Rescue information real-time monitoring method and system

Abstract

The invention provides a rescue information real-time monitoring method and system, belongs to the technical field of computer data processing, and is used for autonomously planning an information transmission path when a communication link is damaged by combining distributed judgment with dynamic routing so as to ensure reliable reporting of alarm information under extreme conditions. A disaster assessment function is preposed to an edge calculation module close to an incident place, so that congestion and delay caused by long-distance transmission of all original data to a remote center for processing are avoided, disasters with different degrees and urgencies can be distinguished at the first time and delivered to rescue centers of corresponding levels, and rescue efficiency is improved. According to the invention, the emergency communication guarantee system is adopted, the golden timeliness of rescue response is improved, the problem of communication islands under disasters is effectively solved through the emergency communication guarantee system, the alarm terminal at the bottom layer can spontaneously organize a temporary communication cluster and maintain the regional sensing ability, and the connection reconstruction with the outside is realized through the mode of actively calling the unmanned aerial vehicle and other maneuvering communication power.

Description

Technical Field

[0001] This invention relates to the field of computer data processing technology, and in particular to a method and system for real-time monitoring of rescue information. Background Technology

[0002] Alarm systems, especially central alarm systems used in disaster monitoring and emergency response, are an important component of the modern public safety system. These systems typically consist of numerous front-end sensing terminals deployed across the monitored area, a communication network responsible for data transmission, and a central control platform for centralized processing and decision-making. Their core function is to monitor potential risks or existing disasters in real time and promptly transmit alarm information to the relevant emergency management departments to initiate rapid and effective rescue operations.

[0003] In existing technologies, most mainstream rescue information monitoring methods employ a centralized star or tree network architecture. Specifically, after detecting an anomaly, the front-end alarm terminal generates an alarm signal and reports it directly to a remote, unified central alarm system via a public mobile communication network or a dedicated wired network. Upon receiving the signal, the central alarm system analyzes and verifies the information and dispatches appropriate rescue forces according to a pre-set process.

[0004] However, the aforementioned existing technical solutions have inherent technical flaws in practical applications. During severe disasters such as earthquakes, floods, and large fires, communication infrastructure in disaster areas, such as base stations and fiber optic cables, is highly susceptible to physical damage, leading to the disruption of signal transmission channels. This high dependence on centralized communication links makes the entire alarm system particularly vulnerable in the face of disasters. Once communication is interrupted, alarm information from the front end cannot be delivered, and the central system cannot obtain information about the disaster, resulting in serious delays or complete failure of rescue operations. Summary of the Invention

[0005] This invention provides a method and system for real-time monitoring of rescue information, which uses a combination of distributed judgment and dynamic routing to autonomously plan information transmission paths when communication links are damaged, ensuring reliable reporting of alarm information under extreme conditions.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: Firstly, a method for real-time monitoring of rescue information is provided, the method being applied to a real-time monitoring system for rescue information that includes intelligent sensing terminals, a rescue center, and an emergency communication network, the method comprising: Acquire alarm trigger signals sent by multiple intelligent sensing terminals deployed in the monitoring area, wherein the alarm trigger signals include terminal location information and sensor data; The alarm trigger signal is processed according to the preset disaster severity assessment rules to generate a local disaster assessment result containing disaster severity level and impact range information; Based on the preset rescue center matching rules and the disaster level in the local disaster assessment results, the target rescue center is determined; Acquire a first communication link reflecting the connection status between the intelligent sensing terminal or its relay node and the target rescue center. The first communication link includes communication status information reflecting the connection status between the intelligent sensing terminal or its relay node and the target rescue center. The communication status information of the first communication link is determined. If the communication threshold for establishing a communication link is not met, a second communication link is established. The local disaster assessment result is transmitted to the available rescue information receiving node through the second communication link. The second communication link uses the relay node sequence as a dynamic routing strategy to meet the communication threshold.

[0007] Optionally, the step of generating a dynamic routing policy includes: Based on the communication status information, a network topology state graph containing nodes and weighted links is constructed. The intelligent sensing terminal and the edge computing module are nodes in the undirected graph, and the link quality information between the intelligent sensing terminal and the edge computing module is an edge. The weight of the edge is based on the reciprocal of the transmission delay or a measure of link reliability. Based on the priority information in the local disaster assessment results, the optimal path and alternative relay paths are calculated from the network topology state diagram through optimal path selection, and the optimal path is determined as the dynamic routing strategy.

[0008] Optionally, a first communication link reflecting the intelligent sensing terminal or its relay node and the target rescue center is obtained: Obtain the first link status between the intelligent sensing terminal and its regional convergence point, i.e., the edge computing module; Obtain the second link status between the edge computing module and the upper-level central node; The first link status and the second link status are combined to form the communication status information; The edge computing module is configured to perform the steps of generating the local disaster assessment result and the dynamic routing strategy.

[0009] Optionally, after obtaining the communication status information, the method further includes: When the communication status information indicates that both the first link status and the second link status are unavailable for a sustained period of time; A communication terminal cluster is established among multiple intelligent sensing terminals in the near-field area, and a temporary outbound call node is selected within the communication terminal cluster. The internally generated monitoring data is aggregated to the temporary outbound call node. The near-field area is divided according to the communication capabilities of the multiple intelligent sensing terminals.

[0010] Optionally, after generating the dynamic routing policy, the method further includes: Monitor the real-time communication quality of the relay node sequence determined by the dynamic routing strategy, and generate a path segment health score; When the health score of the path segment is lower than the preset score for determining whether the link is degraded, the route re-decision process is triggered. In the routing re-decision process, a suboptimal path is selected from the alternative relay paths, or a new dynamic routing strategy is recalculated and generated to update the information transmission path.

[0011] Optionally, after forming the communication terminal cluster, the method further includes: The temporary outbound calling node assesses the disconnection status of the communication terminal cluster and its aggregated monitoring data to generate a cluster-level disaster risk index. When the cluster-level disaster risk index indicates that the number of disconnected communication terminal clusters exceeds a preset high-risk threshold, a mobile relay summoning request is generated. The mobile relay summoning request includes the travel path and communication protocol of the mobile communication relay unit. The mobile relay call request is broadcast to the outside through the coordinated communication capabilities of the communication terminal cluster.

[0012] Optionally, after broadcasting the mobile relay call request, the method further includes: In response to the mobile relay call request, the mobile communication relay unit is dispatched to move to the estimated location of the communication terminal cluster; A temporary directional communication link is established between the mobile communication relay unit and the communication terminal cluster; Complete disaster data packets are obtained from the cluster of communication terminals through the directional communication link.

[0013] Optionally, before the step of processing the alarm trigger signal, the method further includes: Receive preliminary alarm data broadcast from the plurality of intelligent sensing terminals via near-field communication; The preliminary alarm data is identified to identify multiple alarm signals caused by the same physical disaster event, so as to filter out isolated false alarm signals and cluster them to generate one or more alarm clusters; A fused sensing information is generated based on the alarm cluster, and the step of generating a local disaster assessment result is performed based on the fused sensing information.

[0014] Optionally, the step of generating alarm clusters includes: Extract event type, location, and signal strength characteristics from the preliminary alarm data; Calculate the correlation between location distance and signal strength between different alarm data, and generate a weighted feature distance metric that characterizes the possibility of alarm sources being from the same source; Based on a correlation threshold, alarm data with high weighted feature distance metrics are aggregated into alarm clusters, and their core location and diffusion range are estimated.

[0015] Secondly, a real-time rescue information monitoring system is provided, configured to include: Multiple intelligent sensing terminals are used to generate and send alarm trigger signals containing terminal location information and sensor data; At least an edge computing module is communicatively connected to the intelligent sensing terminal, which integrates the following: The disaster assessment module is used to process the alarm trigger signal according to the assessment rules to generate a local disaster assessment result; The routing decision module is used to obtain communication status information and generate dynamic routing policies based on routing decision rules when the communication link is unavailable. A multi-level rescue center system is used to receive the local disaster assessment results transmitted according to the dynamic routing strategy; The routing decision module works in conjunction with the disaster assessment module, enabling the edge computing module to autonomously plan the information reporting path based on real-time network conditions immediately after generating a disaster assessment.

[0016] Thirdly, an electronic device is provided, comprising: a processor and a memory; the memory is used to store a computer program, which, when executed by the processor, causes the electronic device to perform the real-time monitoring method and system for rescue information described in the first aspect.

[0017] In one possible design, the electronic device described in the third aspect may further include a transceiver. This transceiver may be a transceiver circuit or an interface circuit. The transceiver can be used for communication between the electronic device described in the third aspect and other electronic devices.

[0018] In the embodiments of the present invention, the electronic device described in the third aspect may be a terminal, or a chip (system) or other component or assembly disposed in the terminal, or a system containing the terminal.

[0019] Fourthly, a computer-readable storage medium is provided, comprising: a computer program or instructions; when the computer program or instructions are executed on a computer, the computer causes the computer to perform the real-time monitoring method and system for rescue information described in the first aspect.

[0020] In summary, the above methods and systems have the following technical effects: This invention significantly improves the resilience and reliability of the entire alarm system during disasters by performing localized intelligent judgment and dynamic routing decisions at the network edge. When traditional centralized communication links are damaged due to disasters, it autonomously finds and establishes temporary information relay paths to ensure that critical alarm information is not lost. This guarantees that the central alarm system can still receive disaster reports from the front end even in extremely harsh environments. Through rapid processing and hierarchical reporting of alarm information, the delay from the occurrence of an alarm event to the response of rescue forces is greatly shortened. By forwarding the disaster assessment function to the edge computing module near the incident site, all original... The congestion and delays caused by the long-distance transmission of initial data to remote centers for processing enable the differentiation of disaster situations of varying severity and urgency in the first instance, and deliver them to the appropriate level of rescue centers, thus improving the golden timeliness of rescue response. Through the emergency communication support system, the problem of communication islands under disaster is effectively solved. The alarm terminals at the bottom level can spontaneously organize into temporary communication clusters to maintain regional awareness capabilities, and by actively summoning mobile communication forces such as drones, the connection with the outside world is rebuilt. Through the ground-air coordinated communication relay mechanism, a lifeline is opened for disaster-stricken areas in communication blind spots, ensuring that distress messages can be ultimately delivered. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating the real-time monitoring method for rescue information provided in an embodiment of the present invention. Detailed Implementation

[0022] The following will be combined with the appendix Figure 1 The technical solutions in this invention will be described below.

[0023] In this embodiment of the invention, "instruction" can include direct and indirect instructions, as well as explicit and implicit instructions. The information indicated by a certain piece of information is called the information to be instructed. In specific implementation, there are many ways to instruct the information to be instructed, such as, but not limited to, directly instructing the information to be instructed, such as the information to be instructed itself or its index. It can also indirectly instruct the information to be instructed by instructing other information, where there is a correlation between the other information and the information to be instructed. It can also instruct only a part of the information to be instructed, while the other parts are known or pre-agreed upon. For example, the instruction of specific information can be achieved by using a pre-agreed (e.g., protocol-defined) arrangement of various pieces of information, thereby reducing instruction overhead to some extent. Simultaneously, common parts of various pieces of information can be identified and uniformly indicated to reduce the instruction overhead caused by individually indicating the same information.

[0024] Furthermore, the specific indication method can also be any existing indication method, such as, but not limited to, the above-mentioned indication methods and their various combinations. Specific details of various indication methods can be found in existing technologies, and will not be elaborated upon here. As described above, for example, when multiple pieces of information of the same type need to be indicated, the indication methods for different pieces of information may differ. In specific implementation, the required indication method can be selected according to specific needs. This embodiment of the invention does not limit the selected indication method; therefore, the indication methods involved in this embodiment of the invention should be understood to cover various methods that enable the party to be indicated to obtain the information to be indicated.

[0025] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information messages sent separately, and the sending period and / or timing of these sub-information messages can be the same or different. The specific sending method is not limited in this embodiment of the invention. The sending period and / or timing of these sub-information messages can be predefined, for example, according to a protocol, or configured by the sending device by sending configuration information to the receiving device.

[0026] "Predefined" or "pre-configured" can be achieved by pre-saving corresponding codes, tables, or other means that can be used to indicate relevant information in the device. This embodiment of the invention does not limit the specific implementation method. "Saving" can refer to saving in one or more memories. These memories can be separate installations or integrated into the encoder, decoder, processor, or electronic device. Alternatively, some memories can be separately installed, while others are integrated into the decoder, processor, or electronic device. The type of memory can be any form of storage medium, and this embodiment of the invention does not limit this.

[0027] In the embodiments of this invention, "protocol" may refer to a protocol family in the field of communication, a standard protocol with a similar protocol family frame structure, or a related protocol applied to a future real-time monitoring method and system for rescue information. The embodiments of this invention do not specifically limit this.

[0028] In this embodiment of the invention, descriptions such as "when," "under the circumstances," "if," and "if" all refer to the device making corresponding processing under certain objective circumstances, and are not limited to a specific time. They do not require the device to make a judgment action during implementation, nor do they imply any other limitations.

[0029] In the description of the embodiments of the present invention, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can represent A or B. "And / or" in the embodiments of the present invention is merely a description of the relationship between the related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. Furthermore, in the description of the embodiments of the present invention, unless otherwise stated, "multiple" refers to two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. Additionally, to facilitate a clear description of the technical solutions of the embodiments of the present invention, the terms "first" and "second" are used in the embodiments of the present invention to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first," "second," etc., do not limit the quantity or order of execution, and that "first," "second," etc., are not necessarily different. Furthermore, in the embodiments of this invention, words such as "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this invention should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner for ease of understanding.

[0030] The network architecture and business scenarios described in the embodiments of this invention are for the purpose of more clearly illustrating the technical solutions of the embodiments of this invention, and do not constitute a limitation on the technical solutions provided by the embodiments of this invention. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of this invention are also applicable to similar technical problems.

[0031] Figure 1 This is a flowchart illustrating the method provided in an embodiment of the present invention. The specific process of this real-time monitoring method for rescue information is as follows: Acquire alarm trigger signals sent by multiple intelligent sensing terminals deployed in the monitoring area, wherein the alarm trigger signals include terminal location information and sensor data; The alarm trigger signal is processed according to the preset disaster severity assessment rules to generate a local disaster assessment result containing disaster severity level and impact range information; Based on the preset rescue center matching rules and the disaster level in the local disaster assessment results, the target rescue center is determined; Acquire a first communication link reflecting the connection status between the intelligent sensing terminal or its relay node and the target rescue center. The first communication link includes communication status information reflecting the connection status between the intelligent sensing terminal or its relay node and the target rescue center. The communication status information of the first communication link is determined. If the communication threshold for establishing a communication link is not met, a second communication link is established. The local disaster assessment result is transmitted to the available rescue information receiving node through the second communication link. The second communication link uses the relay node sequence as a dynamic routing strategy to meet the communication threshold.

[0032] The intelligent sensing terminal is a low-power embedded device with wireless communication capabilities. It integrates multiple sensors, such as smoke sensors, temperature sensors, vibration sensors, or high-definition cameras, and is equipped with a GPS or Beidou positioning module to obtain the terminal's location information. When the sensor reading exceeds a preset threshold, the microcontroller in the terminal will immediately encapsulate an alarm trigger signal and send it out through its built-in wireless communication module, such as a module that supports ZigBee, LoRa, or Bluetooth Mesh.

[0033] Optionally, the step of generating a dynamic routing policy includes: Based on the communication status information, a network topology state graph containing nodes and weighted links is constructed. The intelligent sensing terminal and the edge computing module are nodes in the undirected graph, and the link quality information between the intelligent sensing terminal and the edge computing module is an edge. The weight of the edge is based on the reciprocal of the transmission delay or a measure of link reliability. Based on the priority information in the local disaster assessment results, the optimal path and alternative relay paths are calculated from the network topology state diagram through optimal path selection, and the optimal path is determined as the dynamic routing strategy.

[0034] By constructing the network topology, link quality information between each edge computing module or smart sensing terminal and its neighboring nodes is collected in real time or periodically. This information includes RSSI (Signal Strength Indicator) values, LQI (Link Quality Indicator) values, and packet transmission success rates. This information is then aggregated to construct a weighted undirected graph G = (V, E), where V represents the set of all nodes in the network, including smart sensing terminals and edge computing modules; and E represents the set of valid communication links between the nodes.

[0035] For each edge e(u, v) ∈ E in the graph, its weight W(u, v) is dynamically calculated based on the link quality information. The weight value can be set as the reciprocal of the transmission delay or a measure of link reliability. The higher the weight, the better the path. Secondly, dynamic matching of path selection algorithms is performed. Based on the urgency of the current task, the most suitable computing tool is selected to find the best path. The priority information contained in the local disaster assessment results will be parsed. For example, a disaster level of "major" corresponds to high priority.

[0036] Based on this priority, a path selection algorithm is chosen from a pre-defined library. For example, for high-priority tasks, the system might choose Dijkstra's algorithm, which guarantees finding the globally optimal path, although it has a slightly higher computational cost, but ensures that information is transmitted in the fastest or most reliable way.

[0037] For low-priority tasks, a greedy algorithm or a distributed Bellman-Ford algorithm, which are faster in computation and consume fewer resources, may be chosen to balance efficiency and network load.

[0038] The execution path calculation and strategy generation process transforms the algorithm's calculation results into specific, executable device actions. Once a matching algorithm is selected, it is used to perform calculations on the constructed network topology state graph G. The starting point of the calculation is the node that currently holds the local disaster assessment results, and the ending point is the set of all known and currently available rescue information receiving nodes; The algorithm outputs a series of alternative relay paths, each consisting of a series of node IDs and a comprehensive path cost C. The path cost C can be expressed by the formula: ; Where f is a function used to combine the weights W(u, v) of all links on the path, such as simple weight summation; The system selects the lowest-cost or highest-performance route from these alternative relay paths and formats it as a dynamic routing policy. This strategy includes an ordered list of node IDs, indicating the relay nodes that a packet should pass through in sequence. The current node then sends a packet containing the local disaster assessment result and the dynamic routing strategy to the next node in the list, thus initiating the relay process.

[0039] Optionally, a first communication link reflecting the intelligent sensing terminal or its relay node and the target rescue center is obtained: Obtain the first link status between the intelligent sensing terminal and its regional convergence point, i.e., the edge computing module; Obtain the second link status between the edge computing module and the upper-level central node; The first link status and the second link status are combined to form the communication status information; The edge computing module is configured to perform the steps of generating the local disaster assessment result and the dynamic routing strategy.

[0040] Optionally, after obtaining the communication status information, the method further includes: When the communication status information indicates that both the first link status and the second link status are unavailable for a sustained period of time; A communication terminal cluster is established among multiple intelligent sensing terminals in the near-field area, and a temporary outbound call node is selected within the communication terminal cluster. The internally generated monitoring data is aggregated to the temporary outbound call node. The near-field area is divided according to the communication capabilities of the multiple intelligent sensing terminals.

[0041] The determination of temporary nodes is based on a preset weight, which emphasizes the node's endurance, communication stability and network centrality. All terminals will independently calculate and compare scores, and the node with the highest score will be determined as the temporary outbound calling node. All terminals participating in the election, together with the newly elected temporary outbound calling node, constitute a communication terminal cluster.

[0042] Optionally, after generating the dynamic routing policy, the method further includes: Monitor the real-time communication quality of the relay node sequence determined by the dynamic routing strategy, and generate a path segment health score; When the health score of the path segment is lower than the preset score for determining whether the link is degraded, the route re-decision process is triggered. In the routing re-decision process, a suboptimal path is selected from the alternative relay paths, or a new dynamic routing strategy is recalculated and generated to update the information transmission path.

[0043] Specifically: The composition of communication status information is defined hierarchically. By accurately distinguishing and quantifying the health status of different levels in the network, refined data input is provided for subsequent routing decisions. The communication status information is divided into two dimensions: first link status and second link status. The first link status describes the underlying sensing network, that is, the communication quality between multiple intelligent sensing terminals and an edge computing module. The edge computing module obtains this status by listening to the periodic heartbeat packets or service data packets sent by the intelligent sensing terminals within its coverage area. If it is within the preset detection period; For example, if a terminal fails to receive a data packet for three consecutive cycles, each lasting 5-10 seconds, or if the RSSI value of the received data packet signal strength remains below a preset availability threshold (e.g., -85dBm), then the first link state corresponding to that terminal is marked as unavailable. The second link state describes the backbone backhaul network, i.e., the communication quality between the edge computing module and one or more preset upstream nodes. The edge computing module is configured by hardware and software to have a dual role: a regional data analysis center and a network routing decision center. As a data analysis center, it executes processing steps based on preset evaluation rules, aggregates alarm trigger signals from subordinate intelligent sensing terminals, runs algorithms such as multi-source information fusion, cross-validates the data, and generates local disaster assessment results containing accurate disaster level and impact range information.

[0044] As the routing decision center, the edge computing module executes dynamic routing strategies using the real-time acquired first and second link states. After generating a local disaster assessment result, the module immediately queries its own second link state. If the link to the primary node is in good condition, it sends the data directly. If the link is unavailable, it queries the link states between itself and other peer edge computing modules and initiates a routing algorithm to calculate an optimal path that relays the data through other edge computing modules.

[0045] To quantify link status, the edge computing module can calculate a comprehensive link quality score S, which can be expressed by the formula: ; Where S is the final link quality score; wR and wP are preset weighting coefficients, representing the importance of signal strength and data packet success rate, and the sum of wR and wP is 1; fR is the normalized signal strength factor calculated based on RSSI value; fP is the normalized transmission success rate factor calculated based on packet loss rate. The edge computing module compares the calculated score S with multiple preset thresholds to accurately determine the link status as excellent, usable, or unusable. This determination result constitutes the direct basis for executing dynamic routing decisions. Optionally, after forming the communication terminal cluster, the method further includes: The temporary outbound calling node assesses the disconnection status of the communication terminal cluster and its aggregated monitoring data to generate a cluster-level disaster risk index. When the cluster-level disaster risk index indicates that the number of disconnected communication terminal clusters exceeds a preset high-risk threshold, a mobile relay summoning request is generated. The mobile relay summoning request includes the travel path and communication protocol of the mobile communication relay unit. The mobile relay call request is broadcast to the outside through the coordinated communication capabilities of the communication terminal cluster.

[0046] Optionally, after broadcasting the mobile relay call request, the method further includes: In response to the mobile relay call request, the mobile communication relay unit is dispatched to move to the estimated location of the communication terminal cluster; A temporary directional communication link is established between the mobile communication relay unit and the communication terminal cluster; Complete disaster data packets are obtained from the cluster of communication terminals through the directional communication link.

[0047] Specifically: for terminal users who are isolated in communication and face high-risk disasters, there is a final guarantee mechanism to request air communication support from the outside world. By "ground-air linkage", information barriers are broken down to ensure that the highest priority distress messages can be transmitted. The system determines the conditions for generating a mobile relay call request, ensuring that the high-cost operation of "summoning drones" is only initiated in the most urgent and unavoidable circumstances. After the communication terminal cluster is formed, its temporary outbound call node is responsible not only for internal coordination but also for the continuous assessment of the entire cluster's environment. This node confirms through internal communication that all members within the cluster are unable to establish connections with any external nodes (including other clusters or edge computing modules), and that this complete disconnection has persisted for more than a "deep disconnection threshold," such as 10-15 minutes. Simultaneously, the temporary outbound call node comprehensively assesses the disaster data collected within the cluster, generating a cluster-level disaster risk index. : ; in, This is the number of terminals that triggered alarms within the cluster. It is the maximum value among all alarm signal strengths, and η and θ are preset weighting coefficients. When Exceeding a preset "high-risk threshold" R high When the conditions for deep disconnection are met simultaneously, the temporary outbound call node will determine that the current situation meets the call conditions and immediately generate a mobile relay call request. The cluster-level disaster risk index... The number of terminals that trigger alarms within the cluster and maximum signal strength All showed a positive correlation.

[0048] Optionally, before the step of processing the alarm trigger signal, the method further includes: Receive preliminary alarm data broadcast from the plurality of intelligent sensing terminals via near-field communication; The preliminary alarm data is identified to identify multiple alarm signals caused by the same physical disaster event, so as to filter out isolated false alarm signals and cluster them to generate one or more alarm clusters; A fused sensing information is generated based on the alarm cluster, and the step of generating a local disaster assessment result is performed based on the fused sensing information.

[0049] Specifically, by cross-validating and fusing multi-source sensing information, the accuracy of disaster assessment is improved, and single-point false alarms and noise interference are effectively filtered out. Thus, before generating local disaster assessment results, a highly reliable fused sensing information that has been preliminarily refined is formed.

[0050] The system performs the collection of preliminary alarm data. When one or more smart sensing terminals trigger an alarm, they immediately broadcast a simplified preliminary alarm data packet to their neighboring nodes via near-field communication protocols such as Bluetooth Mesh or ZigBee. The data packet contains the most essential information, such as terminal ID, event type code, timestamp, raw sensor readings, and geographic location coordinates; Edge computing modules or temporary outbound call nodes in self-organizing mode will continuously listen to and receive such broadcast data from all smart sensing terminals within their coverage area, and establish a dynamically updated list of original events. Perform spatiotemporal correlation analysis and cross-validation. The engineering objective of this step is to identify multiple alarm signals triggered by the same physical disaster event, eliminate false alarms, and calculate the spatiotemporal correlation degree D for any two preliminary alarm data i and j in the original event list. The formula can be expressed as: ; Where Δt is the absolute value of the difference between the timestamps of the two events, and Δd is the Euclidean distance between the geographical locations of the two terminals; α and β are preset weighting coefficients used to adjust the influence of time and spatial distance on the correlation calculation.

[0051] Set a correlation threshold For example, 0.8.

[0052] When D is greater than At that time, the two alarm data are considered to be strongly correlated, meaning they may have been triggered by the same disaster event.

[0053] It can identify "alarm clusters," which are a group of alarm events that are highly concentrated in time and space. Conversely, if a certain alarm data cannot establish a strong correlation with any other alarm data within a certain time window, such as within 30 seconds, it will be marked as a suspected false alarm and placed in a low priority or ignored directly.

[0054] The verified and associated "alarm cluster" data are integrated into a single, more informative fusion sensing information object.

[0055] For each identified alarm cluster, the system will perform data fusion processing.

[0056] For example, the location of the disaster center can be estimated by a weighted average of the locations of all terminals within the cluster, with the weights based on the signal strength or reliability of each terminal.

[0057] The extent of a disaster's impact can be initially defined by the distance between the two furthest terminals within the cluster; The intensity or type of a disaster can be determined by integrating data from multiple sensors of the same or different types within the cluster.

[0058] For example, the assessment of a fire event can combine the concentration readings of multiple smoke sensors and the temperature readings of multiple temperature sensors. The resulting fused perception information is a structured object, which is no longer a scattered single-point alarm, but a description of a disaster event that has been verified from multiple points and has a preliminary range and intensity estimate. This fused perception information will serve as the direct and sole input for the subsequent generation of local disaster assessment results, improving the accuracy and reliability of decision-making.

[0059] Through quantitative analysis and clustering algorithms, the raw, discrete alarm data stream is transformed into structured alarm clusters that reflect the real disaster events, effectively filtering out false alarms and providing high-quality input for subsequent disaster assessment.

[0060] Optionally, the step of generating alarm clusters includes: Extract event type, location, and signal strength characteristics from the preliminary alarm data; Calculate the correlation between location distance and signal strength between different alarm data, and generate a weighted feature distance metric that characterizes the possibility of alarm sources being from the same source; Based on a correlation threshold, alarm data with high weighted feature distance metrics are aggregated into alarm clusters, and their core location and diffusion range are estimated.

[0061] In one embodiment, a real-time rescue information monitoring system is provided, configured to include: Multiple intelligent sensing terminals are used to generate and send alarm trigger signals containing terminal location information and sensor data; At least an edge computing module is communicatively connected to the intelligent sensing terminal, which integrates the following: The disaster assessment module is used to process the alarm trigger signal according to the assessment rules to generate a local disaster assessment result; The routing decision module is used to obtain communication status information and generate dynamic routing policies based on routing decision rules when the communication link is unavailable. A multi-level rescue center system is used to receive the local disaster assessment results transmitted according to the dynamic routing strategy; The routing decision module works in conjunction with the disaster assessment module, enabling the edge computing module to autonomously plan the information reporting path based on real-time network conditions immediately after generating a disaster assessment.

[0062] Among them, the multi-level rescue center system serves as the "brain" and command center of the entire rescue operation. It receives disaster intelligence from the front-end network and dispatches rescue resources. It is usually composed of server clusters deployed in different geographical locations with different command permissions.

[0063] It maintains connection with the front-end edge computing module through various means such as wide area network and satellite communication. When it receives the local disaster situation assessment results processed by the edge computing module and transmitted through dynamic routing, it will immediately display them on the command screen and trigger automated or semi-automated emergency response plans, such as matching the nearest rescue team and planning rescue routes. Through a layered architecture, information is ensured to be refined and processed at each level during transmission, achieving an efficient closed loop from initial perception to final decision-making. The electronic device provided in this embodiment of the invention, exemplarily, can be a network device, or a chip (system) or other component or assembly that can be disposed in a network device. The electronic device may include a processor. Optionally, the electronic device may also include a memory and / or a transceiver. The processor is coupled to the memory and transceiver, for example, by means of a communication bus connection.

[0064] The following is a detailed introduction to the various components of the electronic device: In this context, the processor is the control center of the electronic device. It can be a single processor or a collective term for multiple processing elements. For example, a processor can be one or more central processing units (CPUs), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention, such as one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs).

[0065] Alternatively, the processor can perform various functions of the electronic device, such as the methods described above, by running or executing software programs stored in memory and by calling data stored in memory.

[0066] In a specific implementation, as one example, the processor may include one or more CPUs, such as CPU0 and CPU1.

[0067] In a specific implementation, as one example, the electronic device may also include multiple processors. Each of these processors may be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0068] The memory is used to store the software program that executes the solution of the present invention, and the execution is controlled by the processor. The specific implementation method can be referred to the above method embodiment, and will not be repeated here.

[0069] Optionally, the memory can be read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, random access memory (RAM) or other types of dynamic storage devices capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory can be integrated with the processor or exist independently and coupled to the processor through an interface circuit of an electronic device; the embodiments of the present invention do not specifically limit this.

[0070] A transceiver is used for communication with other electronic devices. For example, if the electronic device is a terminal, the transceiver can be used to communicate with a network device or with another terminal device. Similarly, if the electronic device is a network device, the transceiver can be used to communicate with a terminal or with another network device.

[0071] Optionally, the transceiver may include a receiver and a transmitter. The receiver is used to implement the receiving function, and the transmitter is used to implement the sending function.

[0072] Optionally, the transceiver can be integrated with the processor or exist independently and coupled to the processor through the interface circuit of the electronic device. This embodiment of the invention does not specifically limit this.

[0073] It is understandable that the structure of an electronic device does not constitute a limitation on the electronic device. An actual electronic device may include more or fewer components, or combine certain components, or have different component arrangements.

[0074] Furthermore, the technical effects of the electronic device can be referred to the technical effects of the method described in the above method embodiments, and will not be repeated here.

[0075] It should be understood that the processor in the embodiments of the present invention can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0076] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDRSDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DRRAM).

[0077] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0078] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0079] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0080] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0081] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0082] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0083] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0084] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0085] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0086] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0087] 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 variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should 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 method for real-time monitoring of rescue information, characterized in that, The method is applied to a real-time monitoring system for rescue information that includes intelligent sensing terminals, a rescue center, and an emergency communication network. The method includes: Acquire alarm trigger signals sent by multiple intelligent sensing terminals deployed in the monitoring area, wherein the alarm trigger signals include terminal location information and sensor data; The alarm trigger signal is processed according to the preset disaster severity assessment rules to generate a local disaster assessment result containing disaster severity level and impact range information; Based on the preset rescue center matching rules and the disaster level in the local disaster assessment results, the target rescue center is determined; Acquire a first communication link reflecting the connection status between the intelligent sensing terminal or its relay node and the target rescue center. The first communication link includes communication status information reflecting the connection status between the intelligent sensing terminal or its relay node and the target rescue center. The communication status information of the first communication link is determined. If the communication threshold for establishing a communication link is not met, a second communication link is established. The local disaster assessment result is transmitted to the available rescue information receiving node through the second communication link. The second communication link uses the relay node sequence as a dynamic routing strategy to meet the communication threshold.

2. The real-time monitoring method for rescue information according to claim 1, characterized in that, The steps for generating a dynamic routing policy include: Based on the communication status information, a network topology state graph containing nodes and weighted links is constructed. The intelligent sensing terminal and the edge computing module are nodes in the undirected graph, and the link quality information between the intelligent sensing terminal and the edge computing module is an edge. The weight of the edge is based on the reciprocal of the transmission delay or a measure of link reliability. Based on the priority information in the local disaster assessment results, the optimal path and alternative relay paths are calculated from the network topology state diagram through optimal path selection, and the optimal path is determined as the dynamic routing strategy.

3. The real-time monitoring method for rescue information according to claim 2, characterized in that, Obtain the first communication link reflecting the intelligent sensing terminal or its relay node and the target rescue center: Obtain the first link status between the intelligent sensing terminal and its regional convergence point, i.e., the edge computing module; Obtain the second link status between the edge computing module and the upper-level central node; The first link status and the second link status are combined to form the communication status information; The edge computing module is configured to perform the steps of generating the local disaster assessment result and the dynamic routing strategy.

4. The real-time monitoring method for rescue information according to claim 3, characterized in that, After obtaining the communication status information, the method further includes: When the communication status information indicates that both the first link status and the second link status are unavailable for a sustained period of time; A communication terminal cluster is established among multiple intelligent sensing terminals in the near-field area, and a temporary outbound call node is selected within the communication terminal cluster. The internally generated monitoring data is aggregated to the temporary outbound call node. The near-field area is divided according to the communication capabilities of the multiple intelligent sensing terminals.

5. The real-time monitoring method for rescue information according to claim 2, characterized in that, After generating the dynamic routing policy, the following is also included: Monitor the real-time communication quality of the relay node sequence determined by the dynamic routing strategy, and generate a path segment health score; When the health score of the path segment is lower than the preset score for determining whether the link is degraded, the route re-decision process is triggered. In the routing re-decision process, a suboptimal path is selected from the alternative relay paths, or a new dynamic routing strategy is recalculated and generated to update the information transmission path.

6. The real-time monitoring method for rescue information according to claim 4, characterized in that, After forming the communication terminal cluster, the method further includes: The temporary outbound calling node assesses the disconnection status of the communication terminal cluster and its aggregated monitoring data to generate a cluster-level disaster risk index. When the cluster-level disaster risk index indicates that the number of disconnected communication terminal clusters exceeds a preset high-risk threshold, a mobile relay summoning request is generated. The mobile relay summoning request includes the travel path and communication protocol of the mobile communication relay unit. The mobile relay call request is broadcast to the outside through the coordinated communication capabilities of the communication terminal cluster.

7. The real-time monitoring method for rescue information according to claim 6, characterized in that, Following the broadcast of the aforementioned mobile relay call request, the following is also included: In response to the mobile relay call request, the mobile communication relay unit is dispatched to move to the estimated location of the communication terminal cluster; A temporary directional communication link is established between the mobile communication relay unit and the communication terminal cluster; Complete disaster data packets are obtained from the cluster of communication terminals through the directional communication link.

8. The real-time monitoring method for rescue information according to claim 7, characterized in that, Before the step of processing the alarm trigger signal, the method further includes: Receive preliminary alarm data broadcast from the plurality of intelligent sensing terminals via near-field communication; The preliminary alarm data is identified to identify multiple alarm signals caused by the same physical disaster event, so as to filter out isolated false alarm signals and cluster them to generate one or more alarm clusters; A fused sensing information is generated based on the alarm cluster, and the step of generating a local disaster assessment result is performed based on the fused sensing information.

9. The real-time monitoring method for rescue information according to claim 8, characterized in that, The steps for generating alarm clusters include: Extract event type, location, and signal strength characteristics from the preliminary alarm data; Calculate the correlation between location distance and signal strength between different alarm data, and generate a weighted feature distance metric that characterizes the possibility of alarm sources being from the same source; Based on a correlation threshold, alarm data with high weighted feature distance metrics are aggregated into alarm clusters, and their core location and diffusion range are estimated.

10. A real-time rescue information monitoring system, applied to the real-time rescue information monitoring method according to any one of claims 1-9, characterized in that, Configured to include: Multiple intelligent sensing terminals are used to generate and send alarm trigger signals containing terminal location information and sensor data; At least an edge computing module is communicatively connected to the intelligent sensing terminal, which integrates the following: The disaster assessment module is used to process the alarm trigger signal according to the assessment rules to generate a local disaster assessment result; The routing decision module is used to obtain communication status information and generate dynamic routing policies based on routing decision rules when the communication link is unavailable. A multi-level rescue center system is used to receive the local disaster assessment results transmitted according to the dynamic routing strategy; The routing decision module works in conjunction with the disaster assessment module, enabling the edge computing module to autonomously plan the information reporting path based on real-time network conditions immediately after generating a disaster assessment.

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