] The existing tunnel system safety warning mainly monitors the fire hazards existing in the abnormal lines in the tunnel itself to avoid causing larger-scale losses, but lacks early warning monitoring of abnormal fires in vehicles traveling in the tunnel. In addition, due to the limited senses of the driver and passengers when the vehicle is driving, it is difficult for the driver to respond effectively to the fire when a fire occurs in a part of the vehicle that is out of sight, causing the burning vehicle to continue to move forward, and the fire point of the tunnel fire may continue to move with the vehicle. If the burning vehicle is not handled in time, the fire will further expand, causing greater economic losses and even threatening personal safety. Summary of the invention

[0004] In view of the deficiencies in the prior art, the technical problem solved by the present invention is to provide a safety early warning monitoring system for extra-long highway tunnels, so as to solve the problems that the existing tunnel fire protection system lacks unified monitoring and early warning of fire protection facilities inside and outside the tunnel, and cannot realize monitoring and early warning of vehicle fire risks.

[0005] In order to solve the above problems, the technical solution adopted by the present invention is: a long highway tunnel safety early warning monitoring system, which includes a tunnel safety early warning system; the tunnel safety early warning system includes an environmental information acquisition module, an image recognition module, an analysis and judgment module and an early warning module; The environmental information acquisition module is used to obtain the environmental parameters in the tunnel and input the environmental parameters to the analysis and judgment module. The environmental parameters include smoke information, temperature data, combustible gas data and harmful gas data; the image recognition module is used to obtain vehicle driving images, identify and mark abnormal driving vehicle images from the vehicle driving images, and send the abnormal driving vehicle images to the analysis and judgment module; the analysis and judgment module is used to comprehensively analyze and judge whether the current vehicle has a fire risk based on the environmental parameters and the abnormal driving vehicle images, generate fire warning information based on the judgment results and send it to the warning module; at the same time, the fire warning information is sent to the terminal device of the tunnel guard; the warning module includes an information board and a tweeter, which are used to display and broadcast the fire warning information respectively.

[0006] The analysis and judgment module includes a vehicle analysis unit, an environment analysis unit and an early warning judgment unit. The vehicle analysis unit is used to obtain an abnormal driving index of the vehicle according to the abnormal driving vehicle image, and judge whether the abnormal driving index exceeds a preset value. When the judgment result is "no", no processing is performed. When the judgment result is "yes", the position of the vehicle in the tunnel is obtained according to the position of the image acquisition device where the vehicle image is located. The environment analysis unit is used to obtain abnormal environmental parameters according to environmental information. The early warning judgment unit is used to obtain a fire prediction result according to the abnormal driving index and the abnormal environmental parameters. When the fire prediction result is "no", no processing is performed. When the fire prediction result is "yes", a judgment result of a fire in the tunnel is obtained according to the current position of the vehicle. When the judgment result is "yes", a first fire warning information is sent to the early warning module. When the judgment result is "no", a second fire warning information is sent to the early warning module to guide the vehicle to exit the tunnel. The first fire warning information includes the abnormal vehicle license plate, warning reminder words, and location information of the nearest fire-fighting facility, and the second fire warning information includes the abnormal vehicle license plate and warning avoidance words; the warning judgment unit is also used to send notification information to the terminal device of the tunnel guard; The early warning module also includes an early warning control unit electrically connected to the information board and the tweeter respectively, and the information board and the tweeter are arranged in plurality at intervals in the tunnel; the early warning control unit controls the information board along the vehicle's forward direction to display the fire information and controls the tweeter along the vehicle's forward direction to broadcast the fire warning information according to the fire warning information.

[0007] The beneficial effects of this program are: Through the tunnel safety warning system, the environmental parameters in the tunnel and the images of abnormally running vehicles are collected respectively; since the risk of fire in a vehicle is usually accompanied by problems such as smoke, sparks or flammable gas leakage, the accuracy of judging the risk of fire in the vehicle can be improved by collecting environmental parameters and combining the images of abnormally running vehicles; the risk of fire in abnormal vehicles is predicted in advance, so that the fire warning information can be displayed and broadcasted through the information board and the tweeter, and the vehicles with fire risk are effectively guided and extinguished; thereby avoiding the spread of fire by the fire vehicle without knowing it, expanding the scope of the fire and causing greater losses. In the prior art, for the detection of fire safety hazards in the tunnel, the AI ​​camera is usually used to identify the flame as the target object in the monitoring image in the tunnel, and the environmental sensor is used to monitor the smoke, temperature and other information in the tunnel. In this way, although the fire can be discovered in time, it can only be discovered after the fire incident occurs, and the process from discovery to processing requires a certain response time. Due to the complex environment of the tunnel, the vehicle can only turn around at a fixed position, otherwise the vehicle can only handle it by itself. The longer the response time, the greater the risk of loss of life and property. In this solution, abnormal vehicles with fire risks are identified by recognizing and analyzing images of abnormally moving vehicles, and then reminded and warned by the early warning module. When it is determined that a vehicle will catch fire in the tunnel, the vehicle is stopped at the nearest fire-fighting facility in advance for inspection. If a fire occurs, it can be extinguished in time. At the same time, relevant rescue personnel and management personnel are notified in advance, and emergency measures can be taken for the fire, greatly shortening the rescue response time.

[0008] When it is predicted that a vehicle will catch fire in the tunnel, if the vehicle continues to move towards the tunnel exit, the fire will spread. Therefore, the first fire warning information is used to notify the vehicle to stop at the nearest fire-fighting facility and carry out fire-fighting, and coordinate with the nearest rescue center to assist in fire-fighting to avoid expanding the scope of the fire and curb the spread of the fire in time; when it is predicted that an abnormal vehicle has a risk of fire, but the abnormal vehicle is close to the tunnel exit and it is judged that it will not catch fire in the tunnel, the second fire warning information is used to notify the abnormal vehicle to drive to the emergency lane at the tunnel exit for fire-fighting, and the information board and loud speaker are used to remind the vehicles in front to pay attention to avoid, so that the abnormal vehicle can quickly exit the tunnel, avoiding the vehicle being blocked by the vehicle in front while driving in the tunnel, and failing to quickly exit the tunnel, causing a fire in the tunnel, increasing the difficulty of fire fighting and evacuation.

[0009] Furthermore, the vehicle analysis unit identifies vehicle abnormal parameters by pre-training a vehicle driving image recognition model, and obtains an abnormal driving index based on the vehicle abnormal parameters. The vehicle abnormal parameters include the number of vehicle shakes, the vehicle shake frequency, the number of vehicle offsets, the vehicle offset degree, and whether there are sparks on the vehicle body.

[0010] When there is a risk of fire for a vehicle, it is usually caused by factors such as overheating of the vehicle engine itself or aging of the vehicle lines. Therefore, there are prone to abnormal vehicle driving phenomena, such as multiple vehicle shakes, high shaking frequency, spark flashes, or vehicle driving deviations in time and space. Therefore, the abnormal driving behavior of the vehicle can be judged by parameters such as the number of vehicle shakes, the frequency of vehicle shakes, the number of vehicle deviations, and the degree of vehicle deviation. When sparks are detected, it can be directly determined as an abnormally driving vehicle, and the fire probability and fire location of the abnormal vehicle can be predicted, and different fire warning information can be issued according to the judgment results.

[0011] Furthermore, the environmental information acquisition module includes a smoke detector, a combustible gas detector and a temperature sensor, which constitute an environmental acquisition module. The environmental acquisition module is arranged in multiple groups at intervals in the tunnel. The image recognition module collects multiple types of vehicle driving images through an RGB camera, a thermal imaging camera and a depth camera group. The camera group is arranged in multiple groups at intervals in the tunnel.

[0012] By setting up multiple environment collection modules and camera groups, information can be collected in different areas of the tunnel, so as to collect vehicle information and corresponding environment information at various locations in the tunnel. At the same time, the camera groups arranged at multiple points can also collect real-time images of vehicles traveling in the tunnel, and use thermal imaging cameras to identify whether the vehicle is overheated and the overheated area of ​​the vehicle, so as to further assist in determining whether the vehicle in the image is an abnormal vehicle. When the vehicle is overheated, the vehicle in the image is marked as an abnormal vehicle, and the image is marked as an image of an abnormally traveling vehicle. Secondly, the distance between the abnormal vehicle and the camera in the image of the abnormally traveling vehicle can be obtained with the help of a depth camera, and the accurate location information of the abnormal vehicle can be obtained in combination with the camera group's own location information. The vehicle location information obtained by combining the general image lacking depth information with the camera location information is more accurate.

[0013] Furthermore, the early warning module also includes warning lights, which are respectively arranged at fire-fighting facilities, and the early warning control unit controls the warning lights at the fire-fighting facilities closest to the abnormal vehicle to flash according to the first early warning information. By setting the warning lights and making them flash, it is convenient for the driver of the abnormal vehicle to quickly find the location of the fire-fighting facilities.

[0014] Furthermore, it also includes a fire-fighting facility early warning system; the fire-fighting facility early warning system includes a central control unit, and a water tank water level monitoring unit, a pipe pressure monitoring unit, and a water pump monitoring unit which are respectively connected to the central control unit network, the water level monitoring unit is used to monitor the water level change of the water tank and obtain the water tank water level data and send it to the central control unit, the pipe pressure monitoring unit is used to monitor the pipe pressure data of the fire-fighting water pipes inside and outside the tunnel and send it to the central control unit, the water pump monitoring unit is used to collect the water pump working data and determine whether the water pump has a fault, and send the fault data to the central control unit; the central control unit is used to control the start and stop of the water pump according to the water tank water level data, and send equipment management early warning information to the terminal device of the tunnel guard according to the pipe pressure data and fault data.

[0015] The fire-fighting facility early warning system can monitor abnormal conditions of fire-fighting facilities in the tunnel and the water level of the pool outside the tunnel, and issue early warning information for abnormal conditions in a timely manner, so that relevant personnel can check and repair them according to the early warning information, thereby ensuring that the fire-fighting equipment in the tunnel can be used normally, and then it can play a role in extinguishing fire when a fire occurs.

[0016] Furthermore, the central control unit is also used to determine whether there is a water leak based on the water level data within a preset time period. If the water level drops by more than a preset value within the preset time period, it is determined that the pool is leaking. When the water pump is not working, the water level in the pool will not rise or fall in a short period of time. If the water level changes within the set time, such as the water level drops by more than the set value, it is very likely that the pool has a water leak, so targeted inspections can be carried out based on the early warning information and existing leaks can be repaired. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a schematic diagram of the fire protection facility early warning system module of the present invention; Figure 2 It is a schematic diagram of the tunnel safety early warning system module of the present invention. DETAILED DESCRIPTION

[0018] The following is further described in detail through specific implementation methods: Example 1 This is as attached Figure 1 As shown: A safety early warning monitoring system for an extra-long highway tunnel, which includes a fire-fighting facility early warning system and a tunnel safety early warning system; The tunnel safety warning system includes an environmental information acquisition module, an image recognition module, an analysis and judgment module, and an early warning module; the environmental information acquisition module is used to obtain the environmental parameters in the tunnel and transmit the environmental information to the analysis and judgment module. The environmental parameters include smoke information, temperature data, combustible gas data, and harmful gas data; the image recognition module is used to obtain vehicle driving images, and the image recognition module is also used to identify and mark abnormal driving vehicle images from vehicle driving images, and send abnormal driving vehicle images to the analysis and judgment module. The analysis and judgment module is used to analyze and judge whether the current vehicle has a fire risk based on environmental parameters and abnormal driving vehicle images, and send fire warning information to the early warning module based on the judgment results; at the same time, the fire warning information is sent to the terminal device of the tunnel guard; the early warning judgment unit is also used to send notification information to the terminal device of the tunnel guard and the emergency rescue center around the tunnel. The early warning module includes an information board and a tweeter, which are used to display and broadcast fire warning information respectively.

[0019] Through the tunnel safety warning system, the environmental parameters in the tunnel and the images of abnormally moving vehicles are collected respectively. Since the risk of fire in a vehicle is usually accompanied by problems such as smoke, sparks or flammable gas leakage, the accuracy of judging the risk of fire in the vehicle can be improved by collecting environmental parameters and combining them with the images of abnormally moving vehicles. The fire risk of abnormal vehicles can be predicted in advance, so that the fire warning information can be displayed and broadcasted through the information board and tweeter respectively, and the vehicles with fire risk can be effectively guided and extinguished. This can prevent the fire from spreading without the knowledge of the vehicle on fire, expanding the scope of the fire and causing greater losses.

[0020] The analysis and judgment module includes a vehicle analysis unit, an environment analysis unit and an early warning judgment unit. The vehicle analysis unit is used to obtain the abnormal driving index of the vehicle according to the abnormal driving vehicle image, and judge whether the abnormal driving index exceeds the preset value. When the judgment result is otherwise, no processing is performed. When the judgment result is yes, the position of the vehicle in the tunnel is obtained according to the position of the image acquisition device where the vehicle image is located; the environment analysis unit is used to obtain abnormal environmental parameters according to environmental information. The early warning judgment unit is used to obtain a fire prediction result according to the abnormal driving index and the abnormal environmental parameters. When the fire prediction result is yes, no processing is performed. When the fire prediction result is yes, the judgment result of the fire in the tunnel is obtained according to the current position of the vehicle. When the judgment result is yes, the first fire warning information is sent to the early warning module. When the judgment result is yes, the vehicle is automatically detected. If not, the second fire warning information is sent to the warning module to guide the vehicle to the tunnel exit; the first fire warning information includes the abnormal vehicle license plate, warning reminder words, and the location information of the nearest fire-fighting facility, such as "The vehicle with license plate number XXX is at risk of fire / fire, please drive to the fire-fighting facility at XXM ahead for inspection / fire extinguishing", and notify the tunnel guard, who can view the fire situation in the tunnel through monitoring and deal with it; the second fire warning information includes the abnormal vehicle license plate and warning avoidance words; for example, "The vehicle with license plate number XXX is at risk of fire, please drive to the emergency lane at the tunnel exit as soon as possible to check / extinguish the fire, other vehicles please give way"; and notify relevant personnel in advance to wait at the tunnel exit to deal with the vehicle fire in a timely and rapid manner.

[0021] When it is predicted that a vehicle will catch fire in the tunnel, if the vehicle continues to move towards the tunnel exit, the fire will spread. Therefore, the first fire warning information is used to notify the vehicle to stop at the nearest fire-fighting facility and carry out fire-fighting, and coordinate with the nearest rescue center to assist in fire-fighting to avoid expanding the scope of the fire and curb the spread of the fire in time; when it is predicted that an abnormal vehicle has a risk of fire, but the abnormal vehicle is close to the tunnel exit and it is judged that it will not catch fire in the tunnel, the second fire warning information is used to notify the abnormal vehicle to drive to the emergency lane at the tunnel exit for fire-fighting, and the information board and loud speaker are used to remind the vehicles in front to pay attention to avoid, so that the abnormal vehicle can quickly exit the tunnel, avoiding the vehicle being blocked by the vehicle in front while driving in the tunnel, and failing to quickly exit the tunnel, causing a fire in the tunnel, increasing the difficulty of fire fighting and evacuation.

[0022] The vehicle analysis unit identifies vehicle abnormal parameters by pre-training the vehicle driving image recognition model, and obtains the abnormal driving index based on the vehicle abnormal parameters. The vehicle abnormal parameters include the number of vehicle shakes, the frequency of vehicle shakes, the number of vehicle offsets, the degree of vehicle offset, and whether there are sparks on the vehicle body.

[0023] When there is a risk of fire in a vehicle, it is usually caused by factors such as overheating of the vehicle engine itself or aging of the vehicle lines. Therefore, there is a tendency for the vehicle to have abnormal driving phenomena, such as multiple jitters of the vehicle, high jitter frequency, spark flashes, or vehicle driving deviations in time and space. Therefore, the abnormal driving behavior of the vehicle can be judged by parameters such as the number of vehicle jitters, the frequency of vehicle jitters, the number of vehicle deviations, and the degree of vehicle deviation. When sparks are detected, it can be immediately determined as an abnormal vehicle, and the probability and location of fire of the abnormal vehicle can be predicted, and different fire warning information can be issued according to the judgment results. Secondly, when there is a risk of fire in a vehicle, it is usually accompanied by problems such as smoke or leakage of flammable gas. Therefore, the accuracy of judging the risk of fire in the vehicle can be improved by collecting environmental parameters and combining them with abnormal vehicle parameters.

[0024] The early warning module also includes an early warning control unit electrically connected to the information board and the tweeter, respectively. The information board and the tweeter are arranged at intervals in the tunnel. The early warning control unit controls the information board along the direction of the abnormal vehicle to display the fire information and the tweeter in the direction of the abnormal vehicle to broadcast the fire warning information according to the fire warning information and the position information corresponding to the abnormal vehicle. The system also includes a warning light, which is respectively arranged at the fire-fighting facilities. The early warning control unit controls the warning light at the fire-fighting facility closest to the abnormal vehicle to flash according to the first early warning information. By setting the warning light and making it flash, it is convenient for the driver of the abnormal vehicle to quickly find the location of the fire-fighting facility. By combining the information board with the tweeter, the driver of the abnormal vehicle is given a double visual and auditory prompt, so that the driver can find the abnormal situation as soon as possible and deal with it according to the instructions to avoid causing greater personal harm and economic losses.

[0025] The environmental information acquisition module includes a smoke detector, a combustible gas detector and a temperature sensor. The smoke detector, the combustible gas detector and the temperature sensor constitute the environmental acquisition module. There are multiple groups of environmental acquisition modules at intervals in the tunnel. The image recognition module collects multiple types of vehicle driving images through an RGB camera, a thermal imaging camera and a depth camera group. There are multiple groups of camera groups arranged at intervals in the tunnel.

[0026] By setting up multiple environment collection modules and camera groups, information can be collected in different areas of the tunnel, so as to collect vehicle information and corresponding environment information at various locations in the tunnel. At the same time, the camera groups arranged at multiple points can also collect real-time images of vehicles traveling in the tunnel, and use thermal imaging cameras to identify whether the vehicle is overheated and the overheated area of ​​the vehicle, so as to further assist in determining whether the vehicle in the image is an abnormal vehicle. When the vehicle is overheated, the vehicle in the image is marked as an abnormal vehicle, and the image is marked as an image of an abnormally traveling vehicle. Secondly, the distance between the abnormal vehicle and the camera in the image of the abnormally traveling vehicle can be obtained with the help of a depth camera, and the accurate location information of the abnormal vehicle can be obtained in combination with the camera group's own location information. The vehicle location information obtained by combining the general image lacking depth information with the camera location information is more accurate.

[0027] The fire-fighting facility early warning system includes a central control unit, and a pool water level monitoring unit, a pipe pressure monitoring unit, and a water pump monitoring unit that are respectively connected to the central control unit network. The water level monitoring unit is used to monitor the change of the water level of the pool and obtain the water level data of the pool and send it to the central control unit. The pipe pressure monitoring unit is used to monitor the pipe pressure data of the fire-fighting water pipes inside and outside the tunnel and send it to the central control unit. The water pump monitoring unit is used to collect the working data of the water pump and determine whether the water pump has a fault, and send the fault data to the central control unit; the central control unit is used to control the start and stop of the water pump according to the water level data of the pool, and send the equipment management early warning information to the terminal device of the tunnel guard according to the pipe pressure data and fault data. The fire-fighting facility early warning system can monitor the abnormal conditions of the fire-fighting facilities in the tunnel and the water level of the pool outside the tunnel, and send early warning information in time for abnormal conditions, so that relevant personnel can check and repair according to the early warning information, so as to ensure that the fire-fighting equipment in the tunnel can be used normally, and then play a role in extinguishing fire when a fire occurs.

[0028] The central control unit is also used to determine whether there is a water leak based on the water level data within a preset time period when the water pump is not working. If the water level drops by more than a preset value during the preset time period, it is determined that the pool is leaking. When the water pump is not working, the water level in the pool will not rise or fall in a short period of time. If the water level changes within the set time, such as the water level drops by more than the set value, it is very likely that the pool has a water leak, so targeted inspections can be carried out based on the early warning information and existing leaks can be repaired.

[0029] The above is only an embodiment of the present invention, and the common knowledge such as the known specific structure and characteristics in the scheme is not described in detail here. It should be pointed out that for those skilled in the art, several deformations and improvements can be made without departing from the structure of the present invention, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A safety early warning monitoring system for an extra-long highway tunnel, characterized in that: It includes a tunnel safety early warning system, which includes an environmental information acquisition module, an image recognition module, an analysis and judgment module, and an early warning module; The environmental information acquisition module is used to obtain the environmental parameters in the tunnel and transmit the environmental parameters to the analysis and judgment module. The environmental parameters include smoke information, temperature data, combustible gas data and harmful gas data; the image recognition module is used to obtain vehicle driving images. The image recognition module is also used to identify and mark abnormal driving vehicle images from vehicle driving images, and send the abnormal driving vehicle images to the analysis and judgment module; the analysis and judgment module is used to analyze and judge whether the current vehicle has a fire risk based on the environmental parameters and abnormal driving vehicle images, and send fire warning information to the warning module based on the judgment result; at the same time, the fire warning information is sent to the terminal device of the tunnel guard; the warning module includes an information board and a tweeter, which are used to display and broadcast fire warning information respectively; The analysis and judgment module includes a vehicle analysis unit, an environment analysis unit and an early warning judgment unit. The vehicle analysis unit is used to obtain an abnormal driving index of the vehicle according to the abnormal driving vehicle image, and judge whether the abnormal driving index exceeds a preset value. If the judgment result is no, no processing is performed. If the judgment result is yes, the position of the vehicle in the tunnel is obtained according to the position of the image acquisition device where the vehicle image is located. The environment analysis unit is used to obtain abnormal environment parameters according to the environment information, and the early warning judgment unit is used to obtain a fire prediction result according to the abnormal driving index and the abnormal environment parameters, and no processing is performed when the fire prediction result is otherwise; When the fire prediction result is yes, the judgment result of the fire in the tunnel is obtained according to the current position of the vehicle. When the judgment result is yes, the first fire warning information is sent to the warning module. When the judgment result is no, the second fire warning information is sent to the warning module, and the vehicle is guided to the tunnel exit; The first fire warning information includes the abnormal vehicle license plate, warning reminder words, and location information of the nearest fire-fighting facility, and the second fire warning information includes the abnormal vehicle license plate and warning avoidance words; the warning judgment unit is also used to send notification information to the terminal device of the tunnel guard; The warning module also includes a warning control unit electrically connected to the information board and the tweeter respectively, and the information board and the tweeter are provided in plurality at intervals in the tunnel; the warning control unit controls the information board along the vehicle's forward direction to display the fire information and controls the tweeter in the vehicle's forward direction to broadcast the fire warning information according to the fire warning information; The image recognition module collects multiple types of vehicle driving images through an RGB camera, a thermal imaging camera and a depth camera camera group, and multiple camera groups are arranged at intervals in the tunnel.

2. The extra-long highway tunnel safety early warning monitoring system according to claim 1 is characterized in that: The vehicle analysis unit identifies vehicle abnormal parameters by pre-training a vehicle driving image recognition model, and obtains an abnormal driving index based on the vehicle abnormal parameters. The vehicle abnormal parameters include the number of vehicle shakes, the vehicle shake frequency, the number of vehicle offsets, the vehicle offset degree, and whether there are sparks on the vehicle body.

3. The extra-long highway tunnel safety early warning monitoring system according to claim 1 is characterized in that: The environmental information collection module includes a smoke detector, a combustible gas detector and a temperature sensor. The smoke detector, the combustible gas detector and the temperature sensor constitute an environmental collection module. A plurality of environmental collection modules are arranged at intervals in the tunnel.

4. The extra-long highway tunnel safety early warning monitoring system according to claim 1 is characterized in that: The early warning module also includes warning lights, which are respectively arranged at fire-fighting facilities. The early warning control unit controls the warning lights at the fire-fighting facilities closest to the abnormal vehicle to flash according to the first early warning information.

5. The extra-long highway tunnel safety early warning monitoring system according to claim 1 is characterized in that: It also includes a fire-fighting facility early warning system; the fire-fighting facility early warning system includes a central control unit, and a water tank water level monitoring unit, a pipe pressure monitoring unit, and a water pump monitoring unit which are respectively connected to the central control unit network, the water level monitoring unit is used to monitor the water level change of the water tank and obtain the water tank water level data and send it to the central control unit, the pipe pressure monitoring unit is used to monitor the pipe pressure data of the fire-fighting water pipes inside and outside the tunnel and send it to the central control unit, the water pump monitoring unit is used to collect the water pump working data and determine whether there is a fault in the water pump, and send the fault data to the central control unit; the central control unit is used to control the start and stop of the water pump according to the water tank water level data, and send equipment management early warning information to the terminal device of the tunnel guard according to the pipe pressure data and fault data.

6. The extra-long highway tunnel safety early warning monitoring system according to claim 5 is characterized in that: The central control unit is also used to determine whether there is a water leak based on the water level data within a preset time period. If the water level drops beyond a preset value during the preset time period, it is determined that the pool is leaking.

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