Tunnel fire linkage communication transmission system

Abstract

The present application relates to the technical field of tunnel safety monitoring, in particular to a tunnel fire linkage communication transmission system, comprising: a device for real-time collection of fire hazard parameters by means of a wireless mesh network self-organizing local area network built inside the tunnel, and a multi-sensor node. After the single-node data exceeds the limit, the network disaster working mode is activated, and the global node high-frequency synchronous collection forms a dense space-time sampling data stream. An improved weighted centroid positioning algorithm is introduced, which fuses signal strength features and parameter space-time gradient to accurately measure the initial coordinates of the fire source, dynamically constructs a data aggregation cluster with an adaptive communication radius based on the coordinates, completes the time scale alignment and fusion processing of the data stream, and integrates the standardized tunnel fire fusion data packet. The system realizes cross-domain information interaction with the help of the communication relay module arranged at both ends of the tunnel, stably transmits the fire data to the remote early warning platform, and improves the overall operation capability of fire monitoring, fire source measurement and long-distance communication transmission in the narrow and closed tunnel scene.

Description

Technical Field

[0001] This invention relates to the field of tunnel safety monitoring technology, and in particular to a tunnel fire linkage communication transmission system. Background Technology

[0002] Tunnels are enclosed and elongated spaces with complex internal electromagnetic environments. Existing tunnel fire monitoring and communication systems generally employ fixed network operation modes and constant-frequency data acquisition methods. Local area networks only maintain routine communication operations and lack the ability to autonomously switch operating modes. In conventional monitoring architectures, the data acquisition rhythm of sensor devices remains constant, unable to adjust the acquisition mechanism according to abnormal environmental conditions. The ability to synchronously control data across the entire area after an environmental anomaly is triggered is lacking, the density of environmental parameter acquisition is limited, and continuous data recording during environmental changes is incomplete, making it difficult to meet the refined monitoring needs of special risk scenarios.

[0003] Current methods for calculating fire source locations rely on a single computational dimension, with algorithms analyzing only basic monitoring parameters and failing to incorporate collaborative analysis based on sensor node signal states and spatiotemporal parameter variations. This limits the accuracy of identifying anomaly sources within the environmental space. Data transmission and processing employ a uniform, indiscriminate transmission mechanism, failing to integrate anomaly location information for regionalized data management. Data temporal consistency is poor, and raw monitoring data lacks standardized integration. The rigid data scheduling methods within tunnel local area networks lead to uneven data transmission load distribution over long distances. The adaptability of cross-regional transmission links from internal monitoring data to external platforms is insufficient, and the overall monitoring and communication system's emergency adaptability cannot meet the demands of tunnel fire emergencies. There is a practical need within the industry for an integrated tunnel fire communication and monitoring solution with adaptive mode control, precise positioning, and directional data fusion transmission. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology and propose a tunnel fire linkage communication transmission system.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a tunnel fire linkage communication transmission system, comprising:

[0006] The data acquisition module deploys a self-organizing local area network within the tunnel based on a wireless mesh network, and collects fire hazard parameters in the tunnel in real time through multiple sensor nodes distributed throughout the tunnel.

[0007] The network activation module automatically activates the disaster recovery mode of the self-organizing local area network in the tunnel when the real-time data collected by any sensor node exceeds its preset alarm threshold.

[0008] In disaster-time operation mode, all working sensor nodes in the self-organizing local area network inside the tunnel synchronously collect the fire hazard parameters at the highest sampling frequency, forming a dense spatiotemporal sampling data stream.

[0009] The fire source location module inputs the dense spatiotemporal sampling data stream into the improved weighted centroid location algorithm. The improved weighted centroid location algorithm makes a preliminary estimate of the fire source location based on the signal strength characteristics of multiple sensor nodes and the spatiotemporal gradient of fire hazard parameters, and outputs the initial coordinates of the fire source.

[0010] The data aggregation module dynamically constructs a data aggregation cluster with an adaptive communication radius centered on the initial coordinates of the fire source in the self-organizing local area network within the tunnel, based on the initial coordinates of the fire source. The module then performs time-scale alignment and data fusion of the dense spatiotemporal sampled data stream within the data aggregation cluster to generate a tunnel fire fusion data packet.

[0011] The cross-domain transmission module, through communication relay modules deployed at both ends of the tunnel, transmits tunnel fire fusion data packets across regions to a remote early warning platform outside the tunnel.

[0012] As a further aspect of the present invention, the deployment of a self-organizing local area network within the tunnel based on a wireless mesh network includes:

[0013] Multiple full-function mesh network routers are deployed at equal intervals along the longitudinal direction of the tunnel. Each mesh network router has at least three non-coplanar directional antennas, which are directed toward both ends of the tunnel longitudinally and the top of the tunnel, respectively.

[0014] Establish at least two redundant wireless communication links between adjacent mesh network routers to form a mesh network backbone covering the entire tunnel.

[0015] Based on the mesh network backbone, multiple sensor node clusters are connected in a star topology. Each sensor node cluster contains multiple sensor nodes that collect different fire hazard parameters. Each sensor node establishes a subordinate connection with its nearest mesh network router.

[0016] Configure a unified network time slot synchronization mechanism for the self-organizing local area network throughout the tunnel to ensure that the clocks of all mesh network routers and sensor nodes are synchronized within the microsecond error range.

[0017] As a further aspect of the present invention, the real-time collection of fire hazard parameters within the tunnel by multiple sensor nodes distributed throughout the tunnel includes:

[0018] The fire hazard parameters include temperature data, smoke concentration data, and carbon monoxide concentration data.

[0019] Temperature and humidity composite sensors are installed at multiple height locations at the top, side walls, and bottom of the tunnel to collect temperature data at different spatial levels;

[0020] A laser scattering smoke sensor is installed in the arched area at the top of the tunnel to collect smoke concentration data that reflects the concentration of smoke particles.

[0021] An electrochemical carbon monoxide sensor is installed on the sidewall at a predetermined height above the tunnel surface to collect carbon monoxide concentration data.

[0022] Control all temperature and humidity composite sensors, laser scattering smoke sensors, and electrochemical carbon monoxide sensors to perform cyclic sampling at a preset basic sampling period. Each sampling includes the measurement values ​​of multiple consecutive sampling points, and the arithmetic mean of these values ​​is taken as the temperature data, smoke concentration data, or carbon monoxide concentration data output for the corresponding period.

[0023] As a further aspect of the present invention, when the real-time data collected by any sensor node exceeds its preset alarm threshold, the disaster recovery mode of the self-organizing local area network within the tunnel is automatically activated, including:

[0024] Set type-related independent alarm thresholds for each type of sensor node, where the alarm threshold for temperature data is a preset upper temperature limit, the alarm threshold for smoke concentration data is a preset lower concentration limit, and the alarm threshold for carbon monoxide concentration data is a preset lower gas concentration limit.

[0025] In each acquisition cycle, the sensor node compares its output temperature data, smoke concentration data, or carbon monoxide concentration data with its corresponding independent alarm threshold.

[0026] When any real-time data exceeds its independent alarm threshold, the sensor node that generates the alarm immediately sends a disaster mode activation broadcast frame containing its own node identifier and alarm type to the entire network through the self-organizing local area network in the tunnel.

[0027] Upon receiving the disaster mode activation broadcast frame, the mesh network router in the self-organizing local area network inside the tunnel switches to a preset high-power, high-throughput communication configuration and commands all its subordinate sensor nodes to switch to the highest sampling frequency, thereby globally activating the disaster working mode.

[0028] As a further aspect of the present invention, the improved weighted centroid localization algorithm performs a preliminary estimation of the fire source location based on the signal strength characteristics of multiple sensor nodes and the spatiotemporal gradient of fire hazard parameters, and outputs the initial coordinates of the fire source, including:

[0029] In disaster response mode, the system acquires the fire hazard parameters collected by all sensor nodes in the self-organizing local area network within the tunnel at the current moment, as well as the signal strength indication of the communication link between each sensor node and its associated mesh network router.

[0030] For temperature data, calculate its temperature gradient vector field in the three-dimensional space of the tunnel, and identify the spatial point with the largest magnitude in the temperature gradient vector field.

[0031] For smoke concentration data, calculate its concentration diffusion gradient on the plane formed by the longitudinal and vertical directions of the tunnel, and identify the axis of the direction with the fastest concentration diffusion.

[0032] The signal strength indication reported by each sensor node is converted into a distance weighting factor between the node and the potential fire source. The lower the signal strength indication, the larger the corresponding distance weighting factor.

[0033] By combining the spatial point with the largest magnitude in the temperature gradient vector field, the axis of the direction with the fastest concentration diffusion, and the distance weighting factors of all sensor nodes, the coordinates of the spatial point that minimizes the overall error are obtained by iteratively minimizing the weighted distance error function. The coordinates of the spatial point are the initial coordinates of the fire source output by the improved weighted centroid localization algorithm.

[0034] As a further aspect of the present invention, based on the initial coordinates of the fire source, a data aggregation cluster with an adaptive communication radius centered on the initial coordinates of the fire source is dynamically constructed in a self-organizing local area network within the tunnel, including:

[0035] Based on the projection of the initial coordinates of the fire source onto the longitudinal direction of the tunnel, the mesh network router located closest to the projection position is selected as the cluster head node of the data aggregation cluster;

[0036] Based on the maximum value of temperature data and smoke concentration data reported by all sensor nodes at the current moment, query the preset communication radius mapping table to determine the initial communication radius of the data aggregation cluster;

[0037] Centered on the cluster head node and bounded by the initial communication radius, a geographical circular area is defined in the self-organizing local area network within the tunnel. All mesh network routers and sensor nodes located within the geographical circular area are incorporated into the data aggregation cluster.

[0038] Sensor nodes included in the data aggregation cluster send their dense spatiotemporal sampling data streams directly to the cluster head node, instead of forwarding them in the mesh network routers outside the data aggregation cluster.

[0039] As a further aspect of the present invention, the dense spatiotemporal sampling data stream is time-stamped and fused within a data aggregation cluster to generate a tunnel fire fusion data packet, including:

[0040] The cluster head node receives and aggregates dense spatiotemporal sampled data streams sent by all sensor nodes within the cluster. Each data stream consists of time-stamped data packets.

[0041] The cluster head node performs time synchronization sorting on all received data packets based on the timestamp, and aligns the temperature data, smoke concentration data and carbon monoxide concentration data within the same millisecond time window into a fused data frame;

[0042] Spatial interpolation and confidence-weighted averaging are performed on the multi-sensor data in each fused data frame to generate temperature, smoke concentration and carbon monoxide concentration values ​​at uniform grid points in the tunnel space corresponding to the fused data frame.

[0043] The grid data obtained from processing multiple consecutive fused data frames are packaged in chronological order, and the initial coordinates of the fire source, the data aggregation cluster identifier, and the start and end times of data acquisition are attached to generate a tunnel fire fused data package.

[0044] As a further aspect of the present invention, the method of transmitting tunnel fire fusion data packets across regions to a remote early warning platform outside the tunnel via communication relay modules deployed at both ends of the tunnel includes:

[0045] A communication relay module is deployed outside the tunnel entrance and exit, and each communication relay module contains a long-range wireless communication unit and a high-gain directional antenna;

[0046] The cluster head node of the self-organizing local area network inside the tunnel simultaneously sends the tunnel fire fusion data packet to the nearest mesh network router at both the tunnel entrance and the tunnel exit.

[0047] The mesh network routers at the tunnel entrance and tunnel exit forward the received tunnel fire fusion data packets to the corresponding communication relay modules via wired or short-range wireless means.

[0048] The communication relay modules at the tunnel entrance and exit modulate the tunnel fire fusion data packets onto different licensed frequency bands and transmit them to the remote early warning platform in a point-to-point manner via high-gain directional antennas.

[0049] As a further aspect of the present invention, the system further includes:

[0050] The link control module, wherein the communication relay module establishes a communication link with the remote early warning platform using a hybrid multiple access method that combines time division duplex and frequency division multiplexing;

[0051] The early warning and analysis module allows the remote early warning platform to receive and analyze the tunnel fire fusion data packet, extract the initial coordinates of the fire source and fire hazard parameters, and use them to activate the fire emergency plan.

[0052] The communication relay module establishes a communication link with the remote early warning platform using a hybrid multiple access method combining time division duplex and frequency division multiplexing, including:

[0053] The remote early warning platform periodically broadcasts downlink synchronization beacons on multiple different frequencies;

[0054] The communication relay module scans multiple different frequency points and locks onto the downlink synchronization beacon with the best signal quality, thereby determining the initial operating frequency point and uplink time slot allocation for communication with the remote early warning platform;

[0055] During the data transmission phase, the remote early warning platform and the communication relay module alternately transmit and receive data in time-division duplex mode on the same frequency. The remote early warning platform transmits control commands in the downlink time slot, while the communication relay module transmits tunnel fire fusion data packets in the allocated uplink time slot.

[0056] When the data volume of the tunnel fire fusion data packet exceeds the capacity of a single uplink time slot, the remote early warning platform dynamically allocates additional frequency points to the corresponding communication relay module. The communication relay module simultaneously transmits data in parallel on the initial working frequency point and the additionally allocated frequency points, realizing frequency division multiplexing.

[0057] As a further aspect of the present invention, the remote early warning platform receives and parses the tunnel fire fusion data packet, extracts the initial coordinates of the fire source and fire hazard parameters therein, and uses them to activate the fire emergency plan, including:

[0058] The remote early warning platform deduplicatizes and merges tunnel fire fusion data packets received from different communication relay modules to restore the complete tunnel fire fusion data packets.

[0059] The encapsulation header of the tunnel fire fusion data packet is analyzed to extract the initial coordinates of the fire source, the data aggregation cluster identifier, and the start and end times of data acquisition.

[0060] Parse the payload of the tunnel fire fusion data packet and read the fusion data frames arranged in chronological order. Each fusion data frame contains the temperature value, smoke concentration value and carbon monoxide concentration value at the tunnel spatial grid points.

[0061] The extracted initial coordinates of the fire source and the fused data frame that evolves over time are stored in the early warning platform database, and the fire emergency plan is automatically triggered according to preset rules.

[0062] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0063] Based on the threshold judgment conditions of sensor node monitoring data, the self-organizing local area network (LAN) operation mode within the tunnel can be autonomously switched. The network can autonomously switch between normal working state and disaster-time working mode, and all sensor devices synchronously adjust their operating parameters, uniformly carrying out continuous parameter collection at the highest sampling frequency. This globally synchronized data collection method can improve the collection density of fire hazard parameters, make up for the insufficient data collection frequency under the conventional fixed sampling mode, continuously produce continuous and complete spatiotemporal sampling data, improve the continuous recording of environmental parameters in confined spaces, enrich the volume of raw monitoring data under abnormal conditions, and ensure that the dynamic process of environmental parameter changes is completely preserved, thus improving the slow data update rhythm under normal collection mode.

[0064] By incorporating the signal strength characteristics of sensor nodes and the spatiotemporal gradient of fire hazard parameters into the positioning calculation process, the computational reference dimensions of the weighted centroid positioning algorithm are expanded, enriching the judgment basis for location measurement, optimizing the discrimination logic of heat source location within space, and improving the stability of target point coordinate output in narrow, long-distance spaces. Based on the calculated initial coordinates of the fire source, the data processing range is directionally defined, a data aggregation cluster with an adjustable communication radius is built, the coverage of data interaction is limited, and the data flow path within the local area network is standardized.

[0065] By unifying the time base of multi-source monitoring data within a cluster, integrating and processing multiple data streams, and reducing data clutter caused by the direct transmission of fragmented raw data, the system standardizes the output format of fire data and simplifies subsequent data transmission and processing. The standardized and integrated fire fusion data package is adaptable to the communication transmission conditions of narrow tunnel structures, relies on fixed relay equipment to complete cross-regional data exchange, optimizes the resource allocation of local area network data transmission, balances the data transmission load during long-distance communication, and improves the standardization of data transmission in local area networks during emergency situations. Attached Figure Description

[0066] Figure 1 This is a state diagram of a tunnel fire linkage communication transmission system according to the present invention;

[0067] Figure 2 A flowchart for deploying a self-organizing local area network within a tunnel;

[0068] Figure 3 A flowchart for real-time collection of fire hazard parameters. Detailed Implementation

[0069] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0070] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0071] See Figure 1 This invention provides a tunnel fire-linked communication and transmission system. The system deploys a self-organizing local area network (LAN) within the tunnel based on a wireless mesh network, and collects fire hazard parameters in real time through distributed sensor nodes. When an anomaly is detected, the system automatically activates a disaster-time operating mode, increases data collection density, and initiates the linked communication and transmission process. This process includes preliminary fire source location based on dense data streams, dynamically constructing data aggregation clusters around the fire source for efficient data fusion, and finally transmitting the fused data across regions to a remote early warning platform via communication relay modules at both ends of the tunnel.

[0072] In one embodiment of the invention, a self-organizing local area network (LAN) based on a wireless mesh network is deployed within the tunnel. For deployment details, please refer to [reference needed]. Figure 2 Multiple full-function mesh network routers are deployed at equal intervals along the tunnel's longitudinal direction. Each mesh network router has at least three non-coplanar directional antennas, which are directed towards both ends of the tunnel and the tunnel ceiling, respectively. At least two redundant wireless communication links are established between adjacent mesh network routers, forming a mesh network backbone covering the entire tunnel. Based on this mesh network backbone, multiple sensor node clusters are connected in a star topology. Each sensor node cluster contains multiple sensor nodes collecting different fire hazard parameters, and each sensor node establishes a subordinate connection with its nearest mesh network router. A unified network time slot synchronization mechanism is configured for the self-organizing local area network throughout the tunnel, ensuring that the clocks of all mesh network routers and sensor nodes are synchronized within a microsecond error range.

[0073] In practical implementation, the deployment of the self-organizing local area network (LAN) within the tunnel begins with the deployment of multiple full-function mesh network routers at equal intervals along the tunnel's longitudinal direction. Each full-function mesh network router is equipped with at least three non-coplanar directional antennas, which are directed towards both ends of the tunnel's longitudinal direction and the tunnel ceiling. The directional antennas at the tunnel's longitudinal ends are used to establish wireless communication links with adjacent full-function mesh network routers, while the directional antennas at the tunnel ceiling are used to enhance signal coverage in the vertical direction. In some embodiments, adjacent full-function mesh network routers establish at least two redundant wireless communication links wirelessly. These redundant wireless communication links employ different operating frequency bands or modulation and coding schemes, forming a mesh network backbone covering the entire tunnel. Each redundant wireless communication link in the mesh network backbone has independent data forwarding capabilities. In practical implementation, based on the mesh network backbone, multiple sensor node clusters are connected in a star topology. Each sensor node cluster contains multiple sensor nodes that collect different fire hazard parameters. Each sensor node establishes a subordinate connection with the nearest mesh network router, and the subordinate connection is established through association request and association response frames. Optionally, a unified network time slot synchronization mechanism can be configured for the entire self-organizing local area network within the tunnel. This mechanism is based on a precise time synchronization protocol to ensure that the clocks of all mesh network routers and sensor nodes are synchronized within a microsecond error range. The maximum clock synchronization deviation is calculated using the following formula:

[0074]

[0075] in: Indicates clock synchronization error. This indicates the local clock time of the mesh network router or sensor node. This represents the reference clock time broadcast by the main mesh network router. In some embodiments, the execution process of the network time slot synchronization mechanism includes the main mesh network router periodically sending synchronization messages, and subordinate mesh network routers and sensor nodes calculating clock offsets and adjusting local timers after receiving the synchronization messages. The calculation of clock offsets includes an estimate of message transmission delay. It can be understood that equally spaced deployment of full-function mesh network routers helps maintain the stability of wireless links, non-coplanar directional antenna configuration reduces signal interference, star topology access to sensor node clusters reduces network management complexity, and a unified network time slot synchronization mechanism supports the consistency of timestamp data. In a specific implementation, the initialization steps of the self-organizing local area network within the tunnel include the full-function mesh network router sending beacon frames to announce its existence after startup, neighboring full-function mesh network routers establishing redundant wireless communication links by exchanging neighbor discovery messages, and sensor nodes listening to beacon frames and selecting the full-function mesh network router with the highest received signal strength to initiate association. Optionally, redundant wireless communication links in the mesh network backbone run link-state routing protocols. The link-state routing protocols dynamically update the routing table based on link quality indicators. When a redundant wireless communication link fails, the data stream automatically switches to another redundant wireless communication link to continue transmission.

[0076] In one embodiment of the invention, multiple sensor nodes distributed throughout the tunnel are used to collect fire hazard parameters in real time. (See also...) Figure 3 The collected fire hazard parameters include temperature data, smoke concentration data, and carbon monoxide concentration data. Temperature and humidity composite sensors are installed at multiple heights at the tunnel top, sidewalls, and bottom to collect temperature data at different spatial levels. A laser scattering smoke sensor is installed in the arched area at the tunnel top to collect smoke concentration data reflecting the concentration of smoke particles. An electrochemical carbon monoxide sensor is installed on the sidewall at a preset height above the tunnel surface to collect carbon monoxide concentration data. All temperature and humidity composite sensors, laser scattering smoke sensors, and electrochemical carbon monoxide sensors are controlled to cyclically collect data at a preset basic sampling period. Each collection includes measurements from multiple consecutive sampling points, and the arithmetic mean of these measurements is taken as the output temperature, smoke concentration, or carbon monoxide concentration data for the corresponding period.

[0077] In practical implementation, multiple sensors are deployed and work together to collect fire hazard parameters, including temperature data, smoke concentration data, and carbon monoxide concentration data. Specifically, temperature and humidity composite sensors are installed at multiple heights at the tunnel top, sidewalls, and bottom. These sensors have waterproof and dustproof housings and are used to collect temperature data at different spatial levels. The sensor at the tunnel top monitors the accumulation of hot air, the sensor in the middle of the tunnel sidewalls monitors the horizontal temperature distribution, and the sensor at the tunnel bottom monitors the near-surface temperature. In some embodiments, a laser scattering smoke sensor is installed in the arched area at the tunnel top. This sensor uses a laser diode of a specific wavelength as a light source to collect smoke concentration data reflecting the concentration of smoke particles. The photodetector inside the laser scattering smoke sensor receives the laser signal scattered by the smoke particles. In another implementation, an electrochemical carbon monoxide sensor is installed on the sidewall at a predetermined height above the tunnel surface. This electrochemical carbon monoxide sensor includes sensing electrodes and an electrolyte and is used to collect carbon monoxide concentration data. The predetermined height is determined based on the common exhaust pipe height range of vehicles.

[0078] Optionally, all temperature and humidity composite sensors, laser scattering smoke sensors, and electrochemical carbon monoxide sensors are controlled to cyclically collect data at a preset basic sampling period. This preset basic sampling period is uniformly set by the main mesh network router of the tunnel's self-organizing local area network via broadcast configuration frames. Each sensor's microcontroller activates its analog-to-digital converter when it reaches its own sampling time. In some embodiments, each acquisition includes measurements from multiple consecutive sampling points. These measurements are temporarily stored in the local buffer of the sensor node. The arithmetic mean of these measurements is taken as the output temperature data, smoke concentration data, or carbon monoxide concentration data for the corresponding period. Calculating the arithmetic mean eliminates random noise interference from single sampling. It is understood that the temperature and humidity composite sensors, installed at multiple heights, can construct a vertical temperature profile; the laser scattering smoke sensor is sensitive to small smoke particles; the electrochemical carbon monoxide sensor has a specific response to carbon monoxide gas; and the preset basic sampling period balances power consumption and real-time monitoring. In practical implementation, after completing a basic sampling cycle of data acquisition and processing, the sensor node encapsulates the obtained temperature data, smoke concentration data, or carbon monoxide concentration data into a data packet. The data packet includes the sensor node identifier, parameter type, and timestamp, and is transmitted wirelessly to its associated mesh network router. Optionally, the temperature data output value acquired by the temperature and humidity composite sensor is converted using the following linearization formula:

[0079]

[0080] in: This represents the calculated temperature data (in degrees Celsius). This represents the raw digital reading output by the thermistor in the temperature and humidity composite sensor. This represents the conversion coefficient determined by the thermistor calibration table. This represents the calibration constant determined by the characteristics of the thermistor. It can be understood that the linearization formula converts the raw digital reading into a physically meaningful temperature value; the conversion coefficients and calibration constant are calibrated at the sensor's factory and stored in the sensor node's non-volatile memory.

[0081] In one embodiment of the present invention, when the real-time data collected by any sensor node exceeds its preset alarm threshold, the disaster recovery mode of the self-organizing local area network (VLAN) within the tunnel is automatically activated. A type-related independent alarm threshold is set for each type of sensor node, where the alarm threshold for temperature data is a preset upper temperature limit, the alarm threshold for smoke concentration data is a preset lower concentration limit, and the alarm threshold for carbon monoxide concentration data is a preset lower gas concentration limit. In each acquisition cycle, the sensor node compares its output temperature data, smoke concentration data, or carbon monoxide concentration data with its corresponding independent alarm threshold. When it is determined that any type of real-time data exceeds its independent alarm threshold, the sensor node that generated the alarm immediately sends a disaster recovery mode activation broadcast frame containing its own node identifier and alarm type to the entire network through the VLAN within the tunnel. Upon receiving the disaster recovery mode activation broadcast frame, the mesh network router in the VLAN within the tunnel switches to a preset high-power, high-throughput communication configuration and commands all its subordinate sensor nodes to switch to the highest sampling frequency, thereby globally activating the disaster recovery mode.

[0082] In disaster-prone operation mode, all working sensor nodes within the tunnel's self-organizing local area network synchronously collect fire hazard parameters at the highest sampling frequency, forming a dense spatiotemporal sampling data stream. The fire source location module inputs this dense spatiotemporal sampling data stream into an improved weighted centroid location algorithm. This algorithm makes a preliminary estimate of the fire source location based on the signal strength characteristics of multiple sensor nodes and the spatiotemporal gradient of the fire hazard parameters, outputting the initial coordinates of the fire source. In disaster-prone operation mode, the system acquires the fire hazard parameters collected by all sensor nodes in the tunnel's self-organizing local area network at the current moment, as well as the signal strength indication of the communication link between each sensor node and its associated mesh network router. For temperature data, it calculates the temperature gradient vector field in the tunnel's three-dimensional space and identifies the spatial point with the largest magnitude in the temperature gradient vector field. For smoke concentration data, it calculates the concentration diffusion gradient on the plane formed by the tunnel's longitudinal and height directions and identifies the axis of fastest concentration diffusion. The signal strength indications reported by each sensor node are converted into distance weighting factors between the node and potential fire sources, where the lower the signal strength indication, the larger the corresponding distance weighting factor. By combining the spatial point with the largest magnitude in the temperature gradient vector field, the axis of the direction with the fastest concentration diffusion, and the distance weighting factors of all sensor nodes, the coordinates of the spatial point that minimizes the overall error are obtained by iteratively minimizing the weighted distance error function. These spatial point coordinates are the initial coordinates of the fire source output by the improved weighted centroid localization algorithm.

[0083] In practical implementation, the system sets type-related independent alarm thresholds for each type of sensor node. These thresholds are written to the sensor node's non-volatile memory via a configuration tool during system deployment. During each data acquisition cycle, the sensor node compares its output temperature, smoke concentration, or carbon monoxide concentration data with its stored independent alarm threshold. The alarm threshold for temperature data is a preset upper temperature limit, for smoke concentration data it's a preset lower concentration limit, and for carbon monoxide concentration data it's a preset lower gas concentration limit. Table 1 illustrates one possible independent alarm threshold setting. When any real-time data exceeds its independent alarm threshold, the sensor node generating the alarm immediately sends a disaster mode activation broadcast frame containing its node identifier and alarm type to the entire network via the tunnel's self-organizing local area network. This disaster mode activation broadcast frame uses a specific broadcast address and frame control field to ensure it is received by all mesh network routers.

[0084] In some embodiments, upon receiving a disaster mode activation broadcast frame, the mesh network router in the tunnel's self-organizing local area network switches to a preset high-power, high-throughput communication configuration. This high-power, high-throughput communication configuration includes increasing wireless transmission power, switching to a higher-order modulation and coding scheme, and shortening the wireless channel contention interval. Simultaneously, the mesh network router sends a configuration command containing the highest sampling frequency parameter to all its subordinate sensor nodes. In a specific implementation, after receiving the configuration command from its assigned mesh network router, the sensor node adjusts its own sampling frequency to the highest sampling frequency supported by the hardware. All operating sensor nodes in the tunnel's self-organizing local area network, based on a unified network time slot synchronization mechanism, synchronously collect fire hazard parameters at the highest sampling frequency, forming a dense spatiotemporal sampling data stream. It can be understood that type-related independent alarm thresholds allow for setting different alert levels for different physical quantities, the disaster mode activation broadcast frame triggers a switch in the entire network's operating mode, and the synchronous acquisition at the highest sampling frequency obtains high-resolution data on the fire development process.

[0085] Table 1: Independent Alarm Thresholds for Sensor Nodes

[0086] In practical implementation, the fire source location module operates in disaster-time mode, acquiring fire hazard parameters collected by all sensor nodes in the tunnel's self-organizing local area network at the current moment, as well as the signal strength indication of the communication link between each sensor node and its associated mesh network router. For temperature data, it calculates the temperature gradient vector field in the tunnel's three-dimensional space. This temperature gradient vector field is generated based on the temperature data from discrete sensor nodes using spatial interpolation methods, identifying the spatial point with the largest magnitude in the temperature gradient vector field, which represents the center of the most drastic temperature change. Optionally, for smoke concentration data, it calculates the concentration diffusion gradient on the plane formed by the tunnel's longitudinal and height directions. The concentration diffusion gradient is approximated by calculating the difference in smoke concentration data between adjacent sensor nodes, identifying the axis of fastest concentration diffusion, which is determined by the gradient direction. In some embodiments, the signal strength indication reported by each sensor node is converted into a distance weighting factor between the node and the potential fire source. The distance weighting factor is negatively correlated with the signal strength indication; that is, the lower the signal strength indication, the larger the corresponding distance weighting factor. The conversion formula is:

[0087]

[0088] in: This represents the distance weighting factor for the i-th sensor node. This represents the absolute value of the signal strength indication reported by the i-th sensor node. A constant offset is used to avoid the denominator being zero. In specific implementation, the coordinates of the spatial point with the largest magnitude in the temperature gradient vector field, the direction axis of the fastest concentration diffusion, and the distance weighting factors of all sensor nodes are combined. The coordinates of the spatial point with the smallest comprehensive error are solved by iteratively minimizing the weighted distance error function. The weighted distance error function comprehensively considers the weighted distance deviation from the estimated position to each reference point (the geometric point constrained by gradient and direction information).

[0089] Optionally, the iterative minimization process employs gradient descent, adjusting the estimated spatial point coordinates in each iteration until the weighted distance error function is less than a preset convergence threshold or the maximum number of iterations is reached. The final output spatial point coordinates are the initial coordinates of the fire source output by the improved weighted centroid localization algorithm. It can be understood that signal strength reflects the link quality between the node and the router, indirectly related to environmental interference and attenuation. The distance weighting factor incorporates this information, while temperature gradient and smoke concentration gradient provide direct physical evidence of the fire source's influence range. The improved weighted centroid localization algorithm integrates wireless signal characteristics and physical field characteristics for location estimation.

[0090] In one embodiment of the invention, based on the initial coordinates of the fire source, a data aggregation cluster with an adaptive communication radius is dynamically constructed within the self-organizing local area network (LAN) inside the tunnel. Using the projection of the initial fire source coordinates longitudinally into the tunnel as a reference, the mesh network router closest to the projection location is selected as the cluster head node of the data aggregation cluster. Based on the maximum value of the temperature and smoke concentration data reported by all sensor nodes at the current moment, a preset communication radius mapping table is consulted to determine the initial communication radius of the data aggregation cluster. With the cluster head node as the center and the initial communication radius as the boundary, a geographically circular region is delineated within the self-organizing LAN inside the tunnel, and all mesh network routers and sensor nodes located within this geographically circular region are incorporated into the data aggregation cluster. Sensor nodes incorporated into the data aggregation cluster directly send their collected dense spatiotemporal sampling data streams to the cluster head node, without forwarding them through mesh network routers outside the data aggregation cluster.

[0091] The cluster head node receives dense spatiotemporal sampling data streams from all sensor nodes within the data aggregation cluster. Each data stream consists of time-stamped data packets. Based on the time stamps, the cluster head node performs time synchronization and sorting of all received data packets, aligning temperature, smoke concentration, and carbon monoxide concentration data within the same millisecond time window into a fused data frame. Spatial interpolation and confidence-weighted averaging are performed on the multi-sensor data within each fused data frame to generate temperature, smoke concentration, and carbon monoxide concentration values ​​at uniform grid points within the tunnel space corresponding to the fused data frame. The grid data obtained from processing multiple consecutive fused data frames are packaged in chronological order, along with the initial coordinates of the fire source, the data aggregation cluster identifier, and the start and end times of data acquisition, encapsulating this data to generate a tunnel fire fused data packet.

[0092] In practical implementation, the construction of the data aggregation cluster starts from the initial coordinates of the fire source and uses the projection position of the initial coordinates of the fire source in the longitudinal direction of the tunnel as a reference. The mesh network router located closest to the projection position is selected as the cluster head node of the data aggregation cluster. The selection process is completed by comparing the geometric distance between the known position coordinates of all mesh network routers in the tunnel and the projection position. In some embodiments, based on the maximum value of the temperature data and smoke concentration data reported by all sensor nodes at the current moment, a preset communication radius mapping table is queried to determine the initial communication radius of the data aggregation cluster. The preset communication radius mapping table is stored in the memory of the cluster head node.

[0093] Optionally, a geographically circular region is defined within the self-organizing local area network (LAN) inside the tunnel, centered on the cluster head node and bounded by the initial communication radius. This geographically circular region is determined by calculating the Euclidean distance between the cluster head node and all other nodes in the network. All mesh network routers and sensor nodes located within this geographically circular region are incorporated into the data aggregation cluster. The inclusion operation is completed by the cluster head node sending a cluster membership invitation frame and receiving an acknowledgment frame. In specific implementations, sensor nodes incorporated into the data aggregation cluster directly send their collected dense spatiotemporal sampling data streams to the cluster head node, without forwarding them through mesh network routers outside the data aggregation cluster. The dense spatiotemporal sampling data streams are directly addressed to the media access control address of the cluster head node using unicast addresses. It can be understood that dynamically constructing the data aggregation cluster based on the initial coordinates of the fire source concentrates communication and computing resources in the fire-related area. Querying the communication radius based on the maximum values ​​of temperature and smoke concentration data achieves preliminary adaptation to the fire's impact range. The geographically circular region simplifies the cluster membership determination logic (see Table 2).

[0094] Table 2: Communication Radius Mapping Table

[0095] The cluster head node receives dense spatiotemporal sampling data streams from all sensor nodes within the cluster. Each data stream consists of time-stamped data packets, with the timestamps written into the packet headers by the sensor nodes before transmission according to the network time slot synchronization mechanism of the self-organizing local area network within the tunnel. In some embodiments, the cluster head node performs time synchronization and sorting of all received data packets based on the timestamps, aligning temperature, smoke concentration, and carbon monoxide concentration data within the same millisecond time window into a fused data frame. The boundaries of the time window are defined by the local clock of the cluster head node. In a specific implementation, spatial interpolation and confidence-weighted averaging are performed on the multi-sensor data within each fused data frame. Spatial interpolation uses an inverse distance weighting method. The weight of each sensor data point in the confidence-weighted averaging is pre-set based on the sensor type, historical reliability, and relative distance to the interpolation point, generating temperature, smoke concentration, and carbon monoxide concentration values ​​at uniform grid points within the tunnel space corresponding to the fused data frame. Optionally, the contribution weight of each sensor data point to the grid point interpolation result in the confidence-weighted averaging is... Calculated by the formula:

[0096]

[0097] in: This represents the contribution weight of the j-th sensor data point to the current interpolated grid point. This represents the preset confidence coefficient corresponding to the j-th sensor type. This represents the Euclidean distance from the spatial location of the j-th sensor to the current interpolated grid point. The reference distance constant preset by the system, This represents the distance attenuation coefficient constant. It can be understood that time synchronization and sorting based on time stamps ensures the time alignment of data from different sensors. Spatial interpolation and confidence-weighted averaging fuse discrete point data into spatially continuous gridded data, facilitating subsequent analysis and display. In specific implementation, the gridded data obtained from processing multiple consecutive fused data frames are packaged in chronological order, and the initial coordinates of the fire source, data aggregation cluster identifier, and data acquisition start and end times are appended to generate a tunnel fire fusion data packet. This tunnel fire fusion data packet has a fixed header structure for storing metadata.

[0098] In one embodiment of the invention, tunnel fire fusion data packets are transmitted across regions to a remote early warning platform outside the tunnel via communication relay modules deployed at both ends of the tunnel. One communication relay module is deployed outside the tunnel entrance and exit, each module comprising a long-range wireless communication unit and a high-gain directional antenna. The cluster head node of the self-organizing local area network within the tunnel simultaneously sends the tunnel fire fusion data packets to the nearest mesh network router at both the tunnel entrance and exit. The mesh network routers at the tunnel entrance and exit forward the received tunnel fire fusion data packets to the corresponding communication relay modules via wired or short-range wireless means. The communication relay modules at the tunnel entrance and exit modulate the tunnel fire fusion data packets to different licensed frequency bands and transmit them to the remote early warning platform point-to-point via the high-gain directional antenna.

[0099] The communication relay module establishes a communication link with the remote early warning platform using a hybrid multiple access method combining time-division duplex (TDD) and frequency-division multiplexing (FDM). The remote early warning platform periodically broadcasts downlink synchronization beacons on multiple different frequencies. The communication relay module scans these frequencies and locks onto the downlink synchronization beacon with the best signal quality, thus determining the initial operating frequency and uplink time slot allocation for communication with the remote early warning platform. During data transmission, the remote early warning platform and the communication relay module alternately transmit and receive on the same frequency using TDD. The remote early warning platform sends control commands in the downlink time slot, while the communication relay module sends tunnel fire fusion data packets in its allocated uplink time slot. When the volume of the tunnel fire fusion data packets exceeds the capacity of a single uplink time slot, the remote early warning platform dynamically allocates additional frequencies to the corresponding communication relay module. The communication relay module then transmits data in parallel on both the initial operating frequency and the additionally allocated frequencies, achieving frequency-division multiplexing.

[0100] The remote early warning platform receives and parses the tunnel fire fusion data packet, extracting the initial coordinates of the fire source and fire hazard parameters for activating the fire emergency plan. The platform deduplicates and merges the tunnel fire fusion data packets received from different communication relay modules to reconstruct the complete packet. It parses the packet header to extract the initial coordinates of the fire source, the data aggregation cluster identifier, and the start and end times of data acquisition. It then parses the payload of the fusion data packet, reading the fusion data frames arranged chronologically. Each fusion data frame contains temperature, smoke concentration, and carbon monoxide concentration values ​​at points on the tunnel's spatial grid. The extracted initial fire source coordinates and the chronologically evolving fusion data frames are stored in the early warning platform's database, and the platform automatically triggers the fire emergency plan activation process according to preset rules.

[0101] In implementation, a communication relay module is deployed at both the tunnel entrance and exit. These modules are housed in waterproof enclosures and mounted on dedicated pillars. Each module includes a long-range wireless communication unit and a high-gain directional antenna, with the antenna pointing towards the remote early warning platform. The head node of the self-organizing local area network within the tunnel simultaneously sends the tunnel fire fusion data packets to the nearest mesh network routers at both the tunnel entrance and exit, using unicast transmission with acknowledgment. The mesh network routers at the tunnel entrance and exit forward the received tunnel fire fusion data packets to the corresponding communication relay modules via wired or short-range wireless methods. Wired methods use Ethernet cables, while short-range wireless methods use point-to-point microwave links. In practice, the communication relay modules at the tunnel entrance and exit modulate the tunnel fire fusion data packets to different licensed frequency bands and transmit them to the remote early warning platform point-to-point via the high-gain directional antennas. These licensed frequency bands are pre-allocated by the spectrum management department to avoid co-channel interference. It is understandable that deploying communication relay modules at both ends of the tunnel provides transmission path redundancy, high-gain directional antennas enhance the uplink budget, and modulation to different licensed frequency bands avoids mutual interference between uplink signals at both ends of the tunnel.

[0102] The communication relay module establishes a communication link with the remote early warning platform using a hybrid multiple access method combining time-division duplex (TDD) and frequency-division multiplexing (FDM). In specific implementations, the remote early warning platform periodically broadcasts downlink synchronization beacons on multiple different frequency points. These downlink synchronization beacons contain network identifiers, frame numbers, and uplink time slot allocation mapping information. The communication relay module scans multiple different frequency points; the scanning process is controlled by the baseband processor within the communication relay module, which controls the radio frequency front-end to lock onto the downlink synchronization beacon with the best signal quality. This determines the initial operating frequency point and uplink time slot allocation for communication with the remote early warning platform. Signal quality is comprehensively evaluated based on the received signal strength indication and bit error rate of the downlink synchronization beacon. In some embodiments, during the data transmission phase, the remote early warning platform and the communication relay module alternately transmit and receive on the same frequency point using TDD. The uplink and downlink time slots in TDD are uniformly scheduled by the remote early warning platform through the downlink control channel. The remote early warning platform sends control commands in the downlink time slots, while the communication relay module sends tunnel fire fusion data packets in the allocated uplink time slots. Optionally, when the data volume of the tunnel fire fusion data packet exceeds the capacity of a single uplink time slot, the remote early warning platform dynamically allocates additional frequency points to the corresponding communication relay module. The remote early warning platform sends a frequency reconfiguration command through the downlink control channel. The communication relay module simultaneously transmits data on both the initial operating frequency point and the additionally allocated frequency point, achieving frequency division multiplexing. The data packets transmitted in parallel need to be appended with the same sequence number so that the remote early warning platform can reassemble them. In specific implementation, the total data transmission rate of a single communication relay module in frequency division multiplexing mode is... It can be represented as:

[0103]

[0104] in: This indicates the total data transmission rate of the communication relay module in frequency division multiplexing mode. This indicates the total number of frequency points dynamically allocated to this communication relay module by the remote early warning platform. This represents the channel bandwidth of the nth allocated frequency point. This represents the signal-to-noise ratio (SNR) of the communication relay module at the nth frequency. It can be understood that time-division duplexing provides a flexible uplink / downlink bandwidth allocation, while frequency-division multiplexing enables a single communication relay module to perform parallel transmission across multiple channels, thereby improving data throughput.

[0105] The remote early warning platform receives and parses the tunnel fire fusion data packet, extracting the initial coordinates of the fire source and fire hazard parameters for activating the fire emergency plan. In specific implementation, the remote early warning platform deduplicates and merges the tunnel fire fusion data packets received from different communication relay modules. Deduplication and merging are based on the same data aggregation cluster identifier, data acquisition start and end times, and packet sequence number carried in the tunnel fire fusion data packet header, restoring the complete tunnel fire fusion data packet. Optionally, the encapsulation header of the tunnel fire fusion data packet is parsed to extract the initial coordinates of the fire source, the data aggregation cluster identifier, and the data acquisition start and end times. The format of the encapsulation header is predefined. In some embodiments, the payload of the tunnel fire fusion data packet is parsed to read fusion data frames arranged in chronological order. Each fusion data frame contains temperature values, smoke concentration values, and carbon monoxide concentration values ​​at tunnel spatial grid points. The arrangement order of the fusion data frames is consistent with the chronological order of data acquisition. In practice, the extracted initial coordinates of the fire source and the fused data frames evolving over time are stored in the early warning platform database. This database uses a time-series database structure and automatically triggers the fire emergency response plan based on preset rules. These rules include ensuring that the temperature value at the initial coordinates of the fire source in a critical area of ​​the tunnel or at a grid point consistently exceeds a threshold. Essentially, deduplication and merging of data packets from different paths ensures data integrity, while parsing and encapsulating the header and payload reveals core information about the fire situation. This information is then stored in the database, and the rule-based triggering of the emergency response plan enables automated emergency response.

[0106] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A tunnel fire linkage communication transmission system, characterized in that, include: The data acquisition module deploys a self-organizing local area network within the tunnel based on a wireless mesh network, and collects fire hazard parameters in the tunnel in real time through multiple sensor nodes distributed throughout the tunnel. The network activation module automatically activates the disaster recovery mode of the self-organizing local area network in the tunnel when the real-time data collected by any sensor node exceeds its preset alarm threshold. In disaster-time operation mode, all working sensor nodes in the self-organizing local area network inside the tunnel synchronously collect the fire hazard parameters at the highest sampling frequency, forming a dense spatiotemporal sampling data stream. The fire source location module inputs the dense spatiotemporal sampling data stream into the improved weighted centroid location algorithm. The improved weighted centroid location algorithm makes a preliminary estimate of the fire source location based on the signal strength characteristics of multiple sensor nodes and the spatiotemporal gradient of fire hazard parameters, and outputs the initial coordinates of the fire source. The data aggregation module dynamically constructs a data aggregation cluster with an adaptive communication radius centered on the initial coordinates of the fire source in the self-organizing local area network within the tunnel, based on the initial coordinates of the fire source. The module then performs time-scale alignment and data fusion of the dense spatiotemporal sampled data stream within the data aggregation cluster to generate a tunnel fire fusion data packet. The cross-domain transmission module transmits tunnel fire fusion data packets across regions to a remote early warning platform outside the tunnel via communication relay modules deployed at both ends of the tunnel. The improved weighted centroid localization algorithm performs a preliminary estimation of the fire source location based on the signal strength characteristics of multiple sensor nodes and the spatiotemporal gradient of fire hazard parameters, and outputs the initial coordinates of the fire source, including: In disaster response mode, the system acquires the fire hazard parameters collected by all sensor nodes in the self-organizing local area network within the tunnel at the current moment, as well as the signal strength indication of the communication link between each sensor node and its associated mesh network router. For temperature data, calculate its temperature gradient vector field in the three-dimensional space of the tunnel, and identify the spatial point with the largest magnitude in the temperature gradient vector field. For smoke concentration data, calculate its concentration diffusion gradient on the plane formed by the longitudinal and vertical directions of the tunnel, and identify the axis of the direction with the fastest concentration diffusion. The signal strength indication reported by each sensor node is converted into a distance weighting factor between the node and the potential fire source. The lower the signal strength indication, the larger the corresponding distance weighting factor. By combining the spatial point with the largest magnitude in the temperature gradient vector field, the axis of the direction with the fastest concentration diffusion, and the distance weighting factors of all sensor nodes, the coordinates of the spatial point that minimizes the overall error are obtained by iteratively minimizing the weighted distance error function. The coordinates of the spatial point are the initial coordinates of the fire source output by the improved weighted centroid localization algorithm.

2. The tunnel fire linkage communication transmission system according to claim 1, characterized in that, The deployment of a self-organizing local area network within the tunnel based on a wireless mesh network includes: Multiple full-function mesh network routers are deployed at equal intervals along the longitudinal direction of the tunnel. Each mesh network router has at least three non-coplanar directional antennas, which are directed toward both ends of the tunnel longitudinally and the top of the tunnel, respectively. Establish at least two redundant wireless communication links between adjacent mesh network routers to form a mesh network backbone covering the entire tunnel. Based on the mesh network backbone, multiple sensor node clusters are connected in a star topology. Each sensor node cluster contains multiple sensor nodes that collect different fire hazard parameters. Each sensor node establishes a subordinate connection with its nearest mesh network router. Configure a unified network time slot synchronization mechanism for the self-organizing local area network throughout the tunnel to ensure that the clocks of all mesh network routers and sensor nodes are synchronized within the microsecond error range.

3. The tunnel fire linkage communication transmission system according to claim 1, characterized in that, The method of collecting fire hazard parameters in the tunnel in real time through multiple sensor nodes distributed throughout the tunnel includes: The fire hazard parameters include temperature data, smoke concentration data, and carbon monoxide concentration data. Temperature and humidity composite sensors are installed at multiple height locations at the top, side walls, and bottom of the tunnel to collect temperature data at different spatial levels; A laser scattering smoke sensor is installed in the arched area at the top of the tunnel to collect smoke concentration data that reflects the concentration of smoke particles. An electrochemical carbon monoxide sensor is installed on the sidewall at a predetermined height above the tunnel surface to collect carbon monoxide concentration data. Control all temperature and humidity composite sensors, laser scattering smoke sensors, and electrochemical carbon monoxide sensors to perform cyclic sampling at a preset basic sampling period. Each sampling includes the measurement values ​​of multiple consecutive sampling points, and the arithmetic mean of these values ​​is taken as the temperature data, smoke concentration data, or carbon monoxide concentration data output for the corresponding period.

4. The tunnel fire linkage communication transmission system according to claim 1, characterized in that, When the real-time data collected by any sensor node exceeds its preset alarm threshold, the disaster recovery mode of the self-organizing local area network within the tunnel is automatically activated, including: Set type-related independent alarm thresholds for each type of sensor node, where the alarm threshold for temperature data is a preset upper temperature limit, the alarm threshold for smoke concentration data is a preset lower concentration limit, and the alarm threshold for carbon monoxide concentration data is a preset lower gas concentration limit. In each acquisition cycle, the sensor node compares its output temperature data, smoke concentration data, or carbon monoxide concentration data with its corresponding independent alarm threshold. When any real-time data exceeds its independent alarm threshold, the sensor node that generates the alarm immediately sends a disaster mode activation broadcast frame containing its own node identifier and alarm type to the entire network through the self-organizing local area network in the tunnel. Upon receiving the disaster mode activation broadcast frame, the mesh network router in the self-organizing local area network inside the tunnel switches to a preset high-power, high-throughput communication configuration and commands all its subordinate sensor nodes to switch to the highest sampling frequency, thereby globally activating the disaster working mode.

5. A tunnel fire linkage communication transmission system according to claim 1, characterized in that, Based on the initial coordinates of the fire source, a data aggregation cluster with an adaptive communication radius, centered on the initial coordinates of the fire source, is dynamically constructed in the self-organizing local area network within the tunnel, including: Based on the projection of the initial coordinates of the fire source onto the longitudinal direction of the tunnel, the mesh network router located closest to the projection position is selected as the cluster head node of the data aggregation cluster; Based on the maximum value of temperature data and smoke concentration data reported by all sensor nodes at the current moment, query the preset communication radius mapping table to determine the initial communication radius of the data aggregation cluster; Centered on the cluster head node and bounded by the initial communication radius, a geographical circular area is defined in the self-organizing local area network within the tunnel. All mesh network routers and sensor nodes located within the geographical circular area are incorporated into the data aggregation cluster. Sensor nodes included in the data aggregation cluster send their dense spatiotemporal sampling data streams directly to the cluster head node, instead of forwarding them in the mesh network routers outside the data aggregation cluster.

6. The tunnel fire linkage communication transmission system according to claim 1, characterized in that, The dense spatiotemporal sampled data stream is time-stamped and fused within a data aggregation cluster to generate a tunnel fire fusion data packet, including: The cluster head node receives and aggregates dense spatiotemporal sampled data streams sent by all sensor nodes within the cluster. Each data stream consists of time-stamped data packets. The cluster head node performs time synchronization sorting on all received data packets based on the timestamp, and aligns the temperature data, smoke concentration data and carbon monoxide concentration data within the same millisecond time window into a fused data frame; Spatial interpolation and confidence-weighted averaging are performed on the multi-sensor data in each fused data frame to generate temperature, smoke concentration and carbon monoxide concentration values ​​at uniform grid points in the tunnel space corresponding to the fused data frame. The grid data obtained from processing multiple consecutive fused data frames are packaged in chronological order, and the initial coordinates of the fire source, the data aggregation cluster identifier, and the start and end times of data acquisition are attached to generate a tunnel fire fused data package.

7. A tunnel fire linkage communication transmission system according to claim 1, characterized in that, The method of transmitting tunnel fire fusion data packets across regions to a remote early warning platform outside the tunnel via communication relay modules deployed at both ends of the tunnel includes: A communication relay module is deployed outside the tunnel entrance and exit, and each communication relay module contains a long-range wireless communication unit and a high-gain directional antenna; The cluster head node of the self-organizing local area network inside the tunnel simultaneously sends the tunnel fire fusion data packet to the nearest mesh network router at both the tunnel entrance and the tunnel exit. The mesh network routers at the tunnel entrance and tunnel exit forward the received tunnel fire fusion data packets to the corresponding communication relay modules via wired or short-range wireless means. The communication relay modules at the tunnel entrance and exit modulate the tunnel fire fusion data packets onto different licensed frequency bands and transmit them to the remote early warning platform in a point-to-point manner via high-gain directional antennas.

8. A tunnel fire linkage communication transmission system according to claim 7, characterized in that, Also includes: The link control module, wherein the communication relay module establishes a communication link with the remote early warning platform using a hybrid multiple access method that combines time division duplex and frequency division multiplexing; The early warning and analysis module allows the remote early warning platform to receive and analyze the tunnel fire fusion data packet, extract the initial coordinates of the fire source and fire hazard parameters, and use them to activate the fire emergency plan. The communication relay module establishes a communication link with the remote early warning platform using a hybrid multiple access method combining time division duplex and frequency division multiplexing, including: The remote early warning platform periodically broadcasts downlink synchronization beacons on multiple different frequencies; The communication relay module scans multiple different frequency points and locks onto the downlink synchronization beacon with the best signal quality, thereby determining the initial operating frequency point and uplink time slot allocation for communication with the remote early warning platform; During the data transmission phase, the remote early warning platform and the communication relay module alternately transmit and receive data in time-division duplex mode on the same frequency. The remote early warning platform transmits control commands in the downlink time slot, while the communication relay module transmits tunnel fire fusion data packets in the allocated uplink time slot. When the data volume of the tunnel fire fusion data packet exceeds the capacity of a single uplink time slot, the remote early warning platform dynamically allocates additional frequency points to the corresponding communication relay module. The communication relay module simultaneously transmits data in parallel on the initial working frequency point and the additionally allocated frequency points, realizing frequency division multiplexing.

9. A tunnel fire linkage communication transmission system according to claim 1, characterized in that, The remote early warning platform receives and parses the tunnel fire fusion data packet, extracts the initial coordinates of the fire source and fire hazard parameters, and uses them to activate the fire emergency plan, including: The remote early warning platform deduplicatizes and merges tunnel fire fusion data packets received from different communication relay modules to restore the complete tunnel fire fusion data packets. The encapsulation header of the tunnel fire fusion data packet is analyzed to extract the initial coordinates of the fire source, the data aggregation cluster identifier, and the start and end times of data acquisition. Parse the payload of the tunnel fire fusion data packet and read the fusion data frames arranged in chronological order. Each fusion data frame contains the temperature value, smoke concentration value and carbon monoxide concentration value at the tunnel spatial grid points. The extracted initial coordinates of the fire source and the fused data frame that evolves over time are stored in the early warning platform database, and the fire emergency plan is automatically triggered according to preset rules.

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