Tunnel monitoring emergency system and method based on interpolation algorithm and binary search algorithm

Abstract

The invention provides a tunnel monitoring emergency system and method based on an interpolation algorithm and a binary search algorithm, and the system comprises an Internet of Things data collection module, a data processing module, an alarm module, a plan strategy module and an event handling module which are connected in sequence, and all the modules work cooperatively. According to the method, abnormal or missing data is intelligently complemented through an interpolation algorithm, alarm parameters are dynamically configured for event monitoring equipment in advance based on a tunnel environment, an operation time period and the equipment type of the event monitoring equipment, and a nearest camera and upstream and downstream cameras thereof are rapidly positioned through pile number sorting and a binary search algorithm. In combination with an intelligent analysis and plan linkage mechanism, automatic screen projection of infield pictures and outfield traffic situation awareness are realized, and evacuation decision making is assisted; and finally, by generating and grading emergencies, related units are linked to perform timely processing, so that all-directional perception and intelligent management of the tunnel operation state are realized, and the tunnel safety management level and the emergency response capability are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel monitoring emergency, and in particular to a tunnel monitoring emergency system and method based on an interpolation algorithm and a binary search algorithm. Background Art

[0002] During the operation of a tunnel, it is crucial to monitor various environmental parameters and equipment status in real time. Although the existing tunnel monitoring system can monitor some parameters, it still has some shortcomings.

[0003] On the one hand, due to the limitations of sensor layout, complete parameter data may not be acquired in real time in certain areas, resulting in inaccurate assessments of the tunnel's overall condition. On the other hand, existing monitoring systems often have fixed alarm parameters that are difficult to flexibly adjust to suit different tunnel environments, operating hours, and other factors. This can easily lead to false alarms or missed alarms, failing to meet actual monitoring needs. Furthermore, if a device alarm cannot quickly locate the specific location of nearby cameras, it will be impossible to promptly respond to on-site situations and take appropriate action. Summary of the Invention

[0004] To address existing tunnel monitoring systems, which suffer from inaccurate assessments of the tunnel's overall condition and prone to false alarms and missed alarms due to layout limitations and fixed alarm parameter settings, as well as the inability to quickly locate the specific location of cameras near faulty equipment, the present invention provides a tunnel monitoring emergency system based on an interpolation algorithm and a binary search algorithm. This system effectively improves the accuracy and flexibility of tunnel monitoring, significantly reduces the occurrence of false alarms and missed alarms, and can quickly lock onto the nearest camera, improving emergency response speed. This system achieves comprehensive perception and intelligent management of the tunnel's operating status, significantly enhancing tunnel safety management and emergency response capabilities. The present invention also relates to a tunnel monitoring emergency method based on an interpolation algorithm and a binary search algorithm.

[0005] The technical solutions of the present invention are as follows:

[0006] A tunnel monitoring emergency system based on an interpolation algorithm and a binary search algorithm is characterized by comprising an Internet of Things data acquisition module, a data processing module, an alarm module, a plan strategy module, and an event handling module connected in sequence.

[0007] The IoT data acquisition module is used to collect real-time environmental data in the tunnel and device status data of event monitoring equipment, and transmit the collected data to the data processing module;

[0008] The data processing module receives environmental data and device status data, and determines whether the environmental data and device status data have data missing or abnormalities based on a pre-set condition threshold. When it is determined that data missing or abnormalities exist, the data processing module calculates an estimated value of the current moment based on the environmental data and device status data of two moments adjacent to the current moment using an interpolation algorithm, completes and corrects the environmental data and device status data of the current moment based on the estimated value, and transmits the completed and corrected environmental data and device status data to the alarm module;

[0009] The alarm module dynamically configures alarm parameters for the event monitoring device in advance based on the tunnel environment, operation period and device type of the event monitoring device, and compares the completed and corrected environmental data and device status data with the dynamically configured alarm parameters to determine whether the alarm condition is met. If so, an alarm event is generated, and the event monitoring device that meets the alarm condition is used as the target device, and the location of the target device is used as the alarm point; the pile numbers of all cameras in the tunnel are then arranged in ascending order according to size to obtain a camera pile number sequence, and based on the camera pile number sequence, the pile number of the target device, the uplink and downlink directions and the road section, a binary search algorithm is used to locate the camera closest to the alarm point, and then the upstream camera and downstream camera adjacent to the nearest camera are determined according to the pile number size, uplink and downlink directions and the road section of the nearest camera;

[0010] The emergency plan strategy module includes an emergency plan management submodule, which includes an indoor emergency plan unit and an outdoor emergency plan unit. The indoor emergency plan unit automatically projects the camera image closest to the alarm point to the TV wall of the monitoring center for staff to confirm the on-site situation; the outdoor emergency plan unit monitors the incoming and outgoing directions of the alarm point through upstream and downstream cameras, generates traffic evacuation instructions based on the incoming and outgoing directions for staff to manually execute, and reports the traffic evacuation situation to the event handling module in real time;

[0011] The event handling module generates an emergency event based on the alarm event and the traffic evacuation situation and classifies the emergency event. According to the level of the emergency event, the road section to which it belongs and the event type, it associates the pre-established emergency plan and notifies the relevant units to carry out joint processing.

[0012] Preferably, the plan strategy module also includes a strategy execution submodule, and the strategy execution submodule includes a lighting strategy unit and a ventilation strategy unit. The lighting strategy unit and the ventilation strategy unit both include strategy modes, monitoring indicators, trigger conditions and strategy status; the strategy modes of the lighting strategy unit include time control mode, light control mode and a first manual mode. In the time control mode, the corresponding lighting equipment and enhanced lighting equipment are controlled according to the configured time period; in the light control mode, the lighting equipment is automatically controlled according to the monitoring indicators, trigger conditions and strategy status; in the first manual mode, the lighting equipment is manually and remotely controlled by the monitoring personnel; the strategy modes of the ventilation strategy unit include covi mode and a second manual mode. In the covi mode, the fan is automatically turned on or off according to the monitoring indicators, trigger conditions and strategy status; in the second manual mode, the tunnel fan equipment is manually and remotely controlled by the monitoring personnel.

[0013] Preferably, in the alarm module, based on the camera pile number sequence, the pile number of the target device, the uplink and downlink directions and the road section, and using a binary search algorithm to locate the camera closest to the alarm point specifically includes the following steps:

[0014] S1: Initialize the index of the first camera and the index of the last camera in the camera pile sequence; and use the index of the first camera as the left index and the index of the last camera as the right index;

[0015] S2: Calculate the index of the middle camera based on the initialized left index and right index, and use the index of the middle camera as the middle index. Extract the pile number of the middle camera from the camera pile number sequence based on the middle index, and then compare the pile number of the middle camera with the pile number of the target device. If the pile number of the middle camera is smaller than that of the target device, update the left index to the middle index; if the pile number of the middle camera is larger than that of the target device, update the right index to the middle index; if the pile number of the middle camera is equal to that of the target device, directly output the middle index;

[0016] S3: Repeat step S2 until the left index and the right index are adjacent, and obtain two adjacent cameras corresponding to the left index and the right index respectively;

[0017] S4: Calculate the absolute values ​​of the pile numbers of the two adjacent cameras and the interpolated pile numbers of the target device respectively, and compare the two absolute values. The camera with the smaller absolute value is regarded as the camera closest to the alarm point. If the two absolute values ​​are equal, one of the two adjacent cameras is regarded as the camera closest to the alarm point according to the pile number size, uplink and downlink directions, and road sections according to business rules.

[0018] Preferably, in the data processing module, judging whether there is data missing or abnormality in the environmental data and equipment status data according to a preset conditional threshold specifically includes: comparing each parameter in the environmental data and equipment status data with the preset conditional threshold respectively; if the value of a certain parameter is greater than the conditional threshold, judging that the parameter is missing or abnormal.

[0019] Preferably, in the Internet of Things data acquisition module, the environmental data includes temperature, humidity and harmful gas concentration; the event monitoring equipment includes cameras, harmful gas monitoring equipment, illumination brightness monitoring equipment, meteorological instruments, wind speed and direction equipment, high and low water level pools, information boards, fire alarm equipment and programmable logic controllers; the equipment status data includes current, voltage, power, liquid level and equipment temperature.

[0020] A tunnel monitoring emergency method based on an interpolation algorithm and a binary search algorithm, characterized by comprising the following steps:

[0021] IoT data collection steps: Real-time collection of tunnel environment data and device status data of event monitoring equipment;

[0022] Data processing step: judging whether the environmental data and device status data have data missing or abnormalities according to a pre-set condition threshold; if data missing or abnormalities are determined to exist, using the environmental data and device status data of two adjacent moments and an interpolation algorithm to calculate an estimated value of the current moment; and supplementing and correcting the environmental data and device status data of the current moment according to the estimated value;

[0023] Alarm steps: Based on the tunnel environment, operation period and device type of the event monitoring device, the alarm parameters are dynamically configured in advance for the event monitoring device, and the completed and corrected environmental data and device status data are compared with the dynamically configured alarm parameters to determine whether the alarm condition is met. If so, an alarm event is generated, and the event monitoring device that meets the alarm condition is used as the target device, and the location of the target device is used as the alarm point; then, the pile numbers of all cameras in the tunnel are arranged in ascending order according to size to obtain a camera pile number sequence. Based on the camera pile number sequence, the pile number of the target device, the uplink and downlink directions and the road section, a binary search algorithm is used to locate the camera closest to the alarm point. Then, according to the pile number size, uplink and downlink directions and the road section of the nearest camera, the upstream and downstream cameras adjacent to the nearest camera are determined;

[0024] Emergency plan strategy step: including emergency plan management, which includes internal and external emergency plans. The internal emergency plan automatically projects the camera image closest to the alarm point to the video wall of the monitoring center for staff to confirm the on-site situation. The external emergency plan monitors the incoming and outgoing directions of the alarm point through upstream and downstream cameras, generates traffic evacuation instructions based on the incoming and outgoing directions for staff to manually execute, and reports the traffic evacuation situation to the event handling step in real time;

[0025] Incident handling steps: Generate an emergency based on the alarm event and traffic evacuation situation and classify the emergency. According to the level of the emergency, the road section and the type of incident, link it to the pre-established emergency plan and notify relevant units for joint processing.

[0026] Preferably, the plan strategy step further includes strategy execution, executing lighting strategy and ventilation strategy respectively, wherein the lighting strategy and ventilation strategy each include strategy mode, monitoring index, trigger condition and strategy status;

[0027] The lighting strategy includes a time control mode, a light control mode, and a first manual mode. In the time control mode, the corresponding lighting equipment and enhanced lighting equipment are controlled according to the configured time period. In the light control mode, the lighting equipment is automatically controlled according to the monitoring indicators, trigger conditions, and the strategy status. In the first manual mode, the lighting equipment is manually and remotely controlled by the monitoring personnel.

[0028] The strategy modes of the ventilation strategy unit include covi mode and a second manual mode. In covi mode, the fan is automatically turned on or off according to monitoring indicators, trigger conditions and strategy status; in the second manual mode, the monitoring personnel manually remotely control the switch of the tunnel fan equipment.

[0029] Preferably, in the alarm step, based on the camera pile number sequence, the pile number of the target device, the uplink and downlink directions and the road section, and using a binary search algorithm to locate the camera closest to the alarm point specifically includes the following steps:

[0030] S1: Initialize the index of the first camera and the index of the last camera in the camera pile sequence; and use the index of the first camera as the left index and the index of the last camera as the right index;

[0031] S2: Calculate the index of the middle camera based on the initialized left index and right index, and use the index of the middle camera as the middle index. Extract the pile number of the middle camera from the camera pile number sequence based on the middle index, and then compare the pile number of the middle camera with the pile number of the target device. If the pile number of the middle camera is smaller than the pile number of the target device, update the left index to the middle index, and narrow the range of the camera pile number sequence from the middle index to the right index; if the pile number of the middle camera is greater than or equal to the pile number of the target device, update the right index to the middle index, and narrow the range of the camera pile number sequence from the left index to the middle index;

[0032] S3: Repeat step S2 until the left index and the right index are adjacent, and obtain two adjacent cameras corresponding to the left index and the right index respectively;

[0033] S4: Calculate the absolute values ​​of the pile numbers of the two adjacent cameras and the interpolated pile numbers of the target device respectively, and compare the two absolute values. The camera with the smaller absolute value is regarded as the camera closest to the alarm point. If the two absolute values ​​are equal, one of the two adjacent cameras is regarded as the camera closest to the alarm point according to the pile number size, uplink and downlink directions, and road sections according to business rules.

[0034] Preferably, in the data processing step, judging whether the environmental data and the device status data have data missing or abnormal according to a preset condition threshold specifically includes: comparing each parameter in the environmental data and the device status data with the preset condition threshold respectively; if the value of a certain parameter is greater than the condition threshold, judging that the parameter is missing or abnormal.

[0035] Preferably, in the IoT data collection step, the environmental data includes temperature, humidity and harmful gas concentration; the event monitoring equipment includes cameras, harmful gas monitoring equipment, illumination brightness monitoring equipment, meteorological instruments, wind speed and direction equipment, high and low water level pools, information boards, fire alarm equipment and programmable logic controllers; the equipment status data includes current, voltage, power, liquid level and equipment temperature.

[0036] The beneficial effects of the present invention are:

[0037] The present invention provides a tunnel monitoring emergency system based on an interpolation algorithm and a binary search algorithm. The system comprises an Internet of Things data acquisition module, a data processing module, an alarm module, a plan strategy module and an event handling module which are connected in sequence. The modules work in coordination with each other. The Internet of Things data acquisition module first collects environmental data in the tunnel and device status data of event monitoring equipment in real time. The data processing module determines whether there is data missing or abnormality in the environmental data and device status data. When it is determined that there is data missing or abnormality, an estimated value of the current moment is calculated based on the environmental data and device status data of two moments adjacent to the current moment and an interpolation algorithm is used. The environmental data and device status data of the current moment are supplemented and corrected according to the estimated value. Data that cannot be obtained in real time in certain areas are supplemented and corrected by the interpolation algorithm for missing or abnormal data. This system can more accurately reflect the actual situation in the tunnel and provide a reliable basis for subsequent decision-making. The alarm module dynamically configures alarm parameters for event monitoring devices in advance based on the tunnel environment, operating period and device type of event monitoring devices. By dynamically configuring the alarm parameters of various types of devices on a unified platform, it can be adjusted according to different actual conditions, greatly improving the adaptability and practicality of the system and reducing the occurrence of false alarms and missed alarms. The completed and corrected environmental data and device status data are then compared with the dynamically configured alarm parameters to determine whether the alarm conditions are met to generate an alarm event. The event monitoring device that meets the alarm conditions is used as the target device (also called the alarm device), and the location of the target device is used as the alarm point. The stake numbers of all cameras in the tunnel are then sorted in ascending order according to size. The camera pile number sequence is obtained by sorting the pile numbers, combining the pile number sequence with the target device's pile number, uplink and downlink directions, and road sections. A binary search algorithm is then used to locate the camera closest to the alarm point. The upstream and downstream cameras adjacent to the nearest camera are then determined based on the pile number, uplink and downlink directions, and road sections of the nearest camera. For tunnels, especially long tunnels, once an abnormality is detected, the nearest camera can be quickly identified by sorting the pile numbers and combining the binary search algorithm to locate cameras near the accident site, improving emergency response speed. At the same time, combined with road direction information, the directions of incoming and outgoing vehicles can be accurately determined, providing a basis for subsequent handling and effectively shortening the search time by 40% compared to searching one by one. The indoor plan unit in the plan strategy module automatically projects the nearest camera image onto the TV wall of the monitoring center, making it easier for monitoring personnel to analyze the on-site situation and improve the accuracy of event judgment and command efficiency. The outdoor plan unit monitors the incoming and outgoing directions of vehicles at the alarm point through upstream and downstream cameras, and generates traffic evacuation instructions based on the incoming and outgoing directions for staff to manually execute, and reports the traffic evacuation situation to the event handling module in real time to avoid secondary accidents.Finally, the event handling module generates an emergency event based on the alarm event and reported information (traffic evacuation situation), and then classifies the emergency event according to the Ministry of Transport documents. Based on the level of the emergency event, the road section to which it belongs, and the type of event, it links the pre-established emergency plan and notifies relevant units for joint processing, realizing all-round perception and intelligent management of the tunnel's operating status, significantly improving the tunnel's safety management level and emergency response capabilities.

[0038] This invention establishes a complete closed-loop system for tunnel environmental monitoring and incident handling, encompassing multiple modules covering data collection, intelligent processing, alarm assessment, emergency response, and other functions. Through the coordinated operation of these modules, comprehensive perception and intelligent management of tunnel operating conditions are achieved, significantly improving tunnel safety management and emergency response capabilities, enhancing the accuracy and flexibility of tunnel monitoring, and reducing the occurrence of false alarms and missed reports. Based on IoT data collection technology, real-time collection and transmission of tunnel environmental parameters (such as temperature and humidity, smoke concentration, wind speed, gas content, etc.) and the status of event monitoring equipment are achieved, ensuring data integrity and real-time performance. Interpolation algorithms (such as linear interpolation and cubic spline interpolation) are used to intelligently supplement abnormal or missing data, improving data accuracy and continuity. Alarm parameters are dynamically pre-configured for event monitoring equipment based on the tunnel environment, operating period, and device type of the event monitoring equipment. By adopting a dynamic alarm threshold configuration mechanism, combined with different device types, operating periods, and environmental conditions, the false alarm rate and missed alarm rate are significantly reduced. After the alarm is triggered, the nearest camera and its upstream and downstream devices are quickly located using pile number sorting and binary search algorithms, improving emergency response efficiency. Combined with video intelligent analysis and plan linkage mechanisms, automatic projection of internal field images and awareness of external traffic situation are achieved, assisting evacuation decision-making. Finally, through event classification and multi-department collaborative disposal mechanisms, emergency event levels are automatically generated according to Ministry of Transport standards and linked to relevant units, comprehensively improving the safety, intelligence level, and emergency response capabilities of tunnel operations.

[0039] Furthermore, the emergency plan strategy module also includes a strategy execution submodule, which includes a lighting strategy unit and a ventilation strategy unit. Both the lighting strategy unit and the ventilation strategy unit include strategy modes, monitoring indicators, trigger conditions, and strategy status. The lighting strategy unit's strategy modes include time control mode, light control mode, and a first manual mode. In time control mode, the corresponding lighting equipment and enhanced lighting equipment are turned on and off according to the configured time period. In light control mode, the lighting equipment is automatically turned on and off according to monitoring indicators, trigger conditions, and strategy status. In the first manual mode, the lighting equipment is manually and remotely controlled by the monitoring personnel. The ventilation strategy unit's strategy modes include COVI mode and a second manual mode. In COVI mode, the fan is automatically turned on and off according to monitoring indicators, trigger conditions, and strategy status. In the second manual mode, the tunnel fan equipment is manually and remotely controlled by the monitoring personnel. By supporting multi-mode intelligent control of the lighting and ventilation systems (time control, light control, COVI, and manual), flexible switching can be achieved according to different scenarios, effectively enhancing the system's emergency response capabilities and operational flexibility. While ensuring driving safety, it achieves energy conservation and emission reduction, intelligent scheduling, and reduces operation and maintenance costs.

[0040] Furthermore, judging whether the environmental data and the device status data have data missing or abnormalities according to the pre-set conditional thresholds specifically includes: comparing each parameter in the environmental data and the device status data with the pre-set conditional thresholds respectively; if the value of a certain parameter is greater than the conditional threshold, then judging that the parameter is missing or abnormal, which can timely discover data missing or abnormal situations, ensure that the data relied upon by subsequent analysis and decision-making are true and valid, and improve the stability of system operation.

[0041] The present invention also relates to a tunnel monitoring emergency method based on an interpolation algorithm and a binary search algorithm. This method corresponds to the above-mentioned tunnel monitoring emergency system based on an interpolation algorithm and a binary search algorithm, and can be understood as an implementation method of the above-mentioned tunnel monitoring emergency system based on an interpolation algorithm and a binary search algorithm. This method includes an Internet of Things data collection step, a data processing step, an alarm step, a plan strategy step, and an event handling step. The Internet of Things data collection technology is used to realize real-time collection and transmission of environmental parameters in the tunnel and the status of event monitoring equipment, thereby ensuring the integrity and real-time nature of the data; the interpolation algorithm is used to intelligently supplement abnormal or missing data, thereby improving the accuracy and continuity of the data. ; and by adopting a dynamic alarm threshold configuration mechanism, combined with different equipment types, operating hours and environmental conditions, the false alarm rate and missed alarm rate are significantly reduced; after the alarm is triggered, the pile number sorting and binary search algorithm are used to quickly locate the nearest camera and its upstream and downstream equipment, thereby improving the efficiency of emergency response; combined with video intelligent analysis and plan linkage mechanism, automatic projection of indoor images and perception of outdoor traffic situation are realized to assist evacuation decision-making; finally, through event classification and multi-department collaborative disposal mechanism, the emergency event level is automatically generated according to the standards of the Ministry of Transport and the relevant units are linked, realizing all-round perception and intelligent management of the tunnel operation status, significantly improving the tunnel safety management level and emergency response capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a structural diagram of the tunnel monitoring emergency system based on the interpolation algorithm and the binary search algorithm of the present invention.

[0043] Figure 2 It is a schematic diagram of various devices arranged at different positions in the tunnel of the present invention. DETAILED DESCRIPTION

[0044] The present invention will be described below with reference to the accompanying drawings.

[0045] The present invention relates to a tunnel monitoring emergency system based on an interpolation algorithm and a binary search algorithm. The system is capable of obtaining tunnel parameter information more accurately, dynamically adjusting alarm parameters, and quickly locating and judging on-site conditions, thereby improving the accuracy and flexibility of tunnel monitoring. The structural diagram of the system is shown in FIG. Figure 1 As shown, it includes an Internet of Things data acquisition module, a data processing module, an alarm module, a plan strategy module and an event handling module connected in sequence.

[0046] 1. The IoT data acquisition module collects real-time tunnel environmental data and status data from event monitoring equipment, transmitting this data to the data processing module. Environmental data includes temperature, humidity, and hazardous gas concentrations. Various event monitoring devices are installed at various locations within the tunnel, including cameras, hazardous gas monitoring equipment (COVI), illuminance monitoring equipment, meteorological instruments, wind speed and direction equipment, high and low water level tanks, information boards, fire alarms, and programmable logic controllers (PLCs). Equipment status data includes current, voltage, power, liquid level, and device temperature.

[0047] Specifically, the IoT data acquisition module first uses a variety of sensors and combines PLC equipment (used to control the start and stop and operation logic of tunnel equipment such as fans, lighting, and water pumps) to collect various environmental parameters in the tunnel (such as temperature, humidity, and harmful gas concentrations) and equipment status parameters of event monitoring equipment (such as current, voltage, power, liquid level, and equipment temperature, etc.) in real time, and stores the collected data in the database and caches it in Redis, and transmits the data to the data processing module at the same time. Among them, the real-time data is stored in Redis, and the read and write speed of Redis far exceeds that of the database, which can be used for rapid response and processing of large amounts of collected data. Various devices at different locations in the tunnel, such as Figure 2 shown.

[0048] 2. A data processing module receives environmental data and device status data, and determines whether there is data missing or abnormality in the environmental data and device status data based on a pre-set condition threshold. When it is determined that there is data missing or abnormality, an estimated value of the current moment is calculated based on the environmental data and device status data of two moments adjacent to the current moment, and an interpolation algorithm is used to complete and correct the environmental data and device status data at the current moment based on the estimated value, and the completed and corrected environmental data and device status data are transmitted to the alarm module.

[0049] Specifically, the data processing module receives the environmental data and device status data transmitted by the sensor module and pre-processes the data. First, it determines whether the environmental data and device status data have data missing or abnormalities based on the pre-set condition threshold. By comparing each parameter in the environmental data and device status data with the pre-set condition threshold, if the value of a certain parameter is greater than the condition threshold (that is, the data value of a certain parameter exceeds the reasonable range, such as the temperature sensor shows -200°C, or a certain device does not upload data at the expected time point t), it is determined that the parameter is missing or abnormal. When it is determined that there is data missing or abnormality, based on the environmental data and device status data of two adjacent moments, an interpolation algorithm is used to calculate the estimated value of the current moment to supplement and correct the data in real time. The specific steps are as follows:

[0050] 1) Denote the data collected by adjacent devices at times t1 and t2 as y1 and y2 respectively;

[0051] 2) For the current time t (t1 < t < t2), calculate the estimated value at time t through y = y1+(t2 - t1)(y2 - y1)×(t - t1);

[0052] 3) Complete the environmental data and device status data at the current time t according to the estimated value, and store the estimated value at the current time t in the database and redis;

[0053] Based on the estimated value, it can be judged whether the device parameters at the current time t reach the preset alarm parameter threshold.

[0054] III. Alarm module: Dynamically configure alarm parameters for event monitoring devices in advance based on the tunnel environment, operation period, and device type of the event monitoring devices, and compare the completed and corrected environmental data and device status data with the dynamically configured alarm parameters respectively to determine whether the alarm conditions are met. If so, generate an alarm event, regard the event monitoring device that meets the alarm conditions as the target device, and regard the location of the target device as the alarm point; then sort the mileage numbers of all cameras in the tunnel in ascending order to obtain a camera mileage number sequence, and based on the camera mileage number sequence, the mileage number of the target device, the up / down direction, and the road section, use the binary search algorithm to locate the camera closest to the alarm point, and then determine the upstream camera and downstream camera adjacent to the closest camera according to the mileage number size, up / down direction, and road section of the closest camera.

[0055] The alarm module is divided into three parts. The first is the dynamic configuration of alarm parameters, which allows users to dynamically configure the device's alarm parameters based on factors such as the tunnel environment and device type. Due to the wide variety of device types, dynamic configuration can be adapted to a wide range of devices, reducing workload. The second is the alarm determination function, which compares collected and processed data with the alarm parameters in real time to determine whether the alarm conditions have been met. The third is the use of a binary search algorithm to quickly locate the camera closest to the alarm point, as well as upstream and downstream cameras, projecting the screen onto a video wall to determine the on-site situation. The system then notifies relevant personnel through various means, such as audio and visual alarms and text message notifications. Specifically, first, the alarm parameters are dynamically configured for the event monitoring device based on the tunnel environment, operating period, and device type of the event monitoring device. Then, the completed and corrected environmental data and device status data are compared with the dynamically configured alarm parameters to determine whether the alarm condition has been met (i.e., the alarm is determined). If so, an alarm event is generated, and the event monitoring device that has met the alarm condition is used as the target device, and the location of the target device is used as the alarm point. Finally, since the amount of data from the road camera is large and the cameras are sorted by pile number, the distance between the device target pile number and the camera pile number is calculated one by one to find the nearest device. The time complexity is O(n), while the time complexity of the binary search algorithm is O(log n), which greatly shortens the time. Therefore, using the binary search algorithm for rapid positioning can effectively improve query efficiency. The specific steps are as follows:

[0056] S1: According to the stake number target of the alarm device (target device), the road travel direction (upward and downward) and the section identification, obtain the corresponding up and down camera array arr of the current section (stake number increasing), that is, arrange the stake numbers of all cameras in the tunnel of the current section in ascending order according to size (stake number increasing), and obtain the camera stake number sequence arr; where target is the stake number value of the alarm device; the camera stake number attribute is stakeNum.

[0057] S2: left and right represent the left and right boundaries of the binary search interval, respectively. Initialize the index of the first camera and the index of the last camera in the camera station sequence. That is, initially, left points to the first element in the camera array (index is 0), and right points to the last element in the camera array (index is arr.size()-1). The index of the first camera is used as the left index, and the index of the last camera is used as the right index.

[0058] S3: Calculate the middle position: Calculate the index of the middle camera based on the initialized left index and right index, and use the index of the middle camera as the middle index mid. That is, in each loop, as long as there is at least one element between left and right, the index of the middle element is calculated using the formula mid = left + (right - left) / 2, that is, the middle index mid. This can effectively avoid the integer overflow problem that may occur when (left + right) / 2 is large.

[0059] Compare the middle element with the target value: extract the stake number of the middle camera from the camera stake number sequence according to the middle index, and then compare the stake number of the middle camera with the stake number of the target device. If the stake number of the middle camera is smaller than the stake number of the target device, update the left index to the middle index; if the stake number of the middle camera is larger than the stake number of the target device, update the right index to the middle index; if the stake number of the middle camera is equal to the stake number of the target device, directly output the middle index; that is, if the middle element (the stake number of the middle camera) arr[mid].stakeNum is smaller than the target value (the stake number of the target device) target, it means that the target value may be to the right of mid, update left=mid, and narrow the search range to [mid,right]; if the middle element arr[mid].stakeNum is greater than or equal to the target value target, it means that the target value may be to the left of mid, update right=mid, and narrow the search range to [left,mid];

[0060] S4: Repeat step S3 until the left index and the right index are adjacent, and obtain two adjacent cameras corresponding to the left index and the right index respectively;

[0061] S5: Calculate the absolute values ​​of the stake numbers of the two adjacent cameras and the stake number interpolation of the target device respectively, and compare the two absolute values. The camera with the smaller absolute value is taken as the camera closest to the alarm point; if the two absolute values ​​are equal, then according to the stake number size and the road direction, according to the business rules, one of the two adjacent cameras is taken as the camera closest to the alarm point; that is, when the loop ends, left and right are adjacent. At this time, compare arr[left].stakeNum and arr[right].stakeNum to see which is closer to the alarm point, use the absolute value to compare, and take the camera with the smaller absolute value as the camera closest to the alarm point. If the two absolute values ​​are equal, then according to the stake number size and the road direction (upstream and downstream directions and sections), according to the business rules, determine which device will be the alarm point camera, and then determine the upstream and downstream cameras adjacent to the alarm point camera according to the stake number size and the road direction (upstream and downstream directions and sections).

[0062] Fourth, the plan strategy module, including the plan management submodule and the strategy execution submodule (i.e., it is configured with plans and strategies), is to control various tunnel equipment in a timely manner when an alarm occurs, and is used to remotely guide road order; the plan management submodule configures some road equipment control plans for emergencies; the strategy execution submodule refers to automatically controlling lighting equipment and ventilation equipment according to lighting strategies and ventilation strategies. Among them, 1) the plan management submodule includes the infield plan unit (automatically executed, such as automatically projecting the camera image when an alarm occurs) and the outfield plan unit (manually executed, such as the monitor operating the information board to guide traffic flow). Its attributes include the plan name (unique identifier, such as "fire level 1 plan"), activation status (controls whether the plan is enabled), the road section to which it belongs (the road section tunnel to which the plan type belongs, that is, the physical location to which the plan applies), tunnel partitioning (detailed to specific areas, such as "entrance section", "middle section"), execution method (manual execution by default), and controlled equipment (such as traffic lights, information boards, lane indicators, cross-tunnel gates, cross-tunnels signs, etc.), selects a plan based on the tunnel section, tunnel partition, and associated equipment alarms (bound trigger conditions, such as COVI exceeding the standard, fire alarm); the infield plan unit automatically executes and automatically projects the camera image closest to the alarm point to the TV wall of the monitoring center for staff to confirm the on-site situation; the outfield plan unit monitors the incoming and outgoing directions of the alarm point through upstream and downstream cameras, and generates traffic evacuation instructions based on the incoming and outgoing directions for staff (monitors) to manually execute traffic evacuation to prevent secondary accidents, and reports the traffic evacuation situation to the event handling module in real time.

[0063] 2) The strategy execution submodule includes a lighting strategy unit (divided into time control, light control, and manual modes, controlling lighting according to time or light data) and a ventilation strategy unit (divided into COVI mode and manual mode, regulating fans according to harmful gas concentrations). Both automatically trigger device control by matching preset conditions with real-time data, and support manual intervention, forming a closed-loop management from alarm response to environmental control. Among them, the lighting strategy unit and the ventilation strategy unit both include attributes such as the strategy name (such as "entrance section light control strategy"), strategy mode (manual mode / time control mode / light control mode), road section name, tunnel, strategy status (on / off), monitoring indicators (such as light intensity Lux, time, etc.), trigger conditions (such as starting enhanced lighting when the entrance illumination is <100 Lux), control equipment (lighting lamps, enhanced lighting equipment, etc.), and commands;

[0064] The lighting strategy unit's strategy modes include time control mode, light control mode, and manual mode. Specifically, in time control mode, the corresponding lighting equipment and enhanced lighting equipment are controlled according to the configured time period; in light control mode, the lighting equipment is automatically controlled based on monitoring indicators, trigger conditions, and strategy status; in manual mode, the monitoring personnel manually and remotely control the lighting equipment.

[0065] The strategy modes of the ventilation strategy unit include covi mode and manual mode. Specifically: in covi mode, the fan is automatically turned on or off according to monitoring indicators, trigger conditions and strategy status; in manual mode, the monitoring personnel manually remotely control the switch of the tunnel fan equipment.

[0066] 5. The event handling module generates emergencies based on alarm events and traffic evacuation conditions, and then classifies the emergencies according to the Ministry of Transport documents. Based on the level, road section and event type of the emergency, it links the pre-established emergency plan and notifies relevant units for joint processing.

[0067] Specifically, the event handling module is where staff (monitors) manually convert the alarm events of the alarm module and the traffic evacuation conditions reported by the field plan unit of the plan strategy module into emergencies. They then classify the emergencies according to the Ministry of Transport documents. Based on the emergency level, the road section to which it belongs (the tunnel to which the emergency belongs), and the type of event, they associate the pre-established emergency plan. When an abnormal alarm is detected, they notify relevant personnel of relevant units through pop-up windows, voice notifications, and other means to coordinate the handling (by sending location-enabled text messages and notifying relevant units by phone to quickly arrive at the scene to handle the situation), such as traffic police, firefighters, hospitals, etc., to quickly handle the incident and ensure timely restoration of tunnel traffic. The emergency plan here is an emergency plan for configuring external personnel (traffic police, road administration, maintenance, hospitals, emergency bureaus, rescue, etc.), displaying information on the information board during event handling, and text message and phone notifications to relevant personnel.

[0068] The present invention also relates to a tunnel monitoring emergency method based on an interpolation algorithm and a binary search algorithm. This method corresponds to the above-mentioned tunnel monitoring emergency system based on the interpolation algorithm and the binary search algorithm, and can be understood as an implementation method of the above-mentioned tunnel monitoring emergency system based on the interpolation algorithm and the binary search algorithm. The method includes an Internet of Things data collection step, a data processing step, an alarm step, a plan strategy step, and an event handling step.

[0069] IoT data collection steps: Real-time collection of tunnel environment data and device status data of event monitoring equipment;

[0070] Data processing step: judging whether the environmental data and device status data have data missing or abnormalities according to a pre-set condition threshold; if data missing or abnormalities are determined to exist, using the environmental data and device status data of two adjacent moments and an interpolation algorithm to calculate an estimated value of the current moment; and supplementing and correcting the environmental data and device status data of the current moment according to the estimated value;

[0071] Alarm steps: Based on the tunnel environment, operation period and device type of the event monitoring device, the alarm parameters are dynamically configured in advance for the event monitoring device, and the completed and corrected environmental data and device status data are compared with the dynamically configured alarm parameters to determine whether the alarm condition is met. If so, an alarm event is generated, and the event monitoring device that meets the alarm condition is used as the target device, and the location of the target device is used as the alarm point; then, the pile numbers of all cameras in the tunnel are arranged in ascending order according to size to obtain a camera pile number sequence. Based on the camera pile number sequence, the pile number of the target device, the uplink and downlink directions and the road section, a binary search algorithm is used to locate the camera closest to the alarm point. Then, according to the pile number size, uplink and downlink directions and the road section of the nearest camera, the upstream and downstream cameras adjacent to the nearest camera are determined;

[0072] Emergency plan strategy step: including emergency plan management, which includes internal and external emergency plans. The internal emergency plan automatically projects the camera image closest to the alarm point to the video wall of the monitoring center for staff to confirm the on-site situation. The external emergency plan monitors the incoming and outgoing directions of the alarm point through upstream and downstream cameras, generates traffic evacuation instructions based on the incoming and outgoing directions for staff to manually execute, and reports the traffic evacuation situation to the event handling step in real time;

[0073] Incident handling steps: Generate an emergency based on the alarm event and traffic evacuation situation and classify the emergency. According to the level, road section and event type of the emergency, link it to the pre-established emergency plan and notify relevant units for joint processing.

[0074] Preferably, the plan strategy step further includes strategy execution, executing lighting strategy and ventilation strategy respectively, wherein the lighting strategy and ventilation strategy each include strategy mode, monitoring index, trigger condition and strategy status;

[0075] The lighting strategy includes a time control mode, a light control mode, and a first manual mode. In the time control mode, the corresponding lighting equipment and enhanced lighting equipment are controlled according to the configured time period. In the light control mode, the lighting equipment is automatically controlled according to the monitoring indicators, trigger conditions, and the strategy status. In the first manual mode, the lighting equipment is manually and remotely controlled by the monitoring personnel.

[0076] The strategy modes of the ventilation strategy unit include covi mode and a second manual mode. In covi mode, the fan is automatically turned on or off according to monitoring indicators, trigger conditions and strategy status; in the second manual mode, the monitoring personnel manually remotely control the switch of the tunnel fan equipment.

[0077] Preferably, in the alarm step, based on the camera pile number sequence, the pile number of the target device, the uplink and downlink directions and the road section, and using a binary search algorithm to locate the camera closest to the alarm point specifically includes the following steps:

[0078] S1: Initialize the index of the first camera and the index of the last camera in the camera pile sequence; and use the index of the first camera as the left index and the index of the last camera as the right index;

[0079] S2: Calculate the index of the middle camera based on the initialized left index and right index, and use the index of the middle camera as the middle index. Extract the pile number of the middle camera from the camera pile number sequence based on the middle index, and then compare the pile number of the middle camera with the pile number of the target device. If the pile number of the middle camera is smaller than the pile number of the target device, update the left index to the middle index, and narrow the range of the camera pile number sequence from the middle index to the right index; if the pile number of the middle camera is greater than or equal to the pile number of the target device, update the right index to the middle index, and narrow the range of the camera pile number sequence from the left index to the middle index;

[0080] S3: Repeat step S2 until the left index and the right index are adjacent, and obtain two adjacent cameras corresponding to the left index and the right index respectively;

[0081] S4: Calculate the absolute values ​​of the pile numbers of the two adjacent cameras and the interpolated pile numbers of the target device respectively, and compare the two absolute values. The camera with the smaller absolute value is regarded as the camera closest to the alarm point. If the two absolute values ​​are equal, one of the two adjacent cameras is regarded as the camera closest to the alarm point according to the pile number size, uplink and downlink directions, and road sections according to business rules.

[0082] Preferably, in the data processing step, judging whether the environmental data and the device status data have data missing or abnormal according to a preset condition threshold specifically includes: comparing each parameter in the environmental data and the device status data with the preset condition threshold respectively; if the value of a certain parameter is greater than the condition threshold, judging that the parameter is missing or abnormal.

[0083] Preferably, in the IoT data collection step, the environmental data includes temperature, humidity and harmful gas concentration; the event monitoring equipment includes cameras, harmful gas monitoring equipment, illumination brightness monitoring equipment, meteorological instruments, wind speed and direction equipment, high and low water level pools, information boards, fire alarm equipment and programmable logic controllers; the equipment status data includes current, voltage, power, liquid level and equipment temperature.

[0084] The present invention provides an objective and scientific tunnel monitoring emergency method and system based on interpolation and binary search algorithms. By comprehensively applying multiple methods such as finite element analysis, modal analysis, stress monitoring, and fatigue damage assessment, it achieves comprehensive and efficient health monitoring of key parts of ships, especially welds. This not only improves the monitoring capability of ship structural safety, but also significantly reduces operating costs and reduces the risks caused by structural failure. In addition, by using data from a limited number of local stress monitoring devices, it can accurately calculate the stress in the weld area, consume less computing resources, facilitate long-term fatigue life management, and promote the scientific and refined management of maintenance work. It is of great significance to improving the safety and economic benefits of the entire shipping industry.

[0085] It should be noted that the specific embodiments described above can enable those skilled in the art to more fully understand the present invention, but do not limit the present invention in any way. Therefore, although this specification has described the present invention in detail with reference to the drawings and embodiments, those skilled in the art should understand that the present invention can still be modified or replaced with equivalents. In short, all technical solutions and improvements that do not depart from the spirit and scope of the present invention should be included in the scope of protection of the patent for the present invention.

Claims

1. A tunnel monitoring emergency system based on interpolation algorithm and binary search algorithm, characterized in that: It includes the IoT data acquisition module, data processing module, alarm module, emergency strategy module and event handling module connected in sequence. The IoT data acquisition module is used to collect real-time environmental data in the tunnel and device status data of event monitoring equipment, and transmit the collected data to the data processing module; The data processing module receives environmental data and device status data, and determines whether the environmental data and device status data have data missing or abnormalities based on a pre-set condition threshold. When it is determined that data missing or abnormalities exist, the data processing module calculates an estimated value of the current moment based on the environmental data and device status data of two moments adjacent to the current moment using an interpolation algorithm, completes and corrects the environmental data and device status data of the current moment based on the estimated value, and transmits the completed and corrected environmental data and device status data to the alarm module; The alarm module dynamically configures alarm parameters for the event monitoring device in advance based on the tunnel environment, operation period and device type of the event monitoring device, and compares the completed and corrected environmental data and device status data with the dynamically configured alarm parameters to determine whether the alarm condition is met. If so, an alarm event is generated, and the event monitoring device that meets the alarm condition is used as the target device, and the location of the target device is used as the alarm point; the pile numbers of all cameras in the tunnel are then arranged in ascending order according to size to obtain a camera pile number sequence, and based on the camera pile number sequence, the pile number of the target device, the uplink and downlink directions and the road section, a binary search algorithm is used to locate the camera closest to the alarm point, and then the upstream camera and downstream camera adjacent to the nearest camera are determined according to the pile number size, uplink and downlink directions and the road section of the nearest camera; The emergency plan strategy module includes an emergency plan management submodule, which includes an indoor emergency plan unit and an outdoor emergency plan unit. The indoor emergency plan unit automatically projects the camera image closest to the alarm point to the TV wall of the monitoring center for staff to confirm the on-site situation; the outdoor emergency plan unit monitors the incoming and outgoing directions of the alarm point through upstream and downstream cameras, generates traffic evacuation instructions based on the incoming and outgoing directions for staff to manually execute, and reports the traffic evacuation situation to the event handling module in real time; The event handling module generates an emergency event based on the alarm event and the traffic evacuation situation and classifies the emergency event. According to the level of the emergency event, the road section to which it belongs and the event type, it associates the pre-established emergency plan and notifies the relevant units to carry out joint processing.

2. The tunnel monitoring emergency system based on interpolation algorithm and binary search algorithm according to claim 1 is characterized in that: The plan strategy module also includes a strategy execution submodule, which includes a lighting strategy unit and a ventilation strategy unit. The lighting strategy unit and the ventilation strategy unit each include a strategy mode, a monitoring indicator, a trigger condition, and a strategy state. The strategy modes of the lighting strategy unit include a time control mode, a light control mode, and a first manual mode. In the time control mode, the corresponding lighting device and the enhanced lighting device are controlled to be turned on and off according to the configured time period. In the light control mode, the lighting device is automatically controlled to be turned on and off according to the monitoring indicator, the trigger condition, and the strategy state. In the first manual mode, the lighting equipment switch is manually and remotely controlled by the monitoring personnel; the strategy mode of the ventilation strategy unit includes covi mode and the second manual mode. In covi mode, the fan is automatically turned on or off according to the monitoring indicators, trigger conditions and strategy status; In the second manual mode, the monitoring personnel manually and remotely control the switch of the tunnel fan equipment.

3. The tunnel monitoring emergency system based on interpolation algorithm and binary search algorithm according to claim 1 is characterized in that: In the alarm module, based on the camera pile number sequence, the pile number of the target device, the uplink and downlink directions and the road section, a binary search algorithm is used to locate the camera closest to the alarm point, specifically including the following steps: S1: Initialize the index of the first camera and the index of the last camera in the camera pile sequence; and use the index of the first camera as the left index and the index of the last camera as the right index; S2: Calculate the index of the middle camera based on the initialized left index and right index, and use the index of the middle camera as the middle index. Extract the pile number of the middle camera from the camera pile number sequence based on the middle index, and then compare the pile number of the middle camera with the pile number of the target device. If the pile number of the middle camera is smaller than that of the target device, update the left index to the middle index; if the pile number of the middle camera is larger than that of the target device, update the right index to the middle index; if the pile number of the middle camera is equal to that of the target device, directly output the middle index; S3: Repeat step S2 until the left index and the right index are adjacent, and obtain two adjacent cameras corresponding to the left index and the right index respectively; S4: Calculate the absolute values ​​of the pile numbers of the two adjacent cameras and the interpolated pile numbers of the target device respectively, and compare the two absolute values. The camera with the smaller absolute value is regarded as the camera closest to the alarm point. If the two absolute values ​​are equal, one of the two adjacent cameras is regarded as the camera closest to the alarm point according to the pile number size, uplink and downlink directions, and road sections according to business rules.

4. The tunnel monitoring emergency system based on the interpolation algorithm and the binary search algorithm according to any one of claims 1 to 3, characterized in that: In the data processing module, judging whether the environmental data and the device status data have data missing or abnormal according to the pre-set condition threshold specifically includes: comparing each parameter in the environmental data and the device status data with the pre-set condition threshold respectively; if the value of a certain parameter is greater than the condition threshold, judging that the parameter is missing or abnormal.

5. The tunnel monitoring emergency system based on interpolation algorithm and binary search algorithm according to any one of claims 1 to 3, characterized in that: In the Internet of Things data acquisition module, the environmental data includes temperature, humidity and harmful gas concentration; the event monitoring equipment includes cameras, harmful gas monitoring equipment, illumination brightness monitoring equipment, meteorological instruments, wind speed and direction equipment, high and low water level pools, information boards, fire alarm equipment and programmable logic controllers; the equipment status data includes current, voltage, power, liquid level and equipment temperature.

6. A tunnel monitoring emergency method based on interpolation algorithm and binary search algorithm, characterized in that: The following steps are involved: IoT data collection steps: Real-time collection of tunnel environment data and device status data of event monitoring equipment; Data processing step: judging whether the environmental data and device status data have data missing or abnormalities according to a pre-set condition threshold; if data missing or abnormalities are determined to exist, using the environmental data and device status data of two adjacent moments and an interpolation algorithm to calculate an estimated value of the current moment; and supplementing and correcting the environmental data and device status data of the current moment according to the estimated value; Alarm steps: Based on the tunnel environment, operation period and device type of the event monitoring device, the alarm parameters are dynamically configured in advance for the event monitoring device, and the completed and corrected environmental data and device status data are compared with the dynamically configured alarm parameters to determine whether the alarm condition is met. If so, an alarm event is generated, and the event monitoring device that meets the alarm condition is used as the target device, and the location of the target device is used as the alarm point; then, the pile numbers of all cameras in the tunnel are arranged in ascending order according to size to obtain a camera pile number sequence. Based on the camera pile number sequence, the pile number of the target device, the uplink and downlink directions and the road section, a binary search algorithm is used to locate the camera closest to the alarm point. Then, according to the pile number size, uplink and downlink directions and the road section of the nearest camera, the upstream and downstream cameras adjacent to the nearest camera are determined; Emergency plan strategy step: including emergency plan management, which includes internal and external emergency plans. The internal emergency plan automatically projects the camera image closest to the alarm point to the video wall of the monitoring center for staff to confirm the on-site situation. The external emergency plan monitors the incoming and outgoing directions of the alarm point through upstream and downstream cameras, generates traffic evacuation instructions based on the incoming and outgoing directions for staff to manually execute, and reports the traffic evacuation situation to the event handling step in real time; Incident handling steps: Generate an emergency based on the alarm event and traffic evacuation situation and classify the emergency. According to the level of the emergency, the road section and the type of incident, link it to the pre-established emergency plan and notify relevant units for joint processing.

7. The tunnel monitoring emergency method based on interpolation algorithm and binary search algorithm according to claim 6 is characterized in that: The plan strategy step also includes strategy execution, executing lighting strategy and ventilation strategy respectively, wherein the lighting strategy and ventilation strategy each include strategy mode, monitoring indicators, trigger conditions and strategy status; The lighting strategy includes a time control mode, a light control mode, and a first manual mode. In the time control mode, the corresponding lighting equipment and enhanced lighting equipment are controlled according to the configured time period. In the light control mode, the lighting equipment is automatically controlled according to the monitoring indicators, trigger conditions, and the strategy status. In the first manual mode, the lighting equipment is manually and remotely controlled by the monitoring personnel. The strategy mode of the ventilation strategy unit includes covi mode and a second manual mode. In covi mode, the fan is automatically turned on or off according to the monitoring indicators, trigger conditions and strategy status; In the second manual mode, the monitoring personnel manually and remotely control the switch of the tunnel fan equipment.

8. The tunnel monitoring emergency method based on interpolation algorithm and binary search algorithm according to claim 6 is characterized in that: In the alarm step, based on the camera pile number sequence, the pile number of the target device, the uplink and downlink directions and the road section, a binary search algorithm is used to locate the camera closest to the alarm point, which specifically includes the following steps: S1: Initialize the index of the first camera and the index of the last camera in the camera pile sequence; and use the index of the first camera as the left index and the index of the last camera as the right index; S2: Calculate the index of the middle camera based on the initialized left index and right index, and use the index of the middle camera as the middle index. Extract the pile number of the middle camera from the camera pile number sequence based on the middle index, and then compare the pile number of the middle camera with the pile number of the target device. If the pile number of the middle camera is smaller than the pile number of the target device, update the left index to the middle index, and narrow the range of the camera pile number sequence from the middle index to the right index; if the pile number of the middle camera is greater than or equal to the pile number of the target device, update the right index to the middle index, and narrow the range of the camera pile number sequence from the left index to the middle index; S3: Repeat step S2 until the left index and the right index are adjacent, and obtain two adjacent cameras corresponding to the left index and the right index respectively; S4: Calculate the absolute values ​​of the pile numbers of the two adjacent cameras and the interpolated pile numbers of the target device respectively, and compare the two absolute values. The camera with the smaller absolute value is regarded as the camera closest to the alarm point. If the two absolute values ​​are equal, one of the two adjacent cameras is regarded as the camera closest to the alarm point according to the pile number size, uplink and downlink directions, and road sections according to business rules.

9. The tunnel monitoring emergency method based on interpolation algorithm and binary search algorithm according to any one of claims 6 to 8, characterized in that: In the data processing step, judging whether the environmental data and the device status data have data missing or abnormal according to the pre-set condition threshold specifically includes: comparing each parameter in the environmental data and the device status data with the pre-set condition threshold respectively; if the value of a certain parameter is greater than the condition threshold, judging that the parameter is missing or abnormal.

10. The tunnel monitoring emergency method based on interpolation algorithm and binary search algorithm according to any one of claims 6 to 8, characterized in that: In the IoT data collection step, the environmental data includes temperature, humidity and harmful gas concentration; the event monitoring equipment includes cameras, harmful gas monitoring equipment, illumination brightness monitoring equipment, meteorological instruments, wind speed and direction equipment, high and low water level pools, information boards, fire alarm equipment and programmable logic controllers; the equipment status data includes current, voltage, power, liquid level and equipment temperature.

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