Disaster event priority broadcasting method and system based on minimum necessary information

Abstract

The present application relates to the field of communication and disaster warning, and proposes a disaster event priority broadcast method and system based on minimum necessary information, which comprises the following steps: when an abnormal event is detected by a monitoring node, an event data packet is constructed, the data packet adopts a minimum necessary information structure and only contains node identification, time stamp, type, initial motion characteristic parameter and quality mark; priority score is calculated according to time urgency, spatial density and data quality, and the data packet is classified; an access mechanism based on channel competition is adopted, a competition window is configured according to priority difference, a smaller window is used for high priority data to shorten the backoff time, and the window is dynamically adjusted to maintain the priority difference when the network is congested; the network state is monitored in real time, and the sending strategy is adjusted according to the packet loss rate and the time delay. Through the simplified data structure and dynamic priority control, the present application effectively reduces the transmission delay, solves the concurrent conflict problem, and guarantees the real-time and reliability of the disaster warning information.

Description

Technical Field

[0001] This invention relates to the field of communication and disaster early warning technology, and in particular to a disaster event priority broadcasting method and system based on minimum necessary information. Background Technology

[0002] Geological hazards are diverse, with sudden events such as earthquakes, landslides, and debris flows characterized by their sudden occurrence and wide-ranging impact, posing significant threats to personnel safety and infrastructure operation. To achieve timely detection and early warning of disaster events, a distributed monitoring network consisting of multiple monitoring nodes is typically deployed within the target area. Each node transmits monitoring data to a data processing center for analysis via wireless communication.

[0003] In actual operation, when a disaster occurs, multiple monitoring nodes often trigger and report data almost simultaneously. At this time, the network bears a large number of concurrent data transmission requests in a short period of time. Whether the early warning information can reach the processing center in a timely manner largely depends on the real-time performance and reliability of data transmission. Therefore, how to ensure the priority transmission of critical data in complex network environments has become an important issue in related technologies.

[0004] In existing monitoring systems, nodes typically upload raw waveform data or complete data packets after triggering an anomaly. This type of data is large in volume, consuming significant channel resources and easily leading to increased transmission latency under concurrent conditions, making it difficult to meet the needs of rapid early warning. Furthermore, existing systems often employ relatively simple prioritization methods, such as distinguishing alarm information from regular data, but lack a comprehensive assessment of factors such as event timeliness, spatial distribution characteristics, and data quality, making it difficult to accurately reflect the importance of different events at the current moment.

[0005] In terms of channel access, commonly used carrier sense multiple access (CSM) mechanisms typically prioritize fairness, with minimal differences among nodes competing for the channel. However, when a large number of concurrent transmission requests occur in the network, contention and conflicts can easily arise between data of different priorities, making it difficult for high-priority data to secure stable priority access. Under high network load, this can also lead to increased latency or even loss of critical data transmissions.

[0006] Existing systems have limited adaptability to changes in network conditions. Continuing to send data according to the original strategy when the network is congested or communication quality degrades can easily lead to increased data retransmissions, further exacerbating the network load and impacting overall transmission efficiency. In such scenarios, there is a lack of a mechanism that can dynamically adjust the transmitted content and sending strategy based on network conditions.

[0007] Based on the above, the present invention provides a disaster event priority broadcasting method and system based on minimum necessary information to improve the transmission efficiency and reliability of critical data in complex network environments. Summary of the Invention

[0008] The purpose of this invention is to address the shortcomings of existing technologies by providing a disaster event priority broadcasting method and system based on minimum necessary information, so as to improve the transmission efficiency and reliability of critical data in complex network environments.

[0009] A disaster event priority broadcasting method based on minimum necessary information includes the following steps: S101, the monitoring node continuously collects environmental monitoring data. When an abnormal event is detected, an event data packet is constructed. The event data packet adopts the minimum necessary information structure and contains only the key parameters used to quickly determine the event. S102, calculate the priority score of the event data packet according to the preset scoring function, and divide the event data packet into different priorities according to the score value; S103, a channel contention-based access mechanism is used for data broadcasting, and the contention window in the channel access parameters is adjusted based on the priority so that different priority data correspond to different contention window ranges, wherein high priority data corresponds to a smaller contention window to shorten the backoff time; S104 monitors network status in real time and adaptively adjusts data transmission strategies based on network congestion levels.

[0010] Preferably, in step S101, the criteria for determining abnormal events include at least one of the following: Amplitude threshold determination, monitoring signal amplitude at the current moment Greater than the preset threshold ; The ratio of short-term average to long-term average is determined when the ratio of the short-term average (STA) to the long-term average (LTA) is greater than a preset ratio threshold. .

[0011] Preferably, in S101, the minimum necessary information structure includes: The monitoring node identifier uses a 32-bit code, consisting of an area identifier and a node sequence number; Event timestamp, using 64-bit millisecond-level timestamp; Event type, encoded as a 1-byte enumeration value; Initial motion characteristic parameters, including initial arrival time, initial motion amplitude, and dominant frequency characteristics, are encoded using fixed-point quantization. Data quality labels are discrete levels obtained by mapping the signal-to-noise ratio (SNR). The total length of the event data packet does not exceed 32 bytes.

[0012] Preferably, in step S102, the priority scoring function is: ; in, Rate the priority; It is an indicator of time urgency, and its value decreases as time goes on. This is a spatial density index, representing the percentage of monitoring nodes that trigger abnormal events within a preset spatial range; The numerical value corresponding to the data quality marker; These are the weighting coefficients.

[0013] Preferably, S103 includes: Before sending data, channel listening is performed. When the channel is idle, transmission is executed, and when the channel is busy, a backoff phase is entered. Different competition window ranges are set according to data priority, and the backoff time is determined based on a random backoff mechanism, so that high-priority data has a shorter average backoff time.

[0014] Preferably, in step S103, the contention window range is dynamically adjusted according to data priority and the current network congestion status. When the network congestion level increases, the contention window corresponding to each priority increases as a whole, and a preset contention window difference is maintained between different priorities to improve the channel access success rate of high-priority data under congestion.

[0015] Preferably, in step S104, adaptively adjusting the data transmission strategy according to the network congestion level includes: Calculate the packet loss rate L and the average delay D; When L < 5% and D < 50ms, it is determined to be a normal state, and the minimum necessary information data packet and associated supplementary detailed data are sent. When 5%≤L≤10%, it is determined to be a mild congestion state, and the transmission of low-priority data is restricted. When L > 10%, it is determined to be a severe congestion state, and only the minimum necessary information data packets are sent.

[0016] Preferably, it further includes: for event data classified as high priority, performing repeated broadcasts within a preset time window, wherein the time interval between two adjacent transmissions is a value randomly selected within a preset range. Another objective of this invention is to provide a disaster event priority broadcasting system based on minimum necessary information, comprising: a data generation module, used to construct an event data packet when a monitoring node detects an abnormal event, wherein the event data packet adopts a minimum necessary information structure; The data classification module is used to calculate priority scores according to a preset scoring function and to classify the event data packets by priority. The transmission control module is used to broadcast data using a channel contention-based access mechanism, perform channel listening before data transmission, adjust the contention window range according to data priority, and perform random backoff control. The adaptive adjustment module is used to monitor the network status in real time and adaptively adjust the data transmission strategy according to the degree of network congestion.

[0017] The present invention also provides a computer-readable storage medium storing a disaster event priority broadcasting program based on minimum necessary information, wherein the disaster event priority broadcasting program based on minimum necessary information, when executed by a processor, implements the steps of the disaster event priority broadcasting method based on minimum necessary information as described above.

[0018] The present invention discloses a disaster event priority broadcasting method and system based on minimum necessary information, which has the following beneficial effects.

[0019] This invention employs a minimum necessary information structure to control the data packet length to a very small range, significantly reducing data transmission time and effectively reducing channel occupancy time, thus securing a valuable millisecond-level time window for disaster early warning.

[0020] This invention introduces a comprehensive scoring function that includes time urgency, spatial density, and data quality, enabling dynamic quantitative assessment of the importance of disaster events and ensuring that high-value key early warning data can be accurately identified.

[0021] This invention, through differentiated competition window settings and dynamic adjustment mechanisms, can maintain the advantage of high-priority data in channel competition even when network congestion intensifies, avoiding the "starvation" phenomenon of critical data caused by conflicts in traditional mechanisms, and significantly improving transmission reliability.

[0022] This invention can adaptively adjust the transmission strategy according to the real-time network status and automatically downgrade the transmission of core information when the network quality deteriorates. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the overall process of the disaster event priority broadcasting method based on minimum necessary information provided in the embodiments of the present invention.

[0024] Figure 2 This is a structural block diagram of a disaster event priority broadcasting system based on minimum necessary information provided in an embodiment of the present invention. Detailed Implementation

[0025] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0026] In this document, the term "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The term "embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment, nor does it specifically limit its independence or connection with other embodiments. In principle, in this application, as long as there are no technical contradictions or conflicts, the technical features mentioned in each embodiment can be combined in any way to form corresponding implementable technical solutions.

[0027] Unless otherwise defined, the technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the use of related terms herein is merely for the purpose of describing particular embodiments and is not intended to limit this application.

[0028] In the description of this application, the term "and / or" is used to describe the logical relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A exists, B exists, and A and B exist simultaneously. Additionally, the character " / " in this document generally indicates that the preceding and following objects have an "or" logical relationship.

[0029] Unless otherwise expressly specified or limited, the terms "installation," "connection," "linking," "fixing," and "setting," as used in the description of the embodiments of this application, should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral setting; it can be a mechanical connection, an electrical connection, or a communication connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be the internal connection of two components or the interaction between two components. For those skilled in the art to which this application pertains, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances. Example 1

[0030] like Figure 1 As shown, this embodiment provides a disaster event priority broadcasting method based on minimum necessary information, applied to a distributed disaster monitoring network. This network includes multiple monitoring nodes (such as earthquake monitoring stations, landslide sensors, etc.) distributed within the monitoring area and one or more receivers. Communication between monitoring nodes and between nodes and receivers occurs via wireless channels. Given that a large number of nodes may concurrently report data during a disaster, and that wireless bandwidth resources are limited, this embodiment aims to ensure the transmission of critical early warning information by simplifying the data structure and optimizing the channel access mechanism.

[0031] The method in this embodiment specifically includes steps S101 to S104, as well as a preferred repeated broadcasting step, which is described in detail below: S101: The monitoring node continuously collects environmental monitoring data. When an abnormal event is detected, it constructs an event data packet. By reducing the data packet length, the channel occupancy time is effectively reduced, thereby improving channel utilization efficiency and reducing the probability of collisions.

[0032] Monitoring nodes continuously collect environmental data at high sampling rates (e.g., 100Hz) using sensors such as accelerometers and displacement gauges. To issue alerts as soon as an anomaly occurs, the nodes perform sliding window analysis on the real-time data stream.

[0033] Logic for determining abnormal events: This embodiment employs a dual triggering mechanism, determining an abnormal event as triggered if any of the following conditions are met: (1) Amplitude threshold determination criteria: ,in, To monitor the signal amplitude at the current moment, This is a preset threshold.

[0034] (2) Criteria for determining the ratio of short-term average to long-term average: Where STA is the short-term average and LTA is the long-term average. This is a preset ratio threshold.

[0035] When any of the above conditions are met, an abnormal event is determined to have occurred, and the monitoring node triggers the data packet generation process.

[0036] After an abnormal event is triggered, the monitoring node constructs an event data packet. This event data packet uses a minimal essential information structure, containing only key parameters for quickly determining the event. The minimal essential information data packet includes the following fields: First, the monitoring node identifier uses a 32-bit code, consisting of a region identifier and a node serial number. The region identifier occupies 16 bits, and the node serial number occupies 16 bits, which is used to achieve a unique identifier for the entire network.

[0037] Second, the event timestamp uses a 64-bit timestamp with millisecond precision, generated based on a time synchronization mechanism, which includes GPS time synchronization or network time synchronization.

[0038] Third, event type: Abnormal events are classified according to preset lightweight classification rules and encoded as 1-byte enumeration values. For example, when the main frequency of a signal is lower than a preset frequency threshold and the duration exceeds a first time threshold, it is determined to be an earthquake event; when the signal exhibits instantaneous impact characteristics and the duration is lower than a second time threshold, it is determined to be an interference event.

[0039] Fourth, the initial motion characteristic parameters are obtained by processing the data within a preset time window before and after the trigger, including the P-wave arrival time, initial motion amplitude, and dominant frequency characteristics. The initial motion characteristic parameters are encoded using a fixed-point quantization method.

[0040] Fifth, data quality labeling: The quality level is calculated based on the signal-to-noise ratio (SNR) of the monitored data. The SNR is defined as: ; in, For signal power, The noise power is mapped to discrete levels based on the SNR value, for example: an SNR greater than 20 dB corresponds to high quality, 10 dB to 20 dB corresponds to medium quality, and less than 10 dB corresponds to low quality.

[0041] In this embodiment, the above fields are constructed using a compact encoding method to form an event data packet, the total length of which does not exceed 32 bytes.

[0042] In addition, the monitoring node can generate associated supplementary detailed data containing detailed waveform data for transmission when the channel is idle.

[0043] S102: Calculate the priority of the generated event data packets according to the preset scoring function, and divide the event data packets into different priorities according to the scoring value to determine their transmission priority in the communication process.

[0044] In this embodiment, to address the issue of nodes being unable to obtain real-time information about their neighbors' status in a distributed network, a neighborhood status interaction mechanism is introduced before calculating priorities. After detecting an abnormal event and constructing an event data packet, the monitoring node immediately broadcasts a very short 'event trigger beacon' on the control channel and simultaneously opens a listening window (e.g., lasting 50ms). The monitoring node counts the number of 'event-triggered beacons' received from neighboring nodes within the listening window, and calculates the spatial density index by combining this count with the preset total number of neighboring nodes. .

[0045] In this embodiment, the scoring function can be a linear or nonlinear function, and the priority scoring function is defined as follows: ; in, Rate the priority; It is a time urgency indicator, representing a function of the time elapsed since the event was triggered, and its value decreases as time increases; This is a spatial density index, representing the ratio of the number of monitoring nodes that trigger abnormal events within a preset spatial range to the total number of nodes. The preset spatial range is a preset radius range centered on the current node or a set of adjacent nodes. The numerical value corresponding to the data quality marker; These are the weighting coefficients.

[0046] Based on priority score Compare with a preset threshold: when When, it is determined to be of high priority; when When, it is determined to be of medium priority; when When that happens, it is judged as low priority.

[0047] S103: Data broadcasting is performed using a channel contention-based access mechanism, and the contention window in the channel access parameters is adjusted based on priority.

[0048] In this embodiment, S103 specifically includes the following steps: Before data transmission, the monitoring node performs channel listening. Transmission is performed when the channel is idle; a backoff phase is initiated when the channel is busy. The node determines the backoff time based on a random backoff mechanism, calculated using the following formula: ; in, As a competitive window, This is the base time slot. As the number of collisions increases, the contention window expands according to preset rules; when transmission is successful, the contention window returns to its initial value.

[0049] To avoid channel conflicts caused by multiple monitoring nodes sending data simultaneously and to ensure the transmission efficiency of high-priority data, this embodiment sets different contention window ranges for data of different priorities.

[0050] Specifically, high-priority data corresponds to a smaller contention window, while low-priority data corresponds to a larger contention window. Because the contention window of high-priority data is smaller, its average backoff time is shorter, thus giving it a higher probability of access in channel contention.

[0051] Furthermore, this embodiment introduces a dynamic adjustment mechanism for the contention window. The system monitors the network congestion level in real time (the congestion level is determined based on a combination of packet loss rate and average latency).

[0052] The adjustment rule is as follows: When network congestion increases, the overall contention window corresponding to each priority increases, and a preset contention window difference is maintained between different priorities, so as to improve the channel access success rate of high-priority data under congestion.

[0053] For example, specific numerical examples are as follows: In the initial state: High-priority contention window range: ; Low-priority contention window range: ; Preset competition window difference .

[0054] When the network is detected to be in a state of moderate congestion, the system adaptively increases the contention window: The high-priority contention window has been adjusted to: [8,32]; The low-priority contention window is adjusted to: [20,76].

[0055] Through the above mechanism, although the backoff time of all nodes increases due to network congestion (to reduce collisions), the backoff time of high-priority data is always significantly shorter than that of low-priority data because a preset contention window difference is maintained. This allows high-priority critical early warning data to still preempt the channel with a higher probability in severe environments with increased network congestion, avoiding the "starvation" phenomenon of critical information transmission caused by network performance degradation.

[0056] As an optional supplementary measure, this embodiment also employs a time-slice-based time-division transmission strategy. Time synchronization is performed on each monitoring node, and the communication cycle is divided into several time slices, with each time slice corresponding to one or more monitoring nodes. Nodes only transmit data within their corresponding time slice, remaining in a listening or standby state for the rest of the time, thereby reducing the probability of basic collisions from a time perspective.

[0057] S104: Monitor network status in real time and adaptively adjust data transmission strategy according to network congestion level.

[0058] The sending strategy is dynamically adjusted to adapt to different network conditions.

[0059] In this embodiment, the system monitors the following indicators in real time: calculating the packet loss rate L and the average latency D; wherein, the packet loss rate L is obtained based on the sending and receiving statistics within a preset time window; and the average latency D is calculated based on the time from data sending to acknowledgment.

[0060] Determine network status based on indicators: When L < 5% and D < 50ms, it is determined to be a normal state, and the minimum necessary information data packet and supplementary data packet are sent, so that the central station can still obtain complete seismic waveform data for subsequent analysis while ensuring the timeliness of the early warning. When 5%≤L≤10%, it is determined to be a mild congestion state, and the transmission of low-priority data is restricted. When L > 10%, it is determined to be a severe congestion state, and only the minimum necessary information data packets are sent.

[0061] In this embodiment, for event data classified as high priority, repeated broadcasting is performed within a preset time window, and the time interval between two adjacent transmissions is a value randomly selected within a preset range.

[0062] In this embodiment, the number of repeated transmissions is 2 to 3, and the time interval between two adjacent transmissions is a random value. The random time interval is within a preset range to avoid secondary conflicts caused by multiple nodes transmitting synchronously.

[0063] Through the above steps, this embodiment achieves simplified construction of disaster event data, dynamic priority determination, priority access and transmission, conflict control, adaptive degradation transmission and rebroadcast protection, thereby significantly improving the real-time performance and reliability of disaster early warning information. Example 2

[0064] like Figure 2 As shown, this embodiment provides a disaster event priority broadcasting system based on minimum necessary information to implement the method of Embodiment 1 above.

[0065] The system specifically includes: The data generation module is used to continuously collect environmental monitoring data and construct event data packets when abnormal events are detected.

[0066] The specific configuration is as follows: Perform amplitude threshold determination ( ) or the ratio of short-term average to long-term average () To detect abnormal events.

[0067] After an event is triggered, the module generates a data packet according to the minimum necessary information structure, including: a 32-bit monitoring node identifier (region ID + node sequence number), a 64-bit millisecond-level event timestamp, a 1-byte event type enumeration value, fixed-point quantized initial characteristic parameters, and a data quality tag based on signal-to-noise ratio (SNR) mapping. The total length of the generated data packet is controlled within 32 bytes.

[0068] The data classification module is connected to the data generation module and is used to receive event data packets and calculate their transmission priority.

[0069] The specific configuration is as follows: A built-in priority scoring calculation unit, based on the formula... Calculate the score. This module will calculate the score. The data packets are compared with a preset threshold and marked as high, medium, or low priority.

[0070] The transmission control module is connected to the data classification module and is used to schedule the transmission of data packets according to priority tags.

[0071] The specific configuration is as follows: maintain three transmission queues: high, medium, and low. For high-priority data, activate the repeat broadcast unit and control the wireless communication interface to perform 2 to 3 transmissions within a preset time window, with the transmission interval using a random value to avoid synchronization collisions.

[0072] The collision control module is connected to the transmission control module and is used to execute collision avoidance strategies during channel contention access.

[0073] The specific configuration is as follows: Implement time-slice-based time-division transmission logic and maintain a local time-slice allocation table; Implement a transmission strategy based on random backoff, and calculate the backoff time when the channel is detected to be busy. ; Implement a priority-based transmission preemption mechanism and store multiple sets of contention window parameter configurations. When transmitting high-priority data, select a smaller contention window range; when transmitting low-priority data, select a larger contention window range.

[0074] Furthermore, the module is equipped with a contention window dynamic adjustment unit, which executes the following logic: when a signal of increased network congestion is received, the contention window value of each priority is increased as a whole, and the preset contention window difference between different priorities is maintained to ensure the access advantage of high-priority data in congested conditions.

[0075] The adaptive adjustment module is used to monitor the network status in real time and dynamically adjust the transmission strategy.

[0076] The specific configuration is as follows: calculate the packet loss rate L and average latency D within a preset time window.

[0077] The status determination unit is used for comparison: when L < 5% and D < 50ms, it outputs a "normal state" signal; when 5% ≤ L ≤ 10%, it outputs a "mild congestion" signal; when L > 10%, it outputs a "severe congestion" signal.

[0078] The strategy execution unit performs operations based on status signals: on the one hand, it sends instructions to the conflict control module to trigger dynamic adjustment of the contention window; on the other hand, it sends instructions to the transmission control module to allow the transmission of all data under "normal state"; restrict low-priority data under "mild congestion"; and allow the transmission of only the minimum necessary information data packets under "severe congestion" while suspending other data transmissions to ensure the smooth flow of core early warning information.

[0079] In this embodiment, the readable storage medium may be a non-transitory computer-readable storage medium storing computer instructions, which are used to cause the computer to execute the disaster event priority broadcasting method based on minimum necessary information as described in Embodiment 1 above.

[0080] In an exemplary embodiment, the computer program product includes a computer program that, when executed by a processor, implements the disaster event priority broadcasting method based on minimum necessary information as described in Embodiment 1 above.

[0081] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0082] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0083] Application Examples To more clearly illustrate the practical application effects of this invention, the following describes in detail the application process of the method and system of this invention using a distributed earthquake early warning and monitoring network in a seismically active area as an example. This monitoring network consists of 100 earthquake monitoring nodes deployed around a fault zone. The nodes communicate via a wireless mesh self-organizing network, and the central processing station is located in a regional data center. The network environment is complex, and a large number of nodes may simultaneously report data during an earthquake, placing extremely high demands on real-time transmission.

[0084] During actual operation, at a certain time T0, the earthquake P-wave arrives in the monitoring area near the epicenter. Node A (numbered 0x0101) and the neighboring node B detect the initial motion of the P-wave almost simultaneously (with an error in the millisecond range).

[0085] The data generation module of node A calculates the STA / LTA ratio in real time. When the ratio exceeds a threshold... When this occurs, an abnormal event is triggered.

[0086] According to step S101 of the present invention, node A does not transmit complete acceleration waveform data (which typically requires several KB in conventional methods), but immediately constructs a "minimum necessary information" data packet: Extract the node ID (4 bytes); record the P-wave arrival timestamp (8 bytes, millisecond precision); determine the event type (1 byte, such as earthquake event); calculate the initial motion characteristic parameters (P-wave amplitude quantized to 2000, dominant frequency 2.5Hz, total 8 bytes); based on the signal-to-noise ratio SNR=25dB, map the quality label as 3 (high quality, 1 byte).

[0087] In summary, the total length of the key fields is 22 bytes. Considering protocol overhead or reserving priority flag bits, the final total length of the generated data packet is controlled within 23 bytes, reducing the data volume by more than 90% compared to the traditional method.

[0088] Node A's data hierarchy module executes step S102, entering the priority calculation stage. According to the method of the present invention, Node A opens a short-term listening window before the calculation: Node A broadcast its own "event-triggered beacon" and received an "event-triggered beacon" sent by neighboring node B within its listening window.

[0089] Based on this interaction information, node A determines that a neighboring node has concurrently triggered the event, and the spatial density index... Increase (set to 0.8); due to the recent occurrence of the event, time urgency is high. The highest rating (set to 1.0); data quality The value is 3.

[0090] System input scoring function The calculated score is Because of (Threshold 80) This data packet is determined to be of high priority and marked as Priority 0.

[0091] Meanwhile, node C, which is farther from the epicenter, detected a slight vibration, identified it as an interference event, and generated a low-priority data packet.

[0092] According to step S103, node A and node C simultaneously attempt to send data: Initial contention: Node C (low priority) is configured to use a larger contention window (e.g., The backoff time is relatively long; Node A (high priority) is configured to use a smaller contention window (e.g., Node A won the channel contention and was the first to occupy the channel and send a 23-byte warning data packet. Node C detected that the channel was busy and entered a backoff suspension state.

[0093] As the seismic waves spread, a large number of nodes were triggered, and the network packet loss rate L rose to 12%.

[0094] According to step S104, the system detects that L > 10% and determines that it has entered a "severe congestion state". The system immediately adjusts its strategy: suspends all unnecessary extended data transmission, and only allows the transmission of the minimum necessary information data packets across the entire network to clear the network channels.

[0095] The conflict control module initiates a dynamic adjustment mechanism, adjusting the high-priority contention window to [8,32] and the low-priority window to [20,76]. Although the overall backoff time increases to cope with conflicts, a window difference of approximately 12 is maintained, ensuring that subsequent high-priority data still has a stronger channel preemption capability than low-priority data.

[0096] Within 50ms after successful transmission, node A broadcasts twice at random intervals to ensure that the central station can still receive complete data even under network jitter.

[0097] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A disaster event priority broadcasting method based on minimum necessary information, characterized in that, Includes the following steps: S101, the monitoring node continuously collects environmental monitoring data. When an abnormal event is detected, an event data packet is constructed. The event data packet adopts the minimum necessary information structure and contains only the key parameters used to quickly determine the event. S102, calculate the priority score of the event data packet according to the preset scoring function, and divide the event data packet into different priorities according to the score value; S103, a channel contention-based access mechanism is used for data broadcasting, and the contention window in the channel access parameters is adjusted based on the priority so that different priority data correspond to different contention window ranges, wherein high priority data corresponds to a smaller contention window to shorten the backoff time; S104 monitors network status in real time and adaptively adjusts data transmission strategies based on network congestion levels.

2. The disaster event priority broadcasting method based on minimum necessary information as described in claim 1, characterized in that, In step S101, the criteria for determining abnormal events include at least one of the following: Amplitude threshold determination, monitoring signal amplitude at the current moment Greater than the preset threshold ; The ratio of short-term average to long-term average is determined when the ratio of the short-term average (STA) to the long-term average (LTA) is greater than a preset ratio threshold. .

3. The disaster event priority broadcasting method based on minimum necessary information as described in claim 1, characterized in that, In S101, the minimum necessary information structure includes: The monitoring node identifier uses a 32-bit code, consisting of an area identifier and a node sequence number; Event timestamp, using 64-bit millisecond-level timestamp; Event type, encoded as a 1-byte enumeration value; Initial motion characteristic parameters, including initial arrival time, initial motion amplitude, and dominant frequency characteristics, are encoded using fixed-point quantization. Data quality labels are discrete levels obtained by mapping the signal-to-noise ratio (SNR). The total length of the event data packet does not exceed 32 bytes.

4. The disaster event priority broadcasting method based on minimum necessary information as described in claim 1, characterized in that, In step S102, the priority scoring function is: ; in, Rate the priority; It is an indicator of time urgency, and its value decreases as time goes on. This is a spatial density index, representing the percentage of monitoring nodes that trigger abnormal events within a preset spatial range; The numerical value corresponding to the data quality marker; These are the weighting coefficients.

5. The disaster event priority broadcasting method based on minimum necessary information as described in claim 1, characterized in that, S103 includes: Before sending data, channel listening is performed. When the channel is idle, transmission is executed, and when the channel is busy, a backoff phase is entered. Different competition window ranges are set according to data priority, and the backoff time is determined based on a random backoff mechanism, so that high-priority data has a shorter average backoff time.

6. The disaster event priority broadcasting method based on minimum necessary information as described in claim 5, characterized in that, In step S103, the contention window range is dynamically adjusted according to data priority and the current network congestion status. When the network congestion level increases, the contention window corresponding to each priority increases as a whole, and a preset contention window difference is maintained between different priorities to improve the channel access success rate of high-priority data under congestion.

7. The disaster event priority broadcasting method based on minimum necessary information as described in claim 1, characterized in that, In step S104, the data transmission strategy is adaptively adjusted according to the network congestion level, including: Calculate the packet loss rate L and the average delay D; When L < 5% and D < 50ms, it is determined to be a normal state, and the minimum necessary information data packet and associated supplementary detailed data are sent. When 5%≤L≤10%, it is determined to be a mild congestion state, and the transmission of low-priority data is restricted. When L > 10%, it is determined to be a severe congestion state, and only the minimum necessary information data packets are sent.

8. The disaster event priority broadcasting method based on minimum necessary information as described in claim 1, characterized in that, Also includes: For event data classified as high priority, repeated broadcasts are performed within a preset time window, with the time interval between two adjacent transmissions being a value randomly selected within a preset range.

9. A disaster event priority broadcasting system based on minimum necessary information, characterized in that, include: The data generation module is used to construct an event data packet when an abnormal event is detected by the monitoring node. The event data packet adopts the minimum necessary information structure. The data classification module is used to calculate priority scores according to a preset scoring function and to classify the event data packets by priority. The transmission control module is used to broadcast data using a channel contention-based access mechanism, perform channel listening before data transmission, adjust the contention window range according to data priority, and perform random backoff control. The adaptive adjustment module is used to monitor the network status in real time and adaptively adjust the data transmission strategy according to the degree of network congestion.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method of any one of claims 1 to 8.

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