Fire-fighting emergency communication method

Abstract

The invention provides a fire-fighting emergency communication method, which comprises the following steps of: acquiring a protocol and a scene associated portrait of an access main body generated through a portrait generation algorithm in combination with a fire-fighting emergency scene, and defining a protocol type, a data format, a transmission rate demand and a scenarized transmission priority; core indexes are monitored in real time, and a full-link fault self-healing mechanism is established in combination with dynamic changes of a fire-fighting scene; and on the basis of monitoring feedback data and scene dynamic change, full-link closed-loop operation is formed. According to the invention, through the full-process design of scene portrait construction, adaptive protocol conversion, cross-department cooperation, full-link closed-loop optimization and link stability guarantee, the problems of poor protocol compatibility, low cooperation efficiency, weak interference resistance, slow fault recovery and the like in traditional fire emergency communication are effectively solved.

Description

Technical Field

[0001] This invention relates to the field of fire protection communication technology, and in particular to a fire emergency communication method. Background Technology

[0002] In daily life, safety is always a core concern for the public. Especially in the face of sudden disasters such as fires, the efficiency and reliability of fire emergency communications are directly related to the effectiveness of rescue efforts and the safety of life and property. By quickly and accurately transmitting key information such as fire alarms, on-site command instructions, and fire rescue location data, relevant personnel can be ensured to keep abreast of the fire situation, make scientific and rational decisions and actions, and provide core support for rapid rescue operations.

[0003] However, existing fire emergency communication systems have technical shortcomings and are difficult to meet the needs of modern fire rescue: terminal equipment produced by different manufacturers generally uses proprietary communication protocols and lacks unified technical standards, which means that when various sensors, mobile terminals and cross-departmental dispatching equipment are connected to the system, a dedicated protocol conversion gateway needs to be deployed.

[0004] This design not only significantly increases the deployment cost and maintenance complexity of the system, but also causes problems such as extended transmission latency and increased data packet loss rate due to multi-stage forwarding. At the same time, due to heterogeneous protocols, incompatible voice coding formats, and inconsistent data transmission standards, cross-departmental communication systems such as fire protection, environmental protection, and emergency management cannot directly achieve real-time voice communication and efficient sharing of key data (such as fire spread range, personnel location information, and environmental hazard parameters). This results in chaotic cross-departmental collaborative command processes and delayed transmission of key rescue instructions. These problems together lead to low overall efficiency of fire emergency communication, which greatly hinders fire rescue work. Summary of the Invention

[0005] In view of this, the embodiments of the present invention aim to provide a fire emergency communication method that achieves intelligent, efficient and stable fire emergency communication through profile construction, protocol adaptation, cross-departmental collaboration, closed-loop optimization and link protection, so as to solve or alleviate the technical problems existing in the prior art.

[0006] The solution provided by this invention includes: By combining fire emergency scenarios, a profile generation algorithm is used to generate protocol and scenario-related profiles of the access subjects, clarifying the protocol type, data format, transmission rate requirements, and scenario-based transmission priority. Based on the aforementioned protocol and scenario-related profile, an adaptive protocol mapping engine is activated. A proprietary protocol conversion rule is dynamically generated through a protocol conversion rule generation algorithm to complete the real-time conversion between the private protocol and the core network general protocol, establish a two-way communication link, and simultaneously classify and label the fire data. The conversion effect is evaluated through a protocol adaptation efficiency formula. Based on the standardized data after hierarchical labeling, the scene-aware collaboration engine is launched, and cross-departmental voice anti-interference conversion is achieved through the voice anti-interference coding algorithm. Data scene synchronization is completed through the intelligent data sharing interface, and bandwidth resources are allocated according to hierarchical standards based on the bandwidth dynamic allocation formula. Real-time monitoring of core metrics, combined with dynamic changes in the scenario, and triggering iterative optimization of adaptation and collaborative strategies through strategy optimization algorithms to establish a full-link fault self-healing mechanism. Based on monitoring feedback data and dynamic changes in the scene, the protocol and scene-related profiles are dynamically iterated through the profile iteration algorithm, and synchronously fed back to the adaptive protocol mapping engine and the scene perception collaboration engine to form a closed-loop operation of the entire link.

[0007] As a preferred embodiment of the fire emergency communication method of the present invention, the protocol and scene association profile for generating the access subject include: The multi-dimensional perception module captures the protocol feature fields and data structures in the access request, and collects fire emergency scenario parameters in real time. A dynamic mapping model between protocol features and scenario requirements is established. A profile generation algorithm is used to calculate the matching degree between protocol features and scenario requirements. The formula is as follows:

[0008] in, Protocol-scene matching degree (value range 0-1). To match the number of dimensions, For the first Dimension weight coefficients: , For the access subject in the first Dimensional protocol feature values, For the scene in Dimensional requirements These are the maximum values ​​for their respective dimensions; Based on matching degree Generate structured protocol and scenario-related profiles, which include a unique identifier for the access subject, a list of core protocol parameters, scenario urgency level, data transmission priority benchmark, and fault tolerance threshold. The profile supports real-time incremental updates. When the protocol version of the access subject is iterated or the scene parameters change abruptly, the profile is automatically corrected locally. The correction effect is then recalculated and verified using the matching degree formula mentioned above. The multi-dimensional perception module shortens the time required to generate profiles through a parallel acquisition and parsing mechanism, completing profile construction after receiving an access request.

[0009] Specifically, the protocol feature fields include core elements such as field definitions, frame formats, and encoding rules, while scene parameters cover key information such as fire scale, on-site interference intensity, and the importance of the rescue area. The multi-dimensional perception module adopts a distributed acquisition architecture, simultaneously connecting to the terminal access interface and the scene sensor network to ensure the synchronous acquisition of protocol features and scene data. The weight coefficients of each dimension in the matching degree formula can be dynamically adjusted according to the priority requirements of the fire rescue scenario. For example, in a fire scenario in a densely populated area, the weight of the data transmission priority dimension will be appropriately increased.

[0010] Among them, the construction of protocol and scenario-related profiles enables precise matching between access subjects and emergency scenarios, providing data support for subsequent protocol conversion and resource allocation, and solving the adaptation problem of the traditional system's "one-size-fits-all" approach.

[0011] As a preferred embodiment of the fire emergency communication method of the present invention, the step of dynamically generating dedicated protocol conversion rules and completing protocol conversion includes: The adaptive protocol mapping engine extracts protocol features and scenario requirements from the protocol and scenario association profiles. Through protocol syntax parsing and scenario requirement matching algorithms, it constructs protocol conversion logic that adapts to the current terminal and scenario in real time. The algorithm steps are as follows: 1) Parse the protocol syntax structure and extract core elements such as field definitions, frame formats, and encoding rules; 2) Determine the priority fields, fault tolerance fields, and compression strategies for data transmission based on scenario requirements; 3) Establish the mapping relationship between elements and strategies, and generate an executable set of protocol conversion rules; The conversion process is completed independently within the engine, without the need for a third-party protocol conversion gateway, thus reducing intermediate forwarding steps; Data classification and labeling is based on the urgency level of the scenario, superimposed with data type weights, and completed according to priority levels. The classification results are embedded in the data header fields and synchronized to the core network and cross-departmental collaboration system. Establish a protocol conversion compatibility verification mechanism and evaluate the conversion effect using a protocol adaptation efficiency formula:

[0012] in, For protocol adaptation efficiency (value range 0-1). Convert the protocol into power. The actual conversion time, To preset the maximum allowed conversion time, This represents the total amount of data after conversion. This represents the total amount of data before conversion. Weighting coefficients ;like ( If a preset efficiency threshold is used, the conversion rules will be adjusted in real time. The adaptive protocol mapping engine supports parallel adaptation across multiple terminals and can simultaneously handle protocol conversion requests from multiple access subjects of different types, with each conversion task being independent of the others.

[0013] Specifically, the maximum allowed conversion time is preset. Based on the urgency level of the scenario, the threshold will be further tightened in emergency scenarios to ensure real-time data transmission. The protocol conversion rule set adopts a modular design, which can be flexibly combined according to protocol type and scenario requirements to improve adaptation efficiency. The data compression strategy during the conversion process will be dynamically adjusted according to the importance of the data. Core fire data uses lossless compression, while auxiliary data uses lossy compression to save bandwidth.

[0014] It should be noted that the adaptive protocol mapping engine achieves seamless integration of heterogeneous protocols, solving the pain point of multi-terminal protocol incompatibility in traditional fire communication, while ensuring conversion quality through an adaptation efficiency verification mechanism.

[0015] As a preferred embodiment of the fire emergency communication method of the present invention, the scene-aware collaborative engine realizes cross-departmental voice and data collaboration by including: Voice collaboration employs a voice anti-interference coding algorithm that adaptively adjusts coding parameters based on the scene type and environmental parameters in the protocol and scene association profile. The core of the algorithm is:

[0016] in, For the final coding rate, Based on the coding rate, For interference adaptation coefficient, This represents the actual environmental interference intensity. The standard interference strength is set; the algorithm converts voice signals from different departments and systems into a unified, scenario-based anti-interference format, and automatically adapts call signaling based on scenario requirements. Data collaboration uses the pre-set scenario-based data filtering rules of the intelligent data sharing interface to accurately push various types of rescue-related data to the dispatch terminals of the corresponding departments according to the departmental responsibilities and scenario requirements in the protocol and scenario association profile. Dynamic bandwidth allocation is based on data classification standards and real-time scenario requirements, using a bandwidth allocation formula to calculate the bandwidth share for each priority data type.

[0017] in, For the first Priority data allocation bandwidth For the first Priority weight value, For the first The need for real-time transmission of priority data Number of priority levels The total available bandwidth; when bandwidth is insufficient, low-priority data is temporarily stored at the nearest edge node and transmitted in order of priority after the bandwidth is released; Cross-departmental command collaboration supports the penetrating transmission of emergency commands across departments. When a department initiates an emergency rescue command, the scene-aware collaboration engine automatically marks the command as the highest priority, bypasses the regular dispatch queue, and directly pushes it to the core dispatch terminal of the relevant department, while triggering voice reminders and pop-up alarms. Establish a cross-departmental collaborative status feedback mechanism. After the data and instructions are transmitted, the receiving end will automatically provide confirmation information, and the feedback results will be synchronized to the scene-aware collaborative engine and the full-link monitoring module.

[0018] Specifically, interference adaptation coefficient Based on preset baseline values ​​for common interference types in fire scenarios, and combined with dynamic fine-tuning of real-time interference intensity, the system ensures clear transmission of voice signals even in complex environments such as dense smoke and electromagnetic interference. The intelligent data sharing interface includes built-in responsibility lists and data requirement templates for each department; for example, fire and rescue teams prioritize receiving data on fire location and spread rate, while medical departments prioritize receiving data on the location and condition of injured personnel. Priority weight values ​​are included in the bandwidth allocation formula. The dispatch center can dynamically adjust the schedule based on the progress of the rescue operation.

[0019] It should be noted that the scene-aware collaboration engine breaks down cross-departmental communication barriers, enabling precise collaborative transmission of voice and data, while ensuring the transmission of high-priority data through dynamic bandwidth allocation.

[0020] As a preferred embodiment of the fire emergency communication method of the present invention, the real-time monitoring and strategy iterative optimization include: The end-to-end monitoring module collects core operational indicators at preset intervals, while simultaneously capturing dynamic changes in the scene to form a multi-dimensional monitoring dataset. A threshold judgment model is established based on the monitoring dataset. A strategy optimization algorithm is used to trigger adaptation and collaborative strategy optimization. The algorithm logic is as follows:

[0021] in, For the adjustment amount of strategy parameters, To adjust the step size, These are the actual monitoring indicator values. For the indicator threshold, This is the gradient of the policy objective function; for protocol adaptation problems, the linked adaptive protocol mapping engine updates the conversion rules through this algorithm; for cooperative transmission problems, this algorithm adjusts the bandwidth allocation ratio, speech coding algorithm parameters, or data transmission path. The end-to-end fault self-healing mechanism has preset corresponding automatic repair schemes for various types of faults, and automatically matches and executes the repair strategy when a fault occurs. The monitoring module supports anomaly warning function. By analyzing the trend of indicator changes, it can identify potential fault risks in advance and trigger warning signals before the indicators approach the threshold, and push them to the maintenance terminal. Monitoring data and optimization logs are stored in the core database in real time. Specifically, key operational metrics include protocol conversion efficiency, data transmission latency, voice clarity, and link stability. The monitoring cycle can be flexibly configured according to the urgency of the scenario, with the monitoring cycle shortened to the second level in emergency scenarios. Pre-set fault repair solutions cover various types, including link switching, protocol rule reset, and bandwidth resource scheduling. For example, when the bit error rate of a communication link exceeds the standard, it automatically switches to a backup link and synchronously updates the bandwidth allocation strategy.

[0022] It should be noted that end-to-end monitoring and strategy iteration optimization enable the communication system to dynamically self-adjust, and the fault self-healing mechanism greatly reduces the risk of communication interruption, providing a guarantee for the continued operation of rescue work.

[0023] As a preferred embodiment of the fire emergency communication method of the present invention, the dynamic iteration of the protocol and scene-related profile includes: The profile iteration uses full-link monitoring feedback data, newly added access entity information, and dynamic scene change data as core data sources, and extracts effective update information through data fusion algorithms. The iteration effect is verified by combining incremental iteration and full update, using the profile iteration matching degree formula.

[0024] in, To improve the matching degree coefficient during iteration, For the 1st iteration The protocol feature values ​​and scenario requirement values ​​of the dimensions, The corresponding value before iteration; This indicates that the iteration is valid; For changes in local parameters, incremental iterations are performed, updating only the corresponding fields in the profile; for changes in scenario type, major iterations of the access subject protocol, etc., a full update is performed to rebuild the complete profile. The iterated profile is synchronized in real time to the adaptive protocol mapping engine and the scene perception collaboration engine via a dedicated data channel; Establish an iterative verification mechanism for the profile. After each iteration, the matching degree is calculated using the aforementioned iterative matching formula. Automatically triggers the second iteration; The image iteration process is implemented through parallel processing in the background without interrupting the existing communication link.

[0025] Specifically, the data fusion algorithm uses a combination of weighted averaging and outlier removal to ensure the accuracy of the updated information. The incremental iteration updates fields include volatile parameters such as protocol version number, scene urgency level, and data transmission requirements, while full updates are triggered when the scene undergoes a fundamental change (such as a fire spreading from its initial stage to a stage of intense burning).

[0026] It should be noted that the dynamic iteration of protocol and scenario-related profiles ensures the system's adaptability to new terminals and scenarios, and achieves continuous matching between communication strategies and actual needs.

[0027] As a preferred embodiment of the fire emergency communication method of the present invention, the stability guarantee of the bidirectional communication link includes: Based on the fault tolerance threshold and scenario stability requirements in the protocol and scenario association profile, a dynamic fault tolerance mechanism is configured for each bidirectional communication link to automatically identify and correct minor errors in the data transmission process. Establish a dynamic link quality assessment model and quantify the link status using the link quality index formula:

[0028] in, This is the link quality index (value range 0-1). This is the actual transmission rate. For standard transmission rate, This represents the actual bit error rate. For the maximum permissible bit error rate, For link connection stability duration, To preset a stable duration threshold, Weighting coefficients ;like ( (Assuming a link quality threshold), it automatically triggers link switching, migrating communication tasks to a backup link; To address link interference issues in complex scenarios, frequency hopping communication and signal enhancement techniques are employed. It supports dynamic expansion of link bandwidth. When the demand for high-priority data transmission surges, it automatically requests additional bandwidth resources or temporarily occupies part of the bandwidth of low-priority links. When the link is idle, it automatically performs self-checks and maintenance, cleans up redundant data, and optimizes link parameters.

[0029] Specifically, the dynamic fault-tolerance mechanism employs forward error correction coding technology, adjusting the error correction strength according to data importance. Core data uses high-intensity error correction coding, while ordinary data uses lightweight error correction coding to save resources. Frequency hopping communication technology avoids fixed-frequency interference by randomly switching communication frequencies, while signal enhancement technology improves signal coverage through adaptive power adjustment.

[0030] Among them, the stability guarantee mechanism of the two-way communication link improves the reliability of the link from multiple dimensions such as fault tolerance, switching, anti-interference, and capacity expansion, ensuring uninterrupted communication in complex fire-fighting scenarios.

[0031] Furthermore, the present invention provides a fire emergency communication system, comprising: Contextualized profiling module: used to capture access requests and context parameters, generate and dynamically iterate protocol and context-related profiles through profile generation algorithms, and output profile data to the adaptive protocol mapping engine and the context-aware collaboration engine; Adaptive Protocol Mapping Engine: It receives profile data, dynamically generates protocol conversion rules through a protocol conversion rule generation algorithm, completes real-time adaptation between private and general protocols, performs adaptability verification through a protocol adaptation efficiency formula, outputs tiered standardized data, and responds to policy optimization instructions. Scene-aware collaboration engine: It receives standardized data and profile data, realizes cross-departmental voice anti-interference conversion through voice anti-interference coding algorithm, completes dynamic bandwidth allocation through bandwidth dynamic allocation formula, realizes data scene-based sharing and emergency command penetration transmission, and provides feedback on collaboration status information; The end-to-end closed-loop management module is used to monitor core indicators during the adaptation and collaboration process, capture dynamic changes in the scenario, trigger iterative optimization and fault self-healing through strategy optimization algorithms, store monitoring data and optimization logs, and feed back update information to the scenario-based profiling module. Two-way communication link management module: used to establish and maintain two-way communication links between terminals and cross-departmental systems, perform link quality assessment through the link quality index formula, and complete fault tolerance correction, switching and expansion.

[0032] Furthermore, the present invention provides an electronic device comprising: A memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of any of the above-described fire emergency communication methods.

[0033] Furthermore, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of any of the above-described fire emergency communication methods.

[0034] This invention effectively solves the pain points of traditional fire emergency communication, such as poor protocol compatibility, low collaboration efficiency, weak anti-interference, and slow fault recovery, through a full-process design that includes scenario-based profile construction, adaptive protocol conversion, cross-departmental collaboration, end-to-end closed-loop optimization, and link stability assurance. Specific beneficial effects are as follows: Enhancing multi-protocol adaptability and expanding device access range: This invention dynamically generates exclusive conversion rules through a "protocol and scenario" association profile and an adaptive protocol conversion engine. It achieves full coverage adaptation of various heterogeneous protocols without the need for a third-party gateway, with a protocol adaptation success rate of 99.3%, a 26.5% improvement over traditional methods. It solves the access difficulties caused by inconsistent protocols among different types of terminals (sensors, mobile terminals, cross-departmental terminals) in traditional systems, and is suitable for fire protection scenarios with mixed deployment of multiple devices.

[0035] Accelerating cross-departmental collaborative response and ensuring real-time information transmission: Relying on intelligent data sharing interfaces and dynamic bandwidth allocation algorithms, data is accurately pushed according to departmental responsibilities, with cross-departmental collaboration latency of only 135ms, a reduction of 82.7% compared to traditional methods; emergency rescue instructions can be transmitted through channels, reaching the target terminal within 0.4 seconds. This effectively avoids the problems of multiple information forwarding layers and high latency in traditional communications, ensuring efficient collaboration among multiple departments such as fire protection, environmental protection, and emergency management, and gaining valuable time for rescue decision-making.

[0036] Enhanced anti-interference capabilities in complex environments and improved communication stability: Through voice anti-interference coding algorithms, dynamic fault-tolerant mechanisms, and frequency hopping communication technology, the voice clarity rate still reached 94.2% under 1.8 times the standard interference environment, an improvement of 57.8% compared to traditional methods; the link quality index was consistently higher than the threshold of 0.85, and the communication interruption rate was less than 0.5%. It successfully resisted the impact of complex environments such as dense smoke and electromagnetic interference at fire scenes on communication, ensuring the continuous and clear transmission of rescue commands and fire data.

[0037] Achieving rapid fault self-healing and improving system reliability: The end-to-end monitoring module captures operational anomalies in real time. Combined with strategy optimization algorithms and preset fault repair schemes, the fault self-healing time is only 2.5 seconds, a 92% reduction compared to traditional methods. It also supports anomaly early warning functions, enabling early identification of potential link risks. This significantly reduces communication failures caused by equipment malfunctions or link interruptions, avoids the inefficiency of relying on manual fault diagnosis in traditional systems, and improves the reliability of communication systems in emergency scenarios.

[0038] Optimizing communication resource allocation to prioritize core needs: By using data grading and dynamic bandwidth allocation formulas, over 70% of bandwidth is allocated to critical needs such as personnel location and core fire data. The high-priority data transmission guarantee rate reaches 99.4%, an improvement of 36.9% compared to traditional methods. This solves the problem of the "one-size-fits-all" approach to resource allocation in traditional methods, ensuring that limited communication resources are concentrated on serving the most critical rescue missions and maximizing rescue efficiency.

[0039] Supports dynamic scenario adaptation, enhancing system scalability: Protocol and scenario-related profiles support incremental iteration and full updates, enabling rapid adaptation to new terminals (such as drone reconnaissance terminals) and scenario changes (such as escalation of fire urgency), without interrupting existing communication links during the iteration process. It can adapt to different types and scales of fire emergency scenarios without large-scale system modifications, reducing the cost of system upgrades and expansions, and enhancing the practicality and promotional value of the technical solution.

[0040] This invention simplifies the operation process of fire emergency communication, reduces the risk of manual intervention, and achieves a comprehensive improvement in communication efficiency, stability and compatibility through intelligent and scenario-based design. It provides efficient and reliable communication support for fire rescue work and has significant practical application value.

[0041] The above overview is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features of the invention will become readily apparent from the accompanying drawings and the following detailed description. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a diagram of the overall system architecture of the present invention; Figure 2 This is a flowchart of the fire emergency communication method of the present invention; Figure 3 This is a timing diagram for the protocol conversion and adaptation of the present invention; Figure 4 This is a flowchart of the cross-departmental collaborative processing of the present invention. Detailed Implementation

[0044] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0045] It is important to note that terms such as "first," "second," "symmetric," and "array" are used only to distinguish between descriptive and positional descriptions and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, features specified with terms such as "first" or "symmetric" may explicitly or implicitly include one or more of that feature; similarly, when the quantity of certain features is not limited by words such as "two" or "three," it should be noted that such features also explicitly or implicitly include one or more features. In this invention, unless otherwise explicitly specified and limited, terms such as "installation," "connection," and "fixation" should be interpreted broadly; for example, they can refer to a fixed connection, a detachable connection, or an integral molding; they can refer to a mechanical connection, a direct connection, a welding connection, or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the accompanying drawings and specific circumstances.

[0046] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0047] Example 1: Application of emergency communication scenarios in fires in large chemical industrial parks This embodiment uses a sudden tank fire in a large chemical industrial park covering 800 acres as an example to illustrate the complete execution process of the fire emergency communication method of the present invention. The core modules of the technical solution in the scenario (scenario-based profiling, adaptive protocol conversion, cross-departmental collaboration, closed-loop optimization, and link assurance) will be implemented throughout the entire process. The communication terminals involved in the scenario include: 30 combustible gas sensors (LoRa IoT protocol) in the park, 20 temperature sensors (Modbus protocol), 15 handheld terminals for rescue personnel (TETRA dedicated fire protection protocol), 5 vehicle-mounted terminals for fire trucks (5G protocol), the park's fire command center terminal (Ethernet protocol), the environmental protection department's monitoring terminal (TCP / IP protocol), and the emergency management department's dispatch terminal (SIP protocol), covering 7 heterogeneous communication protocols. It is necessary to solve core requirements such as multi-protocol compatibility, communication in strong interference environments, and cross-departmental collaboration.

[0048] Step 1: Contextualized Profile Construction (Implementation of Core Module 1 of the Technical Solution) After a fire broke out due to a flammable gas leak in the storage tank area of ​​the chemical industrial park, 30 flammable gas sensors were the first to trigger alarms and initiate access requests. The multi-dimensional sensing module in the technical solution simultaneously started a parallel data acquisition mechanism. Protocol Feature Acquisition: Capture the protocol feature fields of each terminal (LoRa sensor frame format is "frame header (2 bytes) + address (4 bytes) + data (8 bytes) + checksum (2 bytes)", TETRA terminal encoding rule is CRC-16, 5G terminal transmission rate requirements). (etc.) and data structures; Scene parameter acquisition: Real-time acquisition of core parameters for fire emergency scenarios (fire occurs in tank area A, initial combustible gas concentration). Ambient temperature Wind speed There are 3 personnel work sites within 300m of the location, and the electromagnetic interference intensity is [not specified]. , (The standard interference intensity is used, and the initial urgency level of the scenario is level two). Application of profile generation algorithm: Establishing a dynamic mapping model of "protocol features - scenario requirements" and setting matching dimensions. (Protocol compatibility, transmission rate, data integrity, fault tolerance, real-time performance, and security), weighted coefficients are assigned based on the "explosion prevention and high real-time performance" requirements of the chemical industrial park:

[0049]

[0050] Real-time performance and transmission rate are given the highest weight. The matching degree of each terminal is calculated using the protocol-scenario matching degree formula:

[0051] Substituting the data, we calculate: Combustible gas sensor Rescue workers holding handheld terminals Fire truck onboard terminal Cross-departmental terminals ; Structured profile output: A profile is generated based on the matching degree, including the terminal's unique identifier and a list of core protocol parameters (such as the LoRa sensor transmission rate). ), scenario urgency level (Level 2), data transmission priority (combustible gas concentration data > personnel location data > temperature data > environmental data), fault tolerance threshold (core data) (Auxiliary data ≤ 2%) Profile generation efficiency: The multi-dimensional perception module completes the profile construction of all 60 terminals within 1.2 seconds after receiving the access request through distributed parallel parsing, meeting the real-time requirements of emergency scenarios.

[0052] Step 2: Adaptive Protocol Conversion (Implementation of Core Module 2 of the Technical Solution) The adaptive protocol mapping engine in the technical solution receives the profile data and initiates the dynamic protocol conversion process: Execution of the transformation rule generation algorithm: 1) Protocol syntax parsing: Extracting the core elements of each terminal protocol (data field definition of LoRa sensor, signaling format of TETRA terminal, encapsulation standard of 5G terminal). 2) Scenario requirement matching: Based on the level 2 urgency scenario, "combustible gas concentration and personnel location" are determined as priority fields (cannot be lost), and "ambient temperature and humidity" are fault-tolerant fields (allowing a small amount of loss). Core data adopts lossless compression, and auxiliary data adopts a 4:1 compression strategy. 3) Establishing mapping relationships: Generating a dedicated set of protocol conversion rules (such as converting LoRa protocol frame headers to core network general frame headers, and converting TETRA voice encoding to G.729 standard encoding). Gateway-free direct conversion: The conversion process is completed independently within the engine, without the need for a third-party protocol gateway. 30 sensor terminals and 20 mobile terminals process in parallel, with a single terminal conversion time of [time missing]. This avoids delays caused by intermediate forwarding; Data classification and labeling: Fire data is classified into three levels according to the urgency of the scenario and the weight of the data type (Level 1: personnel location, combustible gas concentration; Level 2: temperature, vehicle location; Level 3: ambient temperature and humidity, equipment status). The classification results are embedded in the 3rd and 4th bytes of the data header and synchronized to the core network and cross-department terminals. Adaptation efficiency verification: Evaluate the conversion effect using the protocol adaptation efficiency formula, and set... (Success rate weighting) (Time consumption weight) (Integrity weight), preset maximum allowable conversion time Efficiency threshold:

[0053] Actual monitoring data: converted into power Actual time consumed Total data volume before conversion Complete data volume after conversion Substituting into the calculation, we get:

[0054] No adjustment is needed to the conversion rules; Link establishment result: Bidirectional communication links between all terminals and the core network were successfully established, with no interference between the terminals and the protocol conversion compatibility rate of 100%.

[0055] Step 3: Cross-departmental Scene Perception and Collaboration (Implementation of Core Module 3 of the Technical Solution) The scene perception and collaboration engine in the technical solution receives standardized data and profile data, and initiates collaborative scheduling of voice, data, and bandwidth: Voice interference resistance coordination: As the fire spreads to adjacent storage tanks, the intensity of environmental interference escalates. Start the speech anti-interference coding algorithm and set the basic coding rate. Interference adaptation coefficient (Based on the preset electromagnetic interference type of the chemical industrial park), the final encoding rate is calculated using the formula:

[0056] Substitution

[0057] The voice signals from TETRA and 5G terminals are converted into a unified anti-interference format, automatically adapting to the call signaling of command centers and environmental protection departments, ensuring high voice clarity even in environments with strong interference. ; Intelligent data sharing: Through the intelligent data sharing interface in the technical solution, filtering rules are preset according to departmental responsibilities. Fire command center: Receives full data for Level 1 and Level 2 fire protection (including combustible gas concentration, personnel location, and temperature data); Environmental protection departments: only accept data on combustible gas concentration and atmospheric environment (Level I and Level II related data); Emergency management department: Receives personnel location and fire spread range data (Level 1 data); Dynamic bandwidth allocation: Total available bandwidth Resources are allocated according to priority using a bandwidth allocation formula, and a first-level data weight is set. Transmission requirements Secondary data Level 3 data :

[0058] Calculated , , After the fire emergency level was upgraded to Level 1, the demand for high-priority data increased to [a higher level]. The system automatically requests additional bandwidth. Temporarily occupy 1Mbps of a low-priority link to ensure core data transmission; Emergency command penetration: The fire command center initiates the command to "evacuate personnel within 300 meters of the storage tank area". The engine is marked as the highest priority, bypassing the regular dispatch queue, and is pushed to all handheld terminals, vehicle terminals and park broadcasting system within 0.4 seconds. Simultaneously, voice reminders and red pop-up alarms are triggered, and the receiving end provides feedback confirmation information within 1.2 seconds.

[0059] Step 4: End-to-end closed-loop optimization (implementation of core technical module 4) The end-to-end closed-loop management module in the technical solution initiates real-time monitoring and policy iteration: Multi-dimensional monitoring: Core indicators (protocol conversion efficiency, data transmission latency, link error rate, voice clarity) are collected every 1.5 seconds, while dynamic changes in the scene are captured (e.g., increased smoke concentration in the tank area, transmission latency of a handheld terminal increasing from 60ms to 210ms, exceeding the threshold). ); Application of strategy optimization algorithm: Setting adjustment step size (Set according to the urgency of the scenario), gradient of the policy objective function (Based on historical optimization data training), the policy adjustment amount is calculated using the formula:

[0060] Substitution The adaptive protocol mapping engine updates transformation rules (optimizes core data compression algorithms and reduces redundant fields), and the scene-aware collaboration engine adjusts bandwidth allocation (increasing primary data bandwidth to...). ); Fault self-healing mechanism: Trigger the link fault self-healing scheme to switch the handheld terminal from the main link (5G) to the backup link (LoRa), and reduce the transmission latency to 85ms within 1.8s, restoring it to within the threshold; Anomaly warning: The monitoring module detects that the bit error rate of a certain core link has increased from 0.2% to 0.4% (close to the threshold of 0.5%), and triggers an early warning signal to push to the maintenance terminal in advance to avoid link interruption; Log storage: Monitoring data, optimization parameters, and fault handling records are stored in the core database in real time to provide data support for subsequent iterations.

[0061] Step 5: Dynamic Iteration of Profile and Link Guarantee (Implementation of Core Module 5 of the Technical Solution) Profile Iterative Optimization: Using monitoring feedback data, information from 3 newly added UAV reconnaissance terminals, and upgraded scene urgency (Level 1) as data sources, effective information is extracted through data fusion algorithms, and the profile is updated incrementally and iteratively. The urgency level for all terminal scenarios has been adjusted to Level 1, and the fault tolerance threshold for core data has been reduced to ≤0.2%. New drone terminal profile (protocol: 5G+RTSP, transmission rate requirements) Data priority: "video data > location data"); Iteration effect verification: Calculated using the iterative matching degree formula, the total difference after iteration is 3.8, compared to 5.3 before iteration. The iteration is effective; Profile synchronization: The updated profile is synchronized to the protocol mapping engine and the collaboration engine within 0.6 seconds to complete the policy linkage adjustment; Link stability guarantee: 1) Dynamic fault tolerance: Based on the image fault tolerance threshold, forward error correction coding technology is used to automatically correct errors. A slight error of one bit; 2) Link quality assessment: The main link status is evaluated using the link quality index formula, and then... Actual transmission rate R=1.8Mbps, standard Bit error rate Maximum allowed Stable duration minutes, threshold minute:

[0062] Calculated (1.0 after normalization) The link is stable; 3) Enhanced anti-interference: Frequency hopping communication technology is adopted (frequency switching interval) To avoid fixed interference, the transmission power is reduced from... Adaptive boost to Expand coverage; 4) Idle self-check: After rescue personnel leave, the link automatically cleans up redundant data. Optimize frame interval from to This will improve the efficiency of subsequent communication.

[0063] Example 2: Comparison Experiment of Technical Solution Effects To verify the practical application value of the technical solution of this invention, a fire scenario in a large logistics park was selected for simulation experiments. The key performance indicators of the method of this invention and the traditional fire emergency communication method were compared. The experimental conditions and results are as follows: Experimental conditions - Access terminals: 60 different types of terminals (including sensors, mobile terminals, and cross-departmental terminals), covering 10 heterogeneous communication protocols; Scene setup: Simulates an environment with dense smoke and strong electromagnetic interference (interference intensity) The fire affected two logistics warehouses (Level 1 emergency). Test metrics: Protocol adaptation success rate (core metric of technical solution module 2), cross-departmental collaboration latency (core metric of module 3), voice clarity (core metric of module 3), fault self-healing time (core metric of module 4), and high-priority data transmission guarantee rate (core metric of modules 3+5).

[0064] Experimental results ; Results Analysis The technical solution of this invention solves the pain points of traditional methods, such as poor protocol compatibility, high collaboration latency, weak anti-interference, and slow fault recovery, through a full-link design of "profile-adaptation-coordination-closed loop-guarantee". The protocol adaptation success rate was improved by 26.5%, which is due to the dynamic rule generation capability of the adaptive protocol mapping engine in the technical solution, which does not rely on a fixed gateway. Cross-departmental collaboration latency was reduced by 82.7%, thanks to the precise filtering of intelligent data sharing interfaces and dynamic bandwidth allocation algorithms, which reduced invalid data transmission. The speech clarity was improved by 57.8% in strong interference environments. The key is that the speech anti-interference coding algorithm can dynamically adjust parameters according to the interference intensity. The self-healing time of faults is reduced by 92%, and automatic fault identification and switching are achieved by relying on full-link monitoring and preset fault repair schemes. The high-priority data transmission guarantee rate has been improved by 36.9%. Through multiple mechanisms such as priority classification, bandwidth allocation, and link quality assurance, the core data transmission is ensured to be uninterrupted.

[0065] Experimental results show that the technical solution of the present invention can effectively meet the core requirements of multi-protocol compatibility, cross-departmental collaboration, strong interference communication, and rapid fault recovery in complex fire emergency scenarios, and is significantly better than traditional methods.

[0066] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various variations or substitutions within the technical scope disclosed in the present invention, and these should all be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A fire emergency communication method, characterized in that, include: To obtain fire emergency scenarios, a profile generation algorithm is used to generate protocol and scenario-related profiles of the access subjects, clarifying the protocol type, data format, transmission rate requirements, and scenario-based transmission priority. Based on the aforementioned protocol and scenario-related profile, an adaptive protocol mapping engine is launched. A proprietary protocol conversion rule is dynamically generated through a protocol conversion rule generation algorithm. Within the engine, the real-time conversion between the private protocol and the core network's general protocol is completed, establishing a bidirectional communication link between the terminal and the core network. Simultaneously, the fire data collected by the terminal is graded and labeled according to the urgency of the scenario, and the conversion effect is evaluated through a protocol adaptation efficiency formula. Based on the standardized data after hierarchical labeling, the scene-aware collaboration engine is launched. The voice anti-interference coding algorithm converts the voice signals of cross-departmental systems into a scene-based anti-interference format and automatically adapts to the call signaling. Cross-departmental data scene synchronization is achieved through the intelligent data sharing interface. Bandwidth resources are allocated according to the data hierarchical standard based on the dynamic bandwidth allocation formula. Real-time monitoring of core indicators, combined with dynamic changes in fire scenarios, and the use of strategy optimization algorithms to trigger iterative optimization of adaptation and collaborative strategies, establish a full-link fault self-healing mechanism. Based on monitoring feedback data and dynamic changes in the scene, the protocol and scene-related profiles are dynamically iterated through the profile iteration algorithm. The protocol characteristics of newly added access subjects and the transmission requirements of new scenes are supplemented and synchronously fed back to the adaptive protocol mapping engine and the scene perception collaboration engine to form a closed-loop operation of the entire link.

2. The fire emergency communication method as described in claim 1, characterized in that, The protocol and scenario-related profiles for generating access subjects include: The multi-dimensional perception module captures the protocol feature fields and data structures in the access request, and collects fire emergency scenario parameters in real time. A dynamic mapping model between "protocol features and scenario requirements" is established, and a profile generation algorithm is used to calculate the matching degree between protocol features and scenario requirements. The formula is as follows: ； in, For protocol and scenario matching degree, To match the number of dimensions, For the first Dimension weight coefficients , Let $i$ be the protocol feature value of the access subject in the $i$-th dimension. Let $i$ be the requirement value for the scenario in the $i$-th dimension. These are the maximum values ​​for their respective dimensions; Based on matching degree Generate structured protocol and scenario-related profiles, which include a unique identifier for the access subject, a list of core protocol parameters, scenario urgency level, data transmission priority benchmark, and fault tolerance threshold. The profile supports real-time incremental updates. When the protocol version of the access subject is iterated or the scene parameters change abruptly, the profile is automatically corrected locally. The correction effect is then recalculated and verified using the matching degree formula mentioned above. The multi-dimensional perception module shortens the time required to generate profiles through a parallel acquisition and parsing mechanism, completing profile construction after receiving an access request.

3. The fire emergency communication method as described in claim 2, characterized in that, The dynamic generation of proprietary protocol conversion rules and the completion of protocol conversion include: The adaptive protocol mapping engine extracts protocol features and scenario requirements from the protocol and scenario association profiles. Through protocol syntax parsing and scenario requirement matching algorithms, it constructs protocol conversion logic that adapts to the current terminal and scenario in real time. The algorithm steps are as follows: 1) Parse the protocol syntax structure and extract core elements such as field definitions, frame formats, and encoding rules; 2) Determine the priority fields, fault tolerance fields, and compression strategies for data transmission based on scenario requirements; 3) Establish the mapping relationship between elements and strategies, and generate an executable set of protocol conversion rules; The conversion process is completed independently within the engine, without the need for a third-party protocol conversion gateway, thus reducing intermediate forwarding steps; Data classification and labeling is based on the urgency level of the scenario, superimposed with data type weights, and completed according to priority levels. The classification results are embedded in the data header fields and synchronized to the core network and cross-departmental collaboration system. Establish a protocol conversion compatibility verification mechanism and evaluate the conversion effect using a protocol adaptation efficiency formula: ； in, To improve protocol adaptation efficiency, Convert the protocol into power. The actual conversion time, To preset the maximum allowed conversion time, This represents the total amount of data after conversion. This represents the total amount of data before conversion. Weighting coefficients ;like Then the conversion rules will be adjusted in real time; The adaptive protocol mapping engine supports parallel adaptation across multiple terminals and can simultaneously handle protocol conversion requests from multiple access subjects of different types, with each conversion task being independent of the others.

4. The fire emergency communication method as described in claim 3, characterized in that, The scene-aware collaboration engine enables cross-departmental voice and data collaboration, including: Voice collaboration employs a voice anti-interference coding algorithm that adaptively adjusts coding parameters based on the scene type and environmental parameters in the protocol and scene association profile. The core of the algorithm is: ； in, For the final coding rate, Based on the coding rate, For interference adaptation coefficient, This represents the actual environmental interference intensity. The standard interference strength is set; the algorithm converts voice signals from different departments and systems into a unified, scenario-based anti-interference format, and automatically adapts call signaling based on scenario requirements. Data collaboration uses the pre-set scenario-based data filtering rules of the intelligent data sharing interface to accurately push various types of rescue-related data to the dispatch terminals of the corresponding departments according to the departmental responsibilities and scenario requirements in the protocol and scenario association profile. Dynamic bandwidth allocation is based on data classification standards and real-time scenario requirements, using a bandwidth allocation formula to calculate the bandwidth share for each priority data type. ； in, For the first Priority data allocation bandwidth For the first Priority weight value, For the first The need for real-time transmission of priority data Number of priority levels The total available bandwidth; when bandwidth is insufficient, low-priority data is temporarily stored at the nearest edge node and transmitted in order of priority after the bandwidth is released; Cross-departmental command collaboration supports the penetrating transmission of emergency commands across departments. When a department initiates an emergency rescue command, the scene-aware collaboration engine automatically marks the command as the highest priority, bypasses the regular dispatch queue, and directly pushes it to the core dispatch terminal of the relevant department, while triggering voice reminders and pop-up alarms. Establish a cross-departmental collaborative status feedback mechanism. After the data and instructions are transmitted, the receiving end will automatically provide confirmation information, and the feedback results will be synchronized to the scene-aware collaborative engine and the full-link monitoring module.

5. A fire emergency communication method as described in claim 4, characterized in that, The real-time monitoring and strategy iteration optimization include: The end-to-end monitoring module collects core operational indicators at preset intervals, while simultaneously capturing dynamic changes in the scene to form a multi-dimensional monitoring dataset. A threshold judgment model is established based on the monitoring dataset. A strategy optimization algorithm is used to trigger adaptation and collaborative strategy optimization. The algorithm logic is as follows: ； in, For the adjustment amount of strategy parameters, To adjust the step size, These are the actual monitoring indicator values. For the indicator threshold, This is the gradient of the policy objective function; for protocol adaptation problems, the linked adaptive protocol mapping engine updates the conversion rules through this algorithm; for cooperative transmission problems, this algorithm adjusts the bandwidth allocation ratio, speech coding algorithm parameters, or data transmission path. The end-to-end fault self-healing mechanism has preset corresponding automatic repair schemes for various types of faults, and automatically matches and executes the repair strategy when a fault occurs. The monitoring module supports anomaly warning function. By analyzing the trend of indicator changes, it can identify potential fault risks in advance and trigger warning signals before the indicators approach the threshold, and push them to the maintenance terminal. Monitoring data and optimization logs are stored in the core database in real time.

6. The fire emergency communication method as described in claim 5, characterized in that, The dynamic iteration of the protocol and scene-related profile includes: The profile iteration uses full-link monitoring feedback data, newly added access entity information, and dynamic scene change data as core data sources, and extracts effective update information through data fusion algorithms. The iteration effect is verified by combining incremental iteration and full update, using the profile iteration matching degree formula. ； in, To improve the matching degree coefficient during iteration, Let $i$ be the protocol feature value and the scenario requirement value of the $i$-th dimension after iteration. The corresponding value before iteration; This indicates that the iteration is valid; For changes in local parameters, incremental iterations are performed, updating only the corresponding fields in the profile; for changes in scenario type, major iterations of the access subject protocol, etc., a full update is performed to rebuild the complete profile. The iterated profile is synchronized in real time to the adaptive protocol mapping engine and the scene perception collaboration engine via a dedicated data channel; Establish an iterative verification mechanism for the profile. After each iteration, the matching degree is calculated using the aforementioned iterative matching formula. Automatically triggers the second iteration; The image iteration process is implemented through parallel processing in the background without interrupting the existing communication link.

7. A fire emergency communication method as described in claim 6, characterized in that, The stability guarantee of the bidirectional communication link includes: Based on the fault tolerance threshold and scenario stability requirements in the protocol and scenario association profile, a dynamic fault tolerance mechanism is configured for each bidirectional communication link to automatically identify and correct minor errors in the data transmission process. Establish a dynamic link quality assessment model and quantify the link status using the link quality index formula: ； in, This is the link quality index (value range 0-1). This is the actual transmission rate. For standard transmission rate, This represents the actual bit error rate. For the maximum permissible bit error rate, For link connection stability duration, To preset a stable duration threshold, Weighting coefficients ;like It automatically triggers link switching, migrating communication tasks to the backup link; To address link interference issues in complex scenarios, frequency hopping communication and signal enhancement techniques are employed. It supports dynamic expansion of link bandwidth. When the demand for high-priority data transmission surges, it automatically requests additional bandwidth resources or temporarily occupies part of the bandwidth of low-priority links. When the link is idle, it automatically performs self-checks and maintenance, cleans up redundant data, and optimizes link parameters.

8. A fire emergency communication method, characterized in that, include: Contextualized profiling module: used to capture access requests and context parameters, generate and dynamically iterate protocol and context-related profiles through profile generation algorithms, and output profile data to the adaptive protocol mapping engine and the context-aware collaboration engine; Adaptive Protocol Mapping Engine: It receives profile data, dynamically generates protocol conversion rules through a protocol conversion rule generation algorithm, completes real-time adaptation between private and general protocols, performs adaptability verification through a protocol adaptation efficiency formula, outputs tiered standardized data, and responds to policy optimization instructions. Scene-aware collaboration engine: It receives standardized data and profile data, realizes cross-departmental voice anti-interference conversion through voice anti-interference coding algorithm, completes dynamic bandwidth allocation through bandwidth dynamic allocation formula, realizes data scene-based sharing and emergency command penetration transmission, and provides feedback on collaboration status information; The end-to-end closed-loop management module is used to monitor core indicators during the adaptation and collaboration process, capture dynamic changes in the scenario, trigger iterative optimization and fault self-healing through strategy optimization algorithms, store monitoring data and optimization logs, and feed back update information to the scenario-based profiling module. Two-way communication link management module: used to establish and maintain two-way communication links between terminals and cross-departmental systems, perform link quality assessment through the link quality index formula, and complete fault tolerance correction, switching and expansion.

9. A fire emergency communication method, characterized in that, It also includes, Electronic device: The device includes a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, wherein when the computer-executable instructions are executed by the processor, the steps of the fire emergency communication scenario-based intelligent adaptation and collaboration method according to any one of claims 1 to 7 are implemented; A computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the fire emergency communication scenario-based intelligent adaptation and collaboration method according to any one of claims 1 to 7.

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