Emergency broadcast intelligent early warning system applied to disaster prevention and reduction

Abstract

The invention particularly relates to an emergency broadcast intelligent early warning system applied to disaster prevention and reduction, and relates to the technical field of communication. The redundant communication and self-adaptive switching module is configured to establish a multi-mode communication network, monitor link states in real time and realize intelligent switching and load balancing of communication links based on a dynamic algorithm; an intelligent decision-making and precise broadcasting module; and the emergency broadcast terminal is connected with the offline execution module. According to the invention, a multi-mode communication architecture is established, each link monitors parameters such as signal strength, delay, packet loss rate and the like in real time, and intelligent switching and load balancing are carried out through a dynamic routing algorithm; and meanwhile, on the basis of memory thermal characteristic analysis, link faults are pre-judged in advance, switching is triggered, the success rate of early warning information transmission under extreme disasters is ensured, and the problem of transmission interruption of traditional single link communication under the scenes of power failure, base station damage and the like is solved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to an emergency broadcast intelligent early warning system applied to disaster prevention and reduction. Background Art

[0002] Emergency broadcasting for disaster prevention and mitigation is closely tied to the quality of communication links. Problems with the communication link used for broadcasting can lead to a series of issues, including loss of broadcast content. Currently, although the primary link's communication quality can be monitored to switch between the primary and backup links, the switching logic still needs improvement. When the primary or backup link has the following problems: When memory chips age, professional testing tools may fail to reveal physical defects after a deep scan. This is closely related to the hidden nature of the aging mechanism and the limitations of the testing conditions. In the early stages of memory chip aging (e.g., electron migration, oxide layer degradation), internal atomic migration or circuit micro-damage has not yet formed a fixed short circuit / open circuit. Data errors will only occur under specific conditions (e.g., high temperature, high voltage, high frequency operation). Professional tools (such as MemTest86) are generally recommended to run for more than 48 hours to detect occasional errors. However, if the interval between errors caused by aging is as long as several days or only occurs in specific business scenarios (such as the sudden high load of emergency broadcast encoding), a short test may miss the error. Conventional memory tests only verify data read and write accuracy and do not directly check signal transmission quality (such as voltage fluctuations and timing offsets). Aging can increase internal signal delays within memory chips, leading to timing errors at high frequencies but normal performance at low frequencies (such as the tool's default frequency).

[0003] Therefore, an emergency broadcast intelligent warning system is needed for disaster prevention and mitigation to deal with link switching problems during the communication process and hidden memory failures in the link, which may lead to communication problems in subsequent broadcast intelligent warnings. Based on this, the most appropriate communication link can be selected to ensure the effectiveness of the broadcast. Summary of the Invention

[0004] The purpose of the present invention is to solve the above problems and to propose an emergency broadcast intelligent early warning system for disaster prevention and mitigation.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions: The emergency broadcast intelligent early warning system used for disaster prevention and mitigation includes: The multi-source data fusion and intelligent analysis module is configured to collect multi-source data and, after pre-processing, construct a disaster prediction model to provide a scientific basis for early warning decisions; The redundant communication and adaptive switching module is configured to build a multimodal communication network, monitor link status in real time, and implement intelligent switching and load balancing of communication links based on dynamic algorithms; The intelligent decision-making and precise broadcasting module is configured to build a decision-making engine based on rule reasoning and model prediction, combine big data crowd portraits, mudslides, mountain torrents, and fires to establish a targeted communication model, and realize the generation and release of early warning information through a multi-level approval process; The emergency broadcast terminal and offline execution module are configured as a diversified terminal with a built-in offline execution module and two-way communication function, which automatically triggers an early warning before predicting communication interruption.

[0006] Preferably, the multi-source data fusion and intelligent analysis module specifically includes: Collect a wide range of data through multiple devices; Access data from social media platforms to obtain on-site feedback from the public on disasters, and integrate disaster-related data released by authoritative agencies such as government emergency platforms, meteorological departments, earthquake bureaus, and water conservancy bureaus; Use machine learning and deep learning algorithms to build disaster prediction models; Use recurrent neural networks and their variant, long short-term memory networks, to process time series data to predict the probability of earthquakes and the time of flood outbreaks; through in-depth mining of historical disaster data and real-time monitoring data, combined with geographic information system technology, analyze the propagation patterns and impact range of disasters in different geographical environments, providing a scientific basis for early warning decisions.

[0007] Preferably, the redundant communication and adaptive switching module specifically includes: Build a composite network that includes multiple communication methods; collect key parameters of each communication link in real time; use the signal strength monitoring module to continuously track satellite signals and 5G base station signal strength to determine the stability of the communication link; Using the delay monitoring algorithm, the delay time of data transmission is calculated to evaluate the transmission efficiency of the link. The packet loss rate statistics module accurately calculates the proportion of data packets lost within a certain period of time and quantifies the reliability of the link. Based on dynamic routing algorithms and load balancing technology, when the signal strength of the primary communication link falls below the set threshold, the delay is too high, or the packet loss rate exceeds the specified range, the primary and backup link switching process is quickly initiated; According to the real-time load of each link, data transmission tasks are dynamically allocated to achieve load balancing and improve the overall utilization of the communication network.

[0008] Preferably, the primary / backup link switching logic further includes: After analyzing the thermal conduction of the memory, abnormal values ​​of memory temperature rise are obtained; After analyzing the heat exchange between the memory and the environment, the abnormal value of convective heat transfer is obtained; The communication fault assessment coefficient corresponding to the link is obtained by weighting the abnormal value of memory temperature rise and the abnormal value of convection heat transfer; A communication fault assessment coefficient threshold is preset, and the calculated communication fault assessment coefficient is compared with the communication fault assessment coefficient threshold. If the communication fault assessment coefficient is greater than the communication fault assessment coefficient threshold, it is determined that the link corresponding to the communication fault assessment coefficient has a communication quality problem, and a link switching operation is performed.

[0009] Preferably, the process of obtaining the abnormal value of memory temperature rise includes: Through the equation: ; Get climb rate ; is the heat diffusion term, is the thermal diffusivity, is the temperature gradient, divergence operation It is the conversion of gradient into net heat flux per unit volume; is the internal heat source term, It is the heat generation rate of memory particles due to resistance loss; is the temperature-dependent thermal conductivity, is the temperature-dependent density, is the temperature-dependent specific heat capacity at constant pressure; The memory is divided into regions with a preset size space to obtain sub-regions, and the climbing rate corresponding to each sub-region in each time interval is obtained; a climbing rate threshold is preset, and each climbing rate is compared with the climbing rate threshold. Values ​​less than the climbing rate threshold are eliminated, and only climbing rates greater than the climbing rate threshold are retained; Arrange the climbing rates corresponding to the sub-areas at each time interval in descending order according to their numerical values, extract the largest climbing rate, and use it as the climbing reference rate for the sub-area; Obtain the climbing reference rate of each sub-area in turn, and calculate the difference between the climbing reference rates of adjacent sub-areas in turn, which are recorded as adjacent outliers; A preset adjacent abnormality threshold is used, and each adjacent abnormal value is compared with the adjacent abnormality threshold. Adjacent abnormal values ​​greater than the adjacent abnormality threshold are retained, and the maximum adjacent abnormal value retained is extracted and recorded as the memory temperature climb abnormal value.

[0010] Preferably, the process of obtaining the abnormal value of convective heat transfer includes: By formula: ; Get the heat transfer rate ; in: is the heat flux density on the particle surface; is the temperature difference between the particle surface and the ambient air; The variables in the parameters in the above formula are obtained at preset time intervals, and the heat exchange rate corresponding to each time interval is obtained by calculation through the formula. The obtained heat exchange rates are arranged in ascending order according to the size of the values, and the minimum heat exchange rate is extracted, and its reciprocal is taken to obtain the convective heat transfer anomaly value.

[0011] Preferably, the intelligent decision-making and precise broadcasting module specifically includes: Pre-set decision-making rule bases for various disaster scenarios and formulate corresponding warning levels, evacuation areas, and emergency response measures; Combined with the output of the disaster prediction model, the decision tree algorithm is used to analyze and derive the optimal early warning strategy; Leveraging big data analysis and crowd profiling technology, we establish precise targeted communication models. We collect information on regional population distribution, age structure, language preferences, and communication terminal types to segment audiences into different groups. We then develop personalized early warning information content and communication methods tailored to the characteristics of each group. Design a rigorous multi-level approval process to ensure the accuracy and authority of early warning information.

[0012] Preferably, the emergency broadcast terminal and offline execution module specifically include: The emergency broadcast terminal adopts a variety of design solutions to meet different scenarios and user needs; IP sound columns are suitable for urban streets, squares, and community public places. FM radios, as traditional broadcast receiving devices, are widely used in rural areas and remote mountainous areas. Mobile phone apps, as mobile receiving terminals, are integrated into smartphones used by the public. Users can receive various forms of warning information through the apps. To cope with extreme situations of communication interruption, the emergency broadcast terminal has a built-in offline execution module; when a communication link interruption is detected and a local trigger signal is received, the offline emergency broadcast is automatically started.

[0013] Preferably, the monitoring and self-repair module specifically includes: Build a comprehensive monitoring platform for the entire chain to conduct real-time and comprehensive monitoring of all aspects of the emergency broadcast system, including data collection, communication transmission, and content release; Conduct real-time analysis of monitoring data and establish a fault prediction model to predict potential faults in advance; Build a complete security protection system to ensure the information security and stable operation of the emergency broadcast system.

[0014] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. The present invention builds a multimodal communication architecture, monitors parameters such as signal strength, delay, and packet loss rate in real time on each link, and uses a dynamic routing algorithm for intelligent switching and load balancing. At the same time, based on memory thermal characteristic analysis, it predicts link failures in advance and triggers switching, ensuring the success rate of early warning information transmission in extreme disasters, and solving the transmission interruption problem of traditional single-link communication in scenarios such as power outages and base station damage.

[0015] 2. This invention collects professional monitoring data through equipment such as meteorological satellites, seismic monitors, and hydrological sensors, integrates on-site feedback from social media with authoritative government data, and constructs a full-dimensional data network to fill the limitations of a single data source. After data cleaning, format conversion, and missing value filling, it uses CNN to analyze meteorological cloud maps to identify disaster characteristics and combines GIS technology to deduce the laws of disaster propagation. This provides a scientific basis for emergency decision-making, achieving a leap from empirical warning to accurate prediction, and effectively shortening disaster response time. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Further details, features and advantages of the present application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which: Figure 1 This is a system structure diagram of the present invention. DETAILED DESCRIPTION

[0017] Several embodiments of the present application will be described in more detail below with reference to the accompanying drawings so that those skilled in the art can implement the present application. The present application can be embodied in many different forms and for many different purposes and should not be limited to the embodiments described herein. These embodiments are provided to make the present application comprehensive and complete and to fully convey the scope of the present application to those skilled in the art. The embodiments do not limit the present application.

[0018] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the relevant art and / or the context of this specification, and will not be interpreted in an idealized or overly formal sense unless expressly defined as such herein.

[0019] Example 1 The specific implementation method is combined with the attached Figure 1 Provide detailed explanation.

[0020] Attachment Figure 1A structural block diagram of the emergency broadcast intelligent warning system for disaster prevention and mitigation provided in an embodiment of the present invention shows the connection relationship between the multi-source data fusion and intelligent analysis module, the redundant communication and adaptive switching module, the intelligent decision-making and precise broadcasting module, the emergency broadcast terminal and the offline execution module, and marks the main functional interaction process of each module.

[0021] In this embodiment, it includes: The multi-source data fusion and intelligent analysis module is configured to collect multi-source data and, after pre-processing, use machine learning algorithms and GIS technology to build a disaster prediction model to provide a scientific basis for early warning decisions; Specifically include: We collect a wide range of data through various devices, including using meteorological satellites to monitor cloud changes and collect meteorological data such as air pressure, temperature, and humidity; using seismic monitors to capture seismic waves generated by crustal movement; and using hydrological sensors to measure water levels, flow rates, and other hydrological information. Access data from social media platforms to quickly obtain on-site public feedback on disasters, such as photos, videos, and text descriptions, to supplement the limitations of official monitoring data. In addition, integrate disaster-related data released by authoritative agencies such as government emergency platforms, meteorological departments, earthquake bureaus, and water conservancy bureaus to ensure the comprehensiveness and authority of data sources. The massive amount of raw data collected is cleaned to remove noise and outliers caused by sensor failures and signal interference to ensure data accuracy. Next, data format conversion is performed to unify data from different sources and formats into a standard format that the system can recognize for subsequent processing. At the same time, missing data is filled using interpolation and regression analysis. Based on time series analysis or correlation analysis, missing values ​​are inferred using known data to ensure data integrity and provide a reliable foundation for subsequent analysis. Use machine learning and deep learning algorithms to build disaster prediction models; For example, convolutional neural networks are used to analyze meteorological satellite cloud images to identify the characteristics of typhoon, rainstorm and other disaster cloud systems, and predict their development paths and intensity changes. Recurrent neural networks and their variants, long-short-term memory networks, are used to process time series data, such as earthquake monitoring data and water level change data, to predict the probability of earthquakes and the time of flood outbreaks. Through in-depth mining of historical disaster data and real-time monitoring data, combined with geographic information system technology, the spread patterns and impact range of disasters in different geographical environments are analyzed, providing a scientific basis for early warning decisions. The redundant communication and adaptive switching module is configured to build a multi-modal communication network including satellite, 5G / 6G, medium wave broadcast, and Mesh ad hoc network, monitor the link status in real time, and implement intelligent switching and load balancing of communication links based on dynamic algorithms to ensure continuous transmission of warning information; Specifically include: Build a composite network that includes multiple communication methods; satellite communication uses the Beidou satellite short message system, which has the advantages of global coverage and is not restricted by geographical environment. Even in extreme cases where the ground communication network is paralyzed, it can also realize the transmission of emergency broadcast information, such as in remote mountainous areas, oceans and other areas where public network signals are difficult to cover. It plays a key role. The 5G public network uses its high speed and low latency characteristics to undertake the main large-capacity data transmission tasks, such as high-definition video warning information, detailed disaster graphics and text materials, etc. Medium-wave broadcasting, with its long transmission distance and strong signal penetration ability, is used as a supplementary means of wide-area coverage to ensure that warning information can be transmitted to a wider area in large-scale disaster scenarios. Mesh self-organizing networks are suitable for local disaster-stricken areas. Nodes can self-organize and self-heal to quickly establish temporary communication networks and realize the interaction of on-site emergency command information; Real-time collection of key parameters of each communication link; through the signal strength monitoring module, continuous tracking of satellite signals and 5G base station signal strength to determine the stability of the communication link; The delay monitoring algorithm calculates the delay time during data transmission and evaluates the transmission efficiency of the link. The packet loss rate statistics module accurately calculates the proportion of data packets lost within a certain period of time and quantifies the reliability of the link. These parameters are uploaded to the system's central control unit in real time to provide data support for communication link evaluation and switching decisions. Based on dynamic routing algorithms and load balancing technology, when the primary communication link (such as the 5G public network) experiences a fault such as signal strength falling below a set threshold, excessive latency, or packet loss exceeding a specified range, the primary to backup link switching process is rapidly initiated. By evaluating the real-time status of backup links (such as satellite communications, medium-wave broadcasting, and Mesh ad hoc networks), the link with the best signal quality and transmission performance is selected for switching, ensuring the continuity of early warning information transmission. Dynamically allocate data transmission tasks based on the real-time load of each link to achieve load balancing and improve the overall utilization of the communication network; The primary and backup link switching logic also includes: After analyzing the thermal conduction of the memory, abnormal values ​​of memory temperature rise are obtained; After analyzing the heat exchange between the memory and the environment, the abnormal value of convective heat transfer is obtained; The communication fault assessment coefficient corresponding to the link is obtained by weighting the abnormal value of memory temperature rise and the abnormal value of convection heat transfer; Preset weight factors for the abnormal value of memory temperature rise and the abnormal value of convection heat transfer, calculate the product of the abnormal value of memory temperature rise and the abnormal value of convection heat transfer and their corresponding weight factors, and sum them to obtain a communication fault assessment coefficient; Preset a communication fault assessment coefficient threshold, compare the calculated communication fault assessment coefficient with the communication fault assessment coefficient threshold, and if the communication fault assessment coefficient is greater than the communication fault assessment coefficient threshold, determine that the link corresponding to the communication fault assessment coefficient has a communication quality problem, and perform a link switching operation; The process of obtaining abnormal values ​​of memory temperature rise includes: The reason why memory chips are abstracted as anisotropic three-dimensional thermal conductors is that in actual memory packaging, the thermal conductivity of different material layers such as chips, substrates, and solder joints varies significantly in all directions in three-dimensional space, requiring variable coefficient equations to describe them. Through the equation: ; Get climb rate ; is the rate of change of temperature with time; is the heat diffusion term, is the thermal diffusivity, which reflects the comprehensive ability of the material to conduct and store heat; is the temperature gradient (how fast the temperature changes in space), the divergence operation It converts the gradient into the net heat flux per unit volume, and overall describes the heat diffusion process in space; is the internal heat source term, is the heat generation rate of the memory chip due to resistance loss (positively correlated with the square of the current and the resistance, while the resistance changes with temperature); is the temperature-dependent thermal conductivity, is the temperature-dependent density, is the temperature-dependent specific heat capacity at constant pressure; The memory is divided into regions with a preset size space to obtain sub-regions, and the climbing rate corresponding to each sub-region in each time interval is obtained; a climbing rate threshold is preset, and each climbing rate is compared with the climbing rate threshold. Values ​​less than the climbing rate threshold are eliminated, and only climbing rates greater than the climbing rate threshold are retained; Arrange the climbing rates corresponding to the sub-areas at each time interval in descending order according to their numerical values, extract the largest climbing rate, and use it as the climbing reference rate for the sub-area; Obtain the climbing reference rate of each sub-area in turn, and calculate the difference between the climbing reference rates of adjacent sub-areas in turn, which are recorded as adjacent outliers; Preset an adjacent abnormality threshold, compare each adjacent abnormal value with the adjacent abnormality threshold, retain the adjacent abnormal values ​​that are greater than the adjacent abnormality threshold, and extract the maximum adjacent abnormal value retained, which is recorded as the memory temperature climb abnormal value; By abstracting memory chips into anisotropic three-dimensional thermal conductors, the system accurately reflects the thermal property differences among the chip (silicon, high thermal conductivity), substrate (PCB, low thermal conductivity), and solder joints (metal alloy, with intermediate thermal conductivity) in actual packaging. Using a variable-coefficient heat conduction equation, the system meticulously characterizes the heat diffusion patterns in different directions and regions (e.g., fast heat conduction within the chip plane and slow heat conduction perpendicular to the substrate). This overcomes the problem of the traditional isotropic assumption that cannot reflect actual thermal behavior, enabling thermal analysis to move from macroscopic ambiguity to microscopic precision. The process of obtaining the abnormal value of convective heat transfer includes: Memory does not exist in isolation and needs to exchange heat with the outside world (air, heat sink, PCB board). Therefore, boundary conditions determine how heat flows out of the particles. By formula: ; Get the heat transfer rate ; Strongly correlated with air velocity and memory surface roughness; in: is the heat flux density on the particle surface, and the negative sign indicates that the heat flow direction is in the direction normal to the surface. The direction is opposite, the temperature decreases from the inside of the particle to the outside, and the heat flow is from the inside to the outside; is the thermal conductivity, which can be directly obtained after consulting the data; By discretizing the three-dimensional model of memory particles, the heat conduction equation is solved and the temperature gradient field is directly output; It is the temperature difference between the particle surface and the ambient air, which is the driving force of convective heat transfer; is the memory surface temperature, obtained by an infrared thermal imager; It is the ambient air temperature, which is directly measured and read by a thermocouple or temperature and humidity sensor; Obtain the variables in the parameters in the above formula at preset time intervals, and calculate the heat transfer rate corresponding to each time interval through the formula. Then, arrange the obtained heat transfer rates in ascending order according to the size of the values, extract the minimum heat transfer rate, and take its reciprocal to obtain the convective heat transfer anomaly value; Memory heat dissipation is analyzed uniformly from the perspective of heat flow balance, avoiding misjudgments caused by traditional methods that ignore the impact of internal thermal conductivity. For example, a decrease in the internal thermal conductivity of the particle will reduce both conduction and convection efficiency. This process for obtaining convective heat transfer anomaly values ​​deeply couples internal heat conduction, temperature normal, and surface convective heat transfer in memory to build a closed loop of internal, surface, and ambient heat exchange, achieving a transition from empirical judgment to physical modeling. This process covers the entire parameter chain of internal heat conduction and surface convection, enabling precise tracing of heat dissipation faults. Parameters are collected at dynamic time intervals to adapt to complex and changing actual working conditions. Abnormal values ​​are defined by the inverse of the minimum heat exchange rate, breaking through the hysteresis and environmental interference problems of traditional temperature threshold judgment, and can detect aging trends early. The intelligent decision-making and precise broadcasting module is configured to build a decision-making engine based on rule reasoning and model prediction, and to establish a targeted communication model by combining big data crowd portraits, mudslides, mountain torrents, and fires. Through a multi-level approval process, it can achieve the precise generation and rapid release of warning information. Specifically include: Pre-set decision-making rule bases for various disaster scenarios. For example, for earthquakes of different levels, corresponding warning levels, evacuation areas, and emergency response measures are formulated based on factors such as magnitude, focal depth, epicenter location, and surrounding population density. Combining the output of disaster prediction models, such as flood inundation range predictions and typhoon landfall location and time predictions, with the use of algorithms like decision trees and Bayesian networks, we can analyze and derive the optimal early warning strategy. For example, when a typhoon strikes, we can dynamically adjust the warning level and emergency broadcast content for coastal areas based on the typhoon's path forecast, providing precise guidance to the public on protective measures. Leveraging big data analysis and crowd profiling technology, we establish precise targeted communication models. We collect information on regional population distribution, age structure, language preferences, and communication terminal types to segment audiences into different groups. We then develop personalized early warning information content and communication methods tailored to the characteristics of each group. For the elderly, large fonts, high volume, and easy-to-understand voice broadcasts are used, and these are pushed through traditional channels such as FM radio and community radio. For younger groups, mobile phone apps are used to push warning information with pictures, text, and short videos, and these are widely disseminated through social media platforms. This targeted communication method improves the reception rate and effectiveness of warning information. A rigorous multi-level approval process is designed to ensure the accuracy and authority of early warning information. After the early warning information is generated, it will first be preliminarily reviewed by the grassroots emergency management department to check the integrity and rationality of the information. It will then be submitted to the higher-level competent department for a secondary review, focusing on the appropriateness of the warning level and response measures. In an emergency, a fast approval channel will be activated to simplify the approval process to ensure that the information can be released in the shortest possible time. The system supports seamless connection with the government emergency command center, and quickly transmits approved early warning information to the emergency broadcast release platform through a dedicated interface, enabling information to be released in seconds. At the same time, the system has a release record tracing function, which records in detail the release time, publisher, approval process, and other information of each early warning information, which is convenient for subsequent inquiries and audits. The emergency broadcast terminal and offline execution module are configured to design diversified terminals such as IP sound column, FM radio, mobile phone APP, etc., with built-in offline execution module and two-way communication function, supporting device linkage, automatically triggering early warning before predicting communication interruption and ensuring on-site interaction; Specifically include: The emergency broadcast terminal adopts a variety of design solutions to meet different scenarios and user needs; IP sound columns are suitable for urban streets, squares, and community public places. They receive warning information through network connections, have high loudness and clear sound quality, and can cover a large area. FM radios, as traditional broadcast receiving equipment, are widely used in rural areas and remote mountainous areas. Users only need to tune the frequency to receive warning broadcasts, which is simple and convenient to operate. Mobile phone apps, as mobile receiving terminals, are integrated into the smartphones used by the public in daily life. They have the advantages of timely information push and strong interactivity. Users receive warning information in various forms such as text, voice, pictures, and videos through the app, and can provide feedback on the on-site situation. In addition, customized terminal equipment is developed for special places such as schools, hospitals, factories, etc. to meet their specific emergency broadcasting needs. To cope with extreme situations of communication interruption, the emergency broadcast terminal has a built-in offline execution module. The terminal device pre-stores commonly used warning audio files and graphic materials. When a communication link interruption is detected and a local trigger signal is detected (such as an earthquake sensor detecting earthquake waves or a water level sensor detecting that the water level exceeds the warning value), the offline emergency broadcast is automatically started. Through the built-in local storage chip and independent power supply system (such as solar panels and backup batteries), the terminal device can continue to work in an offline state, playing preset warning information and guiding the public to self-rescue and mutual rescue. The terminal device supports manual triggering of the emergency broadcast function. In an emergency, on-site personnel can use the emergency button on the device to start the broadcast and release distress information and on-site conditions. The local storage chip is a semiconductor device used for local data storage. Its main function is to pre-store key information required for emergency broadcasts (such as warning audio, graphic guides, evacuation route maps, etc.), ensuring that the emergency broadcast terminal can operate offline in the event of communication interruption. The emergency broadcast terminal has a two-way communication function, supporting real-time intercom between on-site personnel and the command center. Through the microphone and speaker on the terminal device, users can "wake up and respond to users" while also making voice calls with the command center to provide feedback on the disaster situation on the scene, casualties, etc., providing first-hand information for the command center to make rescue decisions. In addition, the terminal device can be linked with other emergency equipment through RS485, Bluetooth and other interfaces. For example, it can be connected with an LED display to synchronously display warning text information; connected with an audible and visual alarm to enhance the warning effect; linked with the access control system to achieve personnel evacuation control in emergency situations. Through equipment linkage, a comprehensive and three-dimensional emergency warning and response system is established; The monitoring and self-repair module is configured to monitor the entire chain of data collection, communication transmission, and content publishing in real time, using AI technology to achieve intelligent fault diagnosis and self-repair, and combined with the network security protection system to ensure stable system operation; Specifically include: Build a comprehensive monitoring platform for the entire chain to conduct real-time and comprehensive monitoring of all aspects of the emergency broadcast system, including data collection, communication transmission, and content publishing; at the data collection end, monitor the working status of the sensor, including whether the equipment is online, whether the data collection frequency is normal, whether the collected data is within a reasonable range, etc., to promptly detect sensor failures or data anomalies. In the communication transmission link, monitor the signal strength, delay, packet loss rate and other parameters of each communication link in real time, as well as the operating status of communication equipment (such as routers, switches, satellite communication terminals), such as device temperature, CPU usage, memory occupancy, etc., to ensure the stable operation of the communication network. At the content publishing end, monitor the review progress and publishing status of the warning information, as well as the reception status of the broadcast terminal, such as whether the terminal is online, whether the warning information is successfully received and played, etc. Through a unified monitoring interface, the overall operating status of the system is displayed in a visual manner, which facilitates operation and maintenance personnel to grasp the system status in a timely manner; Conduct real-time analysis of monitoring data and establish a fault prediction model to predict potential faults in advance; for example, through long-term monitoring and analysis of the operating parameters of communication equipment, use deep learning algorithms to build an equipment fault prediction model. When the model predicts that the equipment may fail, it issues an early warning and automatically attempts to repair it. For some common faults, such as network connection interruptions and equipment software anomalies, the system has an automatic repair function, which can restore the normal operation of the system by remotely restarting the equipment, reconfiguring parameters, updating software versions, etc. When encountering a serious fault that cannot be automatically repaired, the system immediately activates a multi-level fault alarm mechanism, notifies the operation and maintenance personnel through various methods such as text messages, emails, and phone calls, and generates a detailed fault report, including information such as the time of occurrence of the fault, the location of the fault, the type of fault, possible causes, etc., to provide a basis for the operation and maintenance personnel to quickly locate and resolve the fault; A comprehensive security protection system is established to ensure the information security and stable operation of the emergency broadcast system. In terms of network security, a next-generation firewall is deployed to block external illegal network access and attacks, conduct in-depth inspections on data entering and leaving the network, and identify and intercept security threats such as malware, network viruses, and hacker attacks. At the same time, an intrusion prevention system (IPS) is used to monitor network traffic in real time and proactively defend against suspicious intrusions, such as blocking port scans, SQL injection attacks, and DDoS attacks. In terms of data security, data in transit is encrypted and the SSL / TLS encryption protocol is used to ensure the security of data in the communication link. Stored data is backed up and data recovery tests are performed regularly to prevent data loss. In addition, user authentication and access control are strengthened, and multi-factor authentication is used to ensure that only authorized personnel can access the system. Different operating permissions are set for different users, and the scope of user access to system resources is strictly limited to ensure system security.

[0022] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The influencing weight factors and specific coefficient values ​​in the formula are set by technical personnel in this field according to actual conditions, and can be adjusted and modified later.

[0023] The above embodiments can be implemented in whole or in part through software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0024] The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. 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 or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0025] The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that contains one or more available media. The available medium can be magnetic media, optical media, or semiconductor media. The semiconductor medium can be a solid-state drive.

[0026] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0027] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways.

[0028] For example, the device embodiments described above are merely illustrative. For example, the division of units described herein is merely a logical functional division. Actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through an interface, or indirect coupling or communication connection between devices or units, which may be electrical, mechanical, or other.

[0029] The units described as separate components may or may not be physically separate, and 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 these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0030] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0031] If the functions are implemented in the form of 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 application, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application.

[0032] The aforementioned storage media include: USB flash drives, mobile hard disks, read-only memories, random access memories, magnetic disks, optical disks, and other media that can store program codes.

[0033] The above description of the embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. Emergency broadcast intelligent early warning system applied to disaster prevention and mitigation, characterized by: include: The multi-source data fusion and intelligent analysis module is configured to collect multi-source data and, after pre-processing, construct a disaster prediction model to provide a scientific basis for early warning decisions; The redundant communication and adaptive switching module is configured to build a multimodal communication network, monitor link status in real time, and implement intelligent switching and load balancing of communication links based on dynamic algorithms; The intelligent decision-making and precise broadcasting module is configured to build a decision-making engine based on rule reasoning and model prediction, combine big data crowd portraits, mudslides, mountain torrents, and fires to establish a targeted communication model, and realize the generation and release of early warning information through a multi-level approval process; The emergency broadcast terminal and offline execution module are configured as a diversified terminal with a built-in offline execution module and two-way communication function, which automatically triggers an early warning before predicting communication interruption.

2. The intelligent early warning system for emergency broadcasting used for disaster prevention and mitigation according to claim 1 is characterized in that: Multi-source data fusion and intelligent analysis module, specifically including: Collect a wide range of data through multiple devices; Access data from social media platforms to obtain on-site feedback from the public on disasters, and integrate disaster-related data released by authoritative agencies such as government emergency platforms, meteorological departments, earthquake bureaus, and water conservancy bureaus; Use machine learning and deep learning algorithms to build disaster prediction models; Use recurrent neural networks and their variant, long short-term memory networks, to process time series data to predict the probability of earthquakes and the time of flood outbreaks; through in-depth mining of historical disaster data and real-time monitoring data, combined with geographic information system technology, analyze the propagation patterns and impact range of disasters in different geographical environments, providing a scientific basis for early warning decisions.

3. The intelligent early warning system for emergency broadcasting used for disaster prevention and mitigation according to claim 1 is characterized in that: Redundant communication and adaptive switching module, including: Build a composite network that includes multiple communication methods; collect key parameters of each communication link in real time; use the signal strength monitoring module to continuously track satellite signals and 5G base station signal strength to determine the stability of the communication link; Using the delay monitoring algorithm, the delay time of data transmission is calculated to evaluate the transmission efficiency of the link. The packet loss rate statistics module accurately calculates the proportion of data packets lost within a certain period of time and quantifies the reliability of the link. Based on dynamic routing algorithms and load balancing technology, when the signal strength of the primary communication link falls below the set threshold, the delay is too high, or the packet loss rate exceeds the specified range, the primary and backup link switching process is quickly initiated; According to the real-time load of each link, data transmission tasks are dynamically allocated to achieve load balancing and improve the overall utilization of the communication network.

4. The intelligent early warning system for emergency broadcasting used for disaster prevention and mitigation according to claim 3 is characterized in that: The primary and backup link switching logic also includes: After analyzing the thermal conduction of the memory, abnormal values ​​of memory temperature rise are obtained; After analyzing the heat exchange between the memory and the environment, the abnormal value of convective heat transfer is obtained; The communication fault assessment coefficient corresponding to the link is obtained by weighting the abnormal value of memory temperature rise and the abnormal value of convection heat transfer; A communication fault assessment coefficient threshold is preset, and the calculated communication fault assessment coefficient is compared with the communication fault assessment coefficient threshold. If the communication fault assessment coefficient is greater than the communication fault assessment coefficient threshold, it is determined that the link corresponding to the communication fault assessment coefficient has a communication quality problem, and a link switching operation is performed.

5. The intelligent early warning system for emergency broadcasting used for disaster prevention and mitigation according to claim 4 is characterized in that: The process of obtaining abnormal values ​​of memory temperature rise includes: Through the equation: ; Get climb rate ; is the thermal diffusion term, is the thermal diffusivity, is the temperature gradient, divergence operation It is the conversion of gradient into net heat flux per unit volume; is the internal heat source term, It is the heat generation rate of memory particles due to resistance loss; is the temperature-dependent thermal conductivity, is the temperature-dependent density, is the temperature-dependent specific heat capacity at constant pressure; The memory is divided into regions with a preset size space to obtain sub-regions, and the climbing rate corresponding to each sub-region in each time interval is obtained; a climbing rate threshold is preset, and each climbing rate is compared with the climbing rate threshold. Values ​​less than the climbing rate threshold are eliminated, and only climbing rates greater than the climbing rate threshold are retained; Arrange the climbing rates corresponding to the sub-areas at each time interval in descending order according to their numerical values, extract the largest climbing rate, and use it as the climbing reference rate for the sub-area; Obtain the climbing reference rate of each sub-area in turn, and calculate the difference between the climbing reference rates of adjacent sub-areas in turn, which are recorded as adjacent outliers; A preset adjacent abnormality threshold is used, and each adjacent abnormal value is compared with the adjacent abnormality threshold. Adjacent abnormal values ​​greater than the adjacent abnormality threshold are retained, and the maximum adjacent abnormal value retained is extracted and recorded as the memory temperature climb abnormal value.

6. The intelligent early warning system for emergency broadcasting used for disaster prevention and reduction according to claim 5, characterized in that: The process of obtaining the abnormal value of convective heat transfer includes: By formula: ; Get the heat transfer rate ; in: is the heat flux density on the particle surface; is the temperature difference between the particle surface and the ambient air; The variables in the parameters in the above formula are obtained at preset time intervals, and the heat exchange rate corresponding to each time interval is obtained by calculation through the formula. The obtained heat exchange rates are arranged in ascending order according to the size of the values, and the minimum heat exchange rate is extracted, and its reciprocal is taken to obtain the convective heat transfer anomaly value.

7. The intelligent early warning system for emergency broadcasting used for disaster prevention and mitigation according to claim 1, characterized in that: Intelligent decision-making and precise broadcasting module, including: Pre-set decision-making rule bases for various disaster scenarios and formulate corresponding warning levels, evacuation areas, and emergency response measures; Combined with the output of the disaster prediction model, the decision tree algorithm is used to analyze and derive the optimal early warning strategy; Leveraging big data analysis and crowd profiling technology, we establish precise targeted communication models. We collect information on regional population distribution, age structure, language preferences, and communication terminal types to segment audiences into different groups. We then develop personalized early warning information content and communication methods tailored to the characteristics of each group. Design a rigorous multi-level approval process to ensure the accuracy and authority of early warning information.

8. The intelligent early warning system for emergency broadcasting used for disaster prevention and mitigation according to claim 1, characterized in that: Emergency broadcast terminal and offline execution module, specifically including: The emergency broadcast terminal adopts a variety of design solutions to meet different scenarios and user needs; IP sound columns are suitable for urban streets, squares, and community public places. FM radios, as traditional broadcast receiving devices, are widely used in rural areas and remote mountainous areas. Mobile phone apps, as mobile receiving terminals, are integrated into smartphones used by the public. Users can receive various forms of warning information through the apps. To cope with extreme situations of communication interruption, the emergency broadcast terminal has a built-in offline execution module; when a communication link interruption is detected and a local trigger signal is received, the offline emergency broadcast is automatically started.

9. The intelligent early warning system for emergency broadcasting used for disaster prevention and mitigation according to claim 1, characterized in that: Monitoring and self-repair module, including: Build a comprehensive monitoring platform for the entire chain to conduct real-time and comprehensive monitoring of all aspects of the emergency broadcast system, including data collection, communication transmission, and content release; Conduct real-time analysis of monitoring data and establish a fault prediction model to predict potential faults in advance; Build a complete security protection system to ensure the information security and stable operation of the emergency broadcast system.

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