Risk transfer crowd report information adaptive priority scheduling transmission method

Abstract

Provided is a hedging transfer crowd reported information adaptive priority scheduling transmission method, user information is collected by multiple collection terminals in real time and sent to a relay terminal, the user information at least includes vital sign information, location information and state information; any collection terminal automatically reports to the relay terminal that the collection terminal has a life abnormality; any collection terminal actively reports to the relay terminal that other collection terminals have a life abnormality; the user information from multiple collection terminals is respectively subjected to key degree quantitative evaluation by the relay terminal, and the key degree weight of each user information is obtained; the user information is subjected to adaptive compression and packaging by the relay terminal according to the key degree weight, and sent to a collection background. The method realizes rapid identification and priority transmission of key information, and solves the problems of untimely transmission of key rescue information and high packet loss rate in a weak network environment.

Description

Technical Field

[0001] This invention belongs to the field of emergency communication and disaster prevention technology, specifically relating to an adaptive priority scheduling and transmission method for reporting information of people being evacuated from disaster areas. Specifically, it relates to a method for intelligent sensing, weight calculation, and adaptive priority scheduling and transmission of vital signs and status information of people being evacuated from disaster areas in mountainous or complex geographical environments, taking into account weak network conditions caused by extreme disasters. Background Technology

[0002] Against the backdrop of climate change, extreme natural disasters such as typhoons, flash floods, and mudslides occur more frequently. In disaster evacuation and relocation efforts, timely and accurate information regarding the location, vital signs, and material needs of affected people is crucial for efficient rescue operations. However, existing technologies have the following limitations.

[0003] Extreme disasters are often accompanied by power outages, road closures, and internet outages. Public network infrastructure is severely damaged, resulting in a communication environment with weak networks, high latency, and high packet loss rates at disaster sites. Traditional communication methods are unable to guarantee reliable data transmission.

[0004] Traditional wristbands or mobile phones only support manual reporting. When people are unconscious due to fainting or injury and unable to operate the device, they cannot send out a distress signal, thus missing the golden rescue time.

[0005] Existing technologies typically use fixed-format data packet transmission, transmitting all data such as location, heart rate, and blood oxygen regardless of the importance of the information. In weak network environments with limited bandwidth, this can easily cause channel congestion, leading to failure to send critical distress messages or excessive delays.

[0006] Existing reporting systems are mostly single-point reporting systems, lacking multi-source collaborative verification mechanisms, making it difficult to identify critical information generated in the first instance due to equipment false alarms or people being in special emergency situations.

[0007] Therefore, there is an urgent need to develop a method that can proactively detect dangers to people's lives and adaptively prioritize transmission in weak network environments based on the importance of information, in order to solve the above problems. Summary of the Invention

[0008] This invention addresses the above-mentioned problems and aims to provide an adaptive priority scheduling and transmission method for reporting information on the relocation of people seeking refuge in weak network environments. By constructing an information weight calculation model and combining it with a multi-source collaborative reporting mechanism, the method achieves rapid identification and priority transmission of critical information, thus solving the problems of untimely transmission and high packet loss rate of critical distress information in weak network environments.

[0009] This method is applied to a scheduling and transmission system consisting of multiple acquisition terminals, relay terminals, and an acquisition backend. The acquisition terminals are networked with the relay terminals.

[0010] The method includes: Multiple data acquisition terminals collect user information in real time and send it to a relay terminal. The user information includes at least vital signs information, location information, and status information. Any data acquisition terminal can automatically report a life-threatening abnormality to the relay terminal; Any data acquisition terminal may proactively report any abnormal life events occurring on other data acquisition terminals to the relay terminal; The relay terminal performs a quantitative assessment of the criticality of user information from multiple collection terminals to obtain the criticality weight of each piece of user information. The quantitative assessment of criticality is calculated using the following formula: W=α·ΔV+β·D+γ·T+δ·C in W represents the weight of criticality. ΔV is the vital signs change factor, representing the rate of change in vital signs and whether they are continuously approaching the alarm threshold. D is the evacuation distance factor, representing the spatial distance between the data collection terminal and the evacuation site, or the distance along the evacuation path. T represents the time urgency factor, indicating the duration for which vital signs continue to exceed the predetermined range. C represents the collaborative reporting confidence factor, indicating the number of times vital signs are reported by different data acquisition terminals within a short period of time. α, β, γ, δ are preset weighting coefficients. In one possible implementation, ΔV is a comprehensive factor whose value is determined by the degree of deviation between the current collected value and the normal threshold, as well as the trend of the deviation within the most recent continuous observation window. The relay terminal adaptively compresses and encapsulates user information according to its importance weight, and sends it to the data collection backend; The data collection terminal is a wearable terminal for personnel undergoing evacuation and relocation. The relay terminal is a handheld relay node terminal used by staff. The data collection backend is the receiving end of the disaster avoidance command center.

[0011] The automatic reporting of a life abnormality by any acquisition terminal to the relay terminal includes: the acquisition terminal judging the user data for abnormality, and if the vital signs continuously approach the alarm threshold within a preset time window or a static state after a fall is detected, then automatic reporting is performed.

[0012] The aforementioned active reporting of life anomalies from other acquisition terminals to the relay terminal by any acquisition terminal includes: active reporting via a pre-made template on the acquisition terminal.

[0013] The adaptive compression encapsulation includes: When the weight of criticality is higher than the first priority threshold, only critical information is compressed and encapsulated. When the importance weight is higher than the second priority threshold but lower than the first priority threshold, all user information is compressed and encapsulated. When the criticality weight is lower than the third priority threshold, only heart rate data is compressed and encapsulated to ensure the transmission link is active.

[0014] The sending to the data collection backend includes: Initialize the send list and set the sliding window according to the transmission rate in the weak network environment; The encapsulated user information data packets are stored in the sending list in such a way that the higher the importance weight, the earlier the position. The sliding window starts at the beginning of the sending list; When the data packet fills the sliding window, the data within the sliding window is sent to the acquisition backend, and the sliding window is moved to the next position.

[0015] The sending to the data collection backend further includes: New data packets are inserted into the sending list according to their importance weight, and the sliding window starts at the beginning of the list. When the scheduled time slice ends, the data packets in the sliding window will be sent directly. When transmission fails, the data packets are classified into a hierarchical queue for buffering and retransmission according to their adaptive compression and encapsulation method. Data packets encapsulating key information are classified into the highest priority queue, which is sent immediately upon being awakened, until the queue is cleared. Set the number of retransmissions for different queues. When the number of retransmissions is exhausted, write the data to the local machine for persistent protection.

[0016] According to the present invention, the following beneficial effects can be obtained: 1. Priority protection of critical information: By constructing a weighted calculation model that includes the rate of change of vital signs, distance and collaborative reporting factors, the most dangerous distress information can be accurately identified. Combined with the sliding window queue-jumping mechanism, the priority transmission of "lifeline" information is ensured under the condition of limited bandwidth in weak network.

[0017] 2. Improved transmission efficiency: An adaptive data pruning mechanism is adopted to dynamically adjust the data packet length according to the criticality of the information, which effectively reduces the transmission of redundant data and reduces the occupation of weak network bandwidth.

[0018] 3. Enhanced collaborative rescue capabilities: The introduction of a collaborative reporting mechanism among staff and the improvement of the accuracy of emergency assessment through multi-source verification have prevented false or missed reports.

[0019] 4. High transmission reliability: Combining hierarchical queue management and state machine-driven retransmission mechanism with local persistent storage, the problem of data loss in extreme environments is solved. Attached Figure Description

[0020] Figure 1 This is a system schematic diagram of the scheduling and transmission system of the present invention.

[0021] Figure 2 This is a flowchart of the scheduling and transmission method of the present invention. Detailed Implementation

[0022] It should be understood that, in any work involving the definition of the scope of the claims of this invention, the specific embodiments provided by this invention can fully support the generalization of equivalent or superior suitable solutions derived therefrom, and the scope of the claims should never be construed as not exceeding the examples themselves. It must also be understood that, with the development of technology and the emergence of new scenarios, the technical solutions provided by the embodiments of this application will also be equally applicable to similar technical problems without any inventive effort by those skilled in the art, and the scope of protection of this invention should not be limited to the examples described in the specific embodiments of this invention.

[0023] The terms "first," "second," etc., used in the specification, claims, and drawings of this application serve to distinguish similar objects and are not necessarily used to describe a specific order or sequence, unless otherwise specified. It should be understood that such use of terminology can be interchanged where appropriate. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, so that a process, method, system, product, or apparatus comprising a series of elements is not necessarily limited to those elements, but may include other elements not explicitly listed or inherent to those processes, methods, products, or apparatus.

[0024] The adaptive priority scheduling transmission method of the present invention is applicable to the reporting of information by people seeking refuge and relocating in weak network environments.

[0025] The weak network environment refers to the working state of the communication link that meets any of the following conditions: 1. Bandwidth limitation: Available uplink transmission rate is consistently below 10 kbps (e.g., LoRa, satellite communications, or severely congested cellular networks). 2. High latency: End-to-end round-trip time (RTT) consistently exceeds 3 seconds; 3. High packet loss rate: The packet transmission failure rate (packet loss rate) consistently exceeds 20%; 4. Intermittent interruption: The number of link interruptions (without ACK response) exceeds 3 times within a consecutive 5-minute time window.

[0026] The adaptive priority scheduling transmission method of the present invention is applicable to scheduling transmission systems comprising multiple acquisition terminals, relay terminals, and acquisition backends. For example... Figure 1 The system shown is a dispatch and transmission system 100 comprising multiple wearable terminals 101, staff handheld relay nodes 102, and a command center system 103.

[0027] Reference Figure 2 The specific implementation methods of the scheduling and transmission method of the present invention will be described in detail.

[0028] Step S1: Real-time acquisition and preprocessing of multimodal data: Wearable devices collect user data in real time through integrated sensors, including vital signs data, location data, and status data. Vital signs include basic data representing vital signs such as heart rate, blood oxygen, and blood pressure. Status data includes wearing status, step count data, and fall data, representing the wearer's current status. The collected data is first analyzed for threshold judgment to determine whether the automatic distress call condition is triggered. If the vital signs continue to approach the alarm threshold within the preset time window or a static state after a fall is detected, an automatic distress call trigger signal is generated and sent from the data acquisition terminal to the data collection terminal, which then sends it to the data acquisition backend.

[0029] Step S2: Calculation of the weight of information criticality: A weight calculation formula is constructed in the embedded system of the data collection terminal device to quantitatively evaluate the criticality of user information from the collection terminal. The formula for calculating the weight W is as follows: W=α·ΔV+β·D+γ·T+δ·C in: ΔV is the vital signs change factor, which represents the rate of change of the vital signs monitoring value at the current time T1 compared with the previous time T0 and whether it continues to approach the alarm threshold. The interval between T1 and T0 can be dynamically set, with a default value of 1 minute. The faster the rate of change, the larger this value.

[0030] Here, ΔV is a comprehensive factor, the value of which is determined by the degree of deviation between the current measurement and the normal threshold, and the trend of this deviation within the most recent consecutive observation windows. The greater the deviation and the more obvious the continuous deterioration trend, the larger the ΔV value. The specific calculation method is as follows: ΔV=A×(1+k•m), where A is the current deviation, m is the number of consecutive deterioration windows, and k is an empirical coefficient.

[0031] D is the distance factor from the evacuation and resettlement point, which means the spatial distance between the current data acquisition terminal's coordinates C1 and the evacuation and resettlement point's coordinates C0. The greater the distance, the greater the weight.

[0032] T represents the time urgency factor, indicating the duration for which vital signs such as heart rate, blood pressure, and blood oxygen on the data acquisition terminal continuously exceed the predetermined range. The predetermined ranges for heart rate, blood pressure, and blood oxygen can be dynamically set. The default values ​​are: heart rate range of 60-80 beats per minute, systolic blood pressure less than or equal to 140, diastolic blood pressure greater than or equal to 60, and blood oxygen saturation greater than or equal to 95.

[0033] C is the collaborative reporting weighting factor, representing the confidence level of collaborative reporting. It indicates that when abnormal vital signs information of the same group of people is reported to the data collection terminal, and then reported to the data collection terminal by multiple independent and nearby collection terminals through a pre-made template within a short time window, the C value will increase significantly. The value of C ranges from 1 to 10. When the value of C is 1, it means that only the current user reported it. The increase value represents the number of times the same abnormal information is reported by other collection terminals, with a maximum of 10.

[0034] α, β, γ, δ are preset weighting coefficients.

[0035] Step S3: Adaptive data compression and encapsulation: The data collection terminal receives collected data from multiple collection terminals networked with it, calculates the weight W, and adaptively compresses and encapsulates the information reported by the collection terminals to ensure that the key information with the highest weight is sent first. When W is higher than the high priority threshold (first priority, red), it is judged as a critical message and the most critical fields are sent: user ID, precise location, wearing information and fall information in the status information, and unnecessary auxiliary information is removed. When W is in the middle range (second priority, orange), send out all information including user ID, location information, vital signs, and status information; When W is below the low priority threshold (level 3 priority, green), only the heart rate data of the current wearer's vital signs is sent to ensure the transmission link is active, and the total length is controlled within the preset bytes.

[0036] Step S4: Prioritize transmission scheduling based on sliding window: The sliding window priority scheduling method is mainly implemented on the data collection terminal. It is used to schedule the transmission of data collected from different acquisition terminals. The main method is to build a sliding window transmission mechanism based on a specific time slice. The time slice length can be dynamically set, with a default value of 1 second. The steps are as follows: Data transmission window initialization and transmission logic: During initialization, the data collection terminal clears the list of data to be sent. Based on the transmission rate R detected in the current weak network environment, the sliding window size Smax = R × 0.5 is set. Before receiving data from the acquisition terminal, the data collection terminal's data transmission list is empty, and the transmission window is initialized simultaneously. After receiving the data packet reported by the acquisition terminal, the data collection terminal stores the data packet in the data transmission list. The sliding window starts at the beginning of the data transmission list. When the data packet fills the sliding window, the data collection terminal sends the data within the sliding window to the back-end platform through the transmission network, ensuring timely data transmission. Simultaneously, the entire sliding window moves backward.

[0037] Data packet sending list sorting and scheduling: After the data collection terminal calculates the weight W of the received data packet, it sorts the data packet in the sending data list to determine the position P of the data packet. In the current sliding window, the higher the weight, the earlier the position. Adaptive sending: 1. When a data packet is received and its weight W is calculated to be the largest data packet in the current sliding window, the data collection terminal automatically inserts the data packet into the front of the sliding window; when a data packet is received and its weight W is calculated to be a data packet that is not the largest data packet in the current sliding window, the data collection terminal inserts the data packet into the data transmission list according to its weight and reorders it.

[0038] 2. When a time slice ends, the sending end directly sends out the data packets arranged in the current sliding window; 3. Once more important information is inserted, the sliding window slides forward, and the remaining non-critical information is sent out in subsequent windows in order of weight.

[0039] Step S5: Queue hierarchical management and breakpoint resumption: 4. If transmission fails, the data packet enters the hierarchical queue management module for buffering and retransmission: 5. Design two levels of independent sending queues (red and green), with each queue independently managing its capacity and sending strategy; The red queue has the highest priority; it sends data immediately upon being woken up and continues until it is cleared. 7. A retransmission state machine is introduced to independently maintain the "pending to send - sending - awaiting retransmission - persistent - acknowledged" state for each data packet. After the number of retransmissions is exhausted, the data is written to the local machine for persistent protection.

[0040] The specific embodiments of this invention are provided to enable those skilled in the art to fully understand the invention and are intended to effectively support the claims of this invention. This section also involves the explanation or definition of the features and terms of the technical solutions of this invention. Those skilled in the art should understand the scope of the claims of this invention in conjunction with the explanation of specific features and terms in the specification, and should not arbitrarily misinterpret the true meaning represented by the features and terms of this invention.

Claims

1. A method for adaptive priority scheduling and transmission of information reported by people undergoing evacuation and relocation, characterized in that, The method includes: Multiple data acquisition terminals collect user information in real time and send it to a relay terminal. The user information includes at least vital signs information, location information, and status information. Any data acquisition terminal can automatically report a life-threatening abnormality to the relay terminal; Any data acquisition terminal may proactively report any abnormal life events occurring on other data acquisition terminals to the relay terminal; The relay terminal performs a quantitative assessment of the criticality of user information from multiple collection terminals to obtain the criticality weight of each piece of user information. The quantitative assessment of criticality is calculated using the following formula: W=α·ΔV+β·D+γ·T+δ·C in W represents the weight of importance. ΔV is the vital signs change factor, representing the rate of change in vital signs and whether they are continuously approaching the alarm threshold. D is the evacuation distance factor, representing the spatial distance between the data collection terminal and the evacuation site, or the distance along the evacuation path. T represents the time urgency factor, indicating the duration for which vital signs continue to exceed the predetermined range. C represents the collaborative reporting confidence factor, indicating the number of times vital signs are reported by different data acquisition terminals within a short period of time. α, β, γ, δ are preset weighting coefficients; The relay terminal adaptively compresses and encapsulates user information according to its importance weight, and sends it to the data collection backend; The data collection terminal is a wearable terminal for personnel undergoing evacuation and relocation. The relay terminal is a handheld relay node terminal used by staff. The data collection backend is the receiving end of the disaster avoidance command center.

2. The method as described in claim 1, wherein, The automatic reporting of a life abnormality by any acquisition terminal to the relay terminal includes: the acquisition terminal performs anomaly judgment on user data, and if the vital signs continuously approach the alarm threshold within a preset time window or a static state after a fall is detected, then it automatically reports the abnormality.

3. The method as described in claim 1, wherein, The step of any acquisition terminal actively reporting a life anomaly to the relay terminal includes: actively reporting via a pre-made template on the acquisition terminal.

4. The method of claim 1, wherein, The ΔV is a comprehensive factor, the value of which is determined by the degree of deviation between the current collected value and the normal threshold and the trend of the deviation within the most recent continuous observation window.

5. The method of claim 1, wherein, The adaptive compression encapsulation includes: When the weight of criticality is higher than the first priority threshold, only critical information is compressed and encapsulated. When the importance weight is higher than the second priority threshold but lower than the first priority threshold, all user information is compressed and encapsulated. When the criticality weight is lower than the third priority threshold, only heart rate data is compressed and encapsulated to ensure the transmission link is active.

6. The method of claim 5, wherein, The sending to the data collection backend includes: Initialize the send list and set the sliding window according to the transmission rate in the weak network environment; The encapsulated user information data packets are stored in the sending list in such a way that the higher the importance weight, the earlier the position. The sliding window starts at the beginning of the sending list; When the data packet fills the sliding window, the data within the sliding window is sent to the acquisition backend, and the sliding window is moved to the next position.

7. The method of claim 6, wherein, The sending to the data collection backend includes: New data packets are inserted into the sending list according to their importance weight, and the sliding window is guaranteed to start at the beginning of the list.

8. The method of claim 6, wherein, The sending to the data collection backend includes: When the scheduled time slot ends, the data packets in the sliding window are sent out directly.

9. The method of claim 6, wherein, The sending to the data collection backend includes: When transmission fails, d will classify the data packets into a hierarchical queue for buffering and retransmission according to their adaptive compression and encapsulation method. Data packets encapsulating key information will be classified into the highest priority queue and sent immediately upon being awakened, until the queue is cleared.

10. The method of claim 9, wherein, Set the number of retransmissions for different queues. When the number of retransmissions is exhausted, write the data to the local machine for persistent protection.

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