Method and device for processing emergency disaster information

Abstract

The present application provides a method and device for processing emergency disaster information, which belongs to the technical field of data processing systems or methods in the new generation of information technology specifically suitable for administrative, commercial, financial, management, supervisory or forecasting purposes. The smart wearable device receives disaster warning information from a server; obtains the user's location information, and obtains user status information, the user status information including at least one of physiological characteristic information, user group characteristics, and portable equipment status; generates personalized risk avoidance warning information for the user based on the disaster warning information, location information, and user status information; and displays the personalized risk avoidance warning information on the display interface of the smart wearable device. Therefore, in the present application, by carrying a smart wearable device, the smart wearable device generates personalized risk avoidance warning information adapted to the user's current status based on conventional disaster warning information and the user's personal information, thereby improving the pertinence and effectiveness of disaster warnings.

Description

Technical Field

[0001] The present application belongs to the technical field of data processing systems or methods in the new generation of information technology that are specifically suitable for administrative, commercial, financial, management, supervisory or forecasting purposes, and in particular relates to a method and device for processing emergency disaster information. Background Art

[0002] Current disaster warning systems typically use universal algorithms to send roughly the same warning information and risk avoidance measures to all users within a given area, making it difficult to provide personalized risk avoidance information. Furthermore, in reality, disasters often occur not just in one place, but may involve multiple disasters simultaneously, such as earthquakes triggering fires, mudslides accompanied by floods, and so on. However, existing systems' algorithms and models are insufficient in analyzing the impact of multi-hazard scenarios on individual users and developing targeted risk avoidance measures. Consequently, they are unable to accurately provide users with comprehensive risk avoidance information in complex disaster situations. Summary of the Invention

[0003] This application provides a method and device for processing emergency disaster information. When a user carries a smart wearable device, the smart wearable device generates personalized risk avoidance warning information adapted to the user's current status based on conventional disaster warning information and the user's personal information, thereby improving the pertinence and effectiveness of disaster warnings.

[0004] In the first aspect, the present application provides a method for processing emergency disaster information, which is applied to smart wearable devices in an emergency disaster system, wherein the emergency disaster system includes the smart wearable device and a server, and the method includes: receiving disaster warning information from the server; obtaining the user's positioning information, and obtaining the user's status information, wherein the user status information includes at least one of physiological characteristic information, user group characteristics, and the status of personal equipment; generating personalized risk avoidance warning information for the user based on the disaster warning information, the positioning information, and the user status information; and displaying the personalized risk avoidance warning information on the display interface of the smart wearable device.

[0005] In some embodiments, the disaster warning information includes the disaster type, disaster occurrence range, and disaster level. The generating of the personalized risk avoidance warning information for the user based on the disaster warning information, the positioning information, and the user status information includes: determining the comprehensive disaster warning range based on the disaster warning information; comparing the positioning information with the boundary data of the comprehensive disaster warning range to determine whether the user is within the comprehensive disaster warning range; if it is detected that the positioning information is within the comprehensive disaster warning range, then generating a first personalized risk avoidance prompt information based on at least one of the user status information, the disaster type, the disaster occurrence range, and environmental data near the positioning information, the first personalized risk avoidance prompt information including at least one of a distress signal, an avoidance route, and an avoidance operation; if it is detected that the positioning information is not within the comprehensive disaster warning range, then generating a second personalized risk avoidance prompt information based on the distance between the positioning information and the comprehensive warning range, the second personalized risk avoidance prompt information including at least one of the diffusion trend dynamics of the comprehensive disaster warning range and preventive measures recommendations.

[0006] In some embodiments, determining the comprehensive disaster warning range based on the disaster prompt information includes: determining a first warning range based on the disaster occurrence range and the disaster level of each disaster type; when it is detected that there is a disaster type and the disaster level is lower than a preset level, determining the first warning range as the comprehensive disaster warning range; when it is detected that there is a disaster type and the disaster level is higher than the preset level, determining the range of secondary disasters that may be caused based on the disaster occurrence range and the disaster level; determining the comprehensive disaster warning range based on the secondary disaster range and the first warning range; when it is detected that there are at least two disaster types, determining the range of secondary disasters that may be caused based on the disaster occurrence range and the disaster level of the at least two disaster types; obtaining an interaction coefficient between the at least two disaster types, the interaction coefficient being used to characterize the degree of enhancement or weakening between the at least two disaster types; correcting the first warning range based on the secondary disaster range and the interaction coefficient to obtain the comprehensive disaster warning range.

[0007] In some embodiments, the first warning range is corrected according to the secondary disaster range and the interaction coefficient to obtain the comprehensive disaster warning range, including: correcting the first warning range of each disaster type according to the interaction coefficient to obtain the second warning range; and performing superposition analysis on the secondary disaster range and the second warning range to generate the comprehensive disaster warning range.

[0008] In some embodiments, the determining of the scope of secondary disasters that may be caused based on the disaster occurrence scope and disaster level of the at least two disaster types includes: obtaining the overlapping area of ​​the disaster occurrence scopes of the at least two disaster types; taking the disaster type with the largest disaster level in the overlapping area as the primary disaster, and taking the remaining disaster types as secondary disasters; determining the type of secondary disasters that may be caused based on the primary disaster and the secondary disasters; determining whether the triggering conditions of the corresponding secondary disaster type are met based on the disaster level of the primary disaster, the disaster level of the secondary disaster, and the environmental data of the overlapping area; if met, determining that the secondary disaster type is generated, and obtaining the secondary disaster level based on the disaster level of the primary disaster and the disaster level of the secondary disaster; determining the scope of the secondary disaster based on the secondary disaster level and the overlapping area; if not met, determining that the secondary disaster type is not generated, and the scope of the secondary disaster is 0.

[0009] In some embodiments, the physiological characteristic information includes the user's basic disease information and physical strength data, the user group characteristics include whether they carry children, elderly people, and pets, and the status of the personal equipment includes whether they carry emergency supplies; the first personalized risk avoidance prompt information is generated based on at least one of the user status information, the disaster type, the disaster occurrence range, and the environmental data near the positioning information, including: determining the user's mobility based on the basic disease information, and determining the user's movement speed based on the physical strength data; detecting that the user has the ability to move and the movement speed is greater than a preset speed; generating at least one risk avoidance route based on the disaster type and the environmental data; determining the restrictions on the risk avoidance route and the degree of influence on the movement speed based on the user group characteristics; determining the user's autonomous survival time based on the status of the personal equipment; selecting a target risk avoidance route from the at least one risk avoidance route based on the movement speed, the restrictions, the degree of influence, and the autonomous survival time, and the first personalized risk avoidance prompt information includes the target risk avoidance route.

[0010] In some embodiments, after determining the user's mobility based on the underlying disease information and determining the user's movement speed based on the physical strength data, the method further includes: detecting that the user is not capable of movement, generating a distress signal based on the positioning information, and sending the distress signal to the server, and the first personalized risk avoidance prompt information includes the distress signal; detecting that the user is capable of movement and the movement speed is less than the preset speed, obtaining the user's environmental data, generating the risk avoidance operation based on the disaster type and the environmental data, and the first personalized risk avoidance prompt information includes the risk avoidance operation.

[0011] In the second aspect, the present application provides a device for processing emergency disaster information, which is applied to smart wearable devices in an emergency disaster system. The emergency disaster system includes the smart wearable device and a server. The device includes: a receiving unit for receiving disaster warning information from the server; and obtaining the user's positioning information, and obtaining the user's status information, the user status information including at least one of physiological characteristic information, user group characteristics, and the status of personal equipment; a processing unit for generating personalized risk avoidance warning information for the user based on the disaster warning information, the positioning information, and the user status information; and displaying the personalized risk avoidance warning information on the display interface of the smart wearable device.

[0012] In a third aspect, the present application provides an emergency disaster system, comprising a smart wearable device and a server, wherein the smart wearable device is used to execute the step instructions in the method described in any one of the first aspects.

[0013] In a fourth aspect, the present application provides a server comprising a processor and a memory, wherein the memory comprises one or more programs, and the one or more programs are called by the processor to execute the step instructions in the method as described in any one of the first aspects.

[0014] As can be seen, in the embodiment of the present application, the smart wearable device receives disaster warning information from the server; obtains the user's location information, and obtains user status information, which includes at least one of physiological characteristics, user group characteristics, and the status of personal equipment; generates personalized risk avoidance warning information for the user based on the disaster warning information, location information, and user status information; and displays the personalized risk avoidance warning information on the display interface of the smart wearable device. Therefore, in the present application, by having the user carry the smart wearable device, the smart wearable device generates personalized risk avoidance warning information adapted to the user's current status based on conventional disaster warning information and the user's personal information, thereby improving the pertinence and effectiveness of disaster warnings. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 A schematic diagram of a disaster emergency system according to an embodiment of the present invention;

[0017] Figure 2 A schematic diagram of another scenario of a disaster emergency system provided in an embodiment of the present application;

[0018] Figure 3 A schematic diagram of the structure of the server provided in the embodiment of the present application;

[0019] Figure 4 A schematic diagram of the structure of the smart wearable device provided in an embodiment of the present application;

[0020] Figure 5 A flowchart of a method for processing emergency disaster information provided in an embodiment of the present application;

[0021] Figure 6 A conventional earthquake early warning prompt interface provided in the embodiment of the present application;

[0022] Figure 7 A schematic diagram of a first prompt interface provided in an embodiment of the present application;

[0023] Figure 8 A schematic diagram of a second prompt interface provided in an embodiment of the present application;

[0024] Figure 9 A schematic diagram of a third prompt interface provided in an embodiment of the present application;

[0025] Figure 10 A schematic diagram of the fourth prompt interface provided in an embodiment of the present application;

[0026] Figure 11 This is a functional unit block diagram of a device for processing emergency disaster information provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0028] The terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements, but may, in some embodiments, also include steps or elements not listed, or may, in some embodiments, include other steps or elements inherent to the process, method, product, or apparatus.

[0029] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0030] In the embodiments of this application, "and / or" describes the relationship between associated objects and indicates that three relationships can exist. For example, "A and / or B" can represent the following three situations: A exists alone; A and B exist simultaneously; and B exists alone. A and B can be singular or plural.

[0031] In the embodiments of the present application, the symbol " / " can indicate that the preceding and following objects are in an "or" relationship. In addition, the symbol " / " can also represent a division sign, that is, performing a division operation. For example, A / B can mean A divided by B.

[0032] In the embodiments of the present application, "at least one item" or similar expressions refers to any combination of these items, including any combination of single items or plural items, and refers to one or more, and multiple refers to two or more. For example, at least one item (item) of a, b, or c can represent the following seven situations: a, b, c, a and b, a and c, b and c, a, b, and c. Among them, each of a, b, and c can be an element or a set containing one or more elements.

[0033] In the embodiments of this application, "equal to" can be used in conjunction with "greater than" and is applicable to the technical solution adopted when "greater than" is used, and can also be used in conjunction with "less than" and is applicable to the technical solution adopted when "less than" is used. When "equal to" is used in conjunction with "greater than", it should not be used in conjunction with "less than"; when "equal to" is used in conjunction with "less than", it should not be used in conjunction with "greater than".

[0034] Current disaster warning systems usually use a universal algorithm to send roughly the same warning information and risk avoidance measures to all users in a certain area. For example, see Figure 6 , Figure 6 A conventional earthquake early warning prompt interface provided in the embodiment of the present application is as follows: Figure 6 As shown, the earthquake early warning prompt interface 6 includes the disaster location, magnitude, premonition intensity, the distance between the current user and the epicenter, and prompt information, such as "Please remain calm, stay away from hanging objects, do not take the elevator, and choose the nearest life triangle or open area to take shelter."

[0035] Clearly, the aforementioned disaster warnings are insufficient to provide users with personalized risk avoidance tips. Furthermore, in reality, disasters often occur infrequently in isolation; multiple disasters may occur simultaneously, such as earthquakes triggering fires, mudslides accompanied by floods, and so on. However, existing system algorithms and models are inadequate in analyzing the impact of multiple disaster scenarios on individual users and developing targeted risk avoidance measures. Consequently, they are unable to accurately provide users with comprehensive risk avoidance tips in complex disaster situations.

[0036] In order to solve the above technical problems, the present application provides a method and device for processing emergency disaster information. By carrying a smart wearable device, the user can generate personalized risk avoidance warning information adapted to the user's current status based on conventional disaster warning information and the user's personal information, thereby improving the pertinence and effectiveness of disaster warnings.

[0037] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0038] See also Figure 1-Figure 2 The emergency disaster system 1 includes a server 10, a smart wearable device 20 worn by a user, and a smart gateway 30.

[0039] In some embodiments, when the public network communication system can be used normally, the server 10 is directly connected to the smart wearable device 20 for communication, such as Figure 1 shown.

[0040] In some embodiments, when the server 10 and the smart wearable device 20 cannot connect, for example, due to an address disaster that destroys the signal base station, the smart wearable device 20 cannot communicate with the server 10. Figure 2 , a smart gateway 30 is set, and the smart wearable device 20 is connected to the server 10 through the smart gateway 30.

[0041] The server 10 may specifically include a server that is applied to one side of the network platform and is responsible for data processing in the background, which can realize functions such as data transmission and data processing. It can be a physical server or a server cluster or distributed system composed of multiple physical servers. In this embodiment, there is no specific limit on the number of servers 10. Alternatively, it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0042] For details, see Figure 3 , Figure 3 A schematic diagram of the structure of the server provided in the embodiment of the present application is shown in FIG. Figure 3 As shown, the server 10 includes a processor 11, a memory 13, a communication interface 12, and one or more programs 131. The one or more programs 131 are stored in the memory 13 and configured to be executed by the processor 11. The one or more programs 131 include instructions for executing any step in the following method embodiment.

[0043] The smart wearable device 20 may include a front-end device applied to the user side that can realize positioning, data collection, data transmission and other functions, and may be a user device such as a mobile phone, handheld device, wearable device, etc. with positioning function. Preferably, Figure 1 The watch is shown.

[0044] For details, see Figure 4 The smart wearable device 20 includes a Beidou positioning module 201 and a user information acquisition module 202. The Beidou positioning module 201 is used to obtain the user's positioning information; the user information acquisition module 202 is used to obtain user status information, and the user status information includes but is not limited to physiological characteristic information, user group characteristics, and personal equipment status, wherein the physiological characteristic information includes but is not limited to the user's basic disease information and physical strength data, the user group characteristics include but are not limited to whether they carry children, the elderly, and pets, and the personal equipment status includes but is not limited to whether they carry emergency supplies. The above-mentioned user status information can be entered into the smart wearable device 20 in advance by the user through voice or text according to his or her own situation, or can be obtained from the corresponding information database through user authorization and user identity information, such as obtaining user medical records through user identity information. Of course, the above-mentioned user status information can also be entered in other suitable ways, and this application does not make specific restrictions on this.

[0045] The smart wearable device 20 also includes various application programming interfaces (APIs) 203 for data interaction with other systems, such as obtaining meteorological data from the meteorological department through API interface 1, obtaining real-time disaster data from the emergency management department through API interface 2, and obtaining terrain and environmental data from the geographic information system and satellite remote sensing data platform through API interface 3.

[0046] The smart wearable device 20 further includes a controller 204, which is configured to execute the step instructions of any one of the following method embodiments.

[0047] See also Figure 5 , Figure 5 A flowchart of a method for processing emergency disaster information provided in an embodiment of the present application is applied to Figure 1The method for the smart wearable device shown includes the following steps S501 to S504:

[0048] Step S501: receiving disaster warning information from the server.

[0049] The disaster warning information herein is the common disaster warning information in the prior art. For example, the disaster warning information includes but is not limited to information such as the disaster type, disaster occurrence range, and disaster level.

[0050] Step S502: Acquire the user's location information and user status information.

[0051] The user status information includes at least one of physiological characteristic information, user group characteristics, and portable equipment status.

[0052] Among them, physiological characteristic information is used to characterize the user's mobility and speed, user group characteristics are used to characterize the degree of positive or negative impact on the speed of movement, and the status of personal equipment is used to characterize the user's survival time alone.

[0053] Step S503: Generate personalized risk avoidance reminder information for the user based on the disaster reminder information, the positioning information, and the user status information.

[0054] In some embodiments, the disaster warning information includes the disaster type, disaster occurrence range, and disaster level. The generating of the personalized risk avoidance warning information for the user based on the disaster warning information, the positioning information, and the user status information includes: determining the comprehensive disaster warning range based on the disaster warning information; comparing the positioning information with the boundary data of the comprehensive disaster warning range to determine whether the user is within the comprehensive disaster warning range; if it is detected that the positioning information is within the comprehensive disaster warning range, then generating a first personalized risk avoidance prompt information based on at least one of the user status information, the disaster type, the disaster occurrence range, and environmental data near the positioning information, the first personalized risk avoidance prompt information including at least one of a distress signal, an avoidance route, and an avoidance operation; if it is detected that the positioning information is not within the comprehensive disaster warning range, then generating a second personalized risk avoidance prompt information based on the distance between the positioning information and the comprehensive warning range, the second personalized risk avoidance prompt information including at least one of the diffusion trend dynamics of the comprehensive disaster warning range and preventive measures recommendations.

[0055] Among them, after the smart wearable device determines the comprehensive disaster warning range based on the disaster prompt information, it compares the boundaries of the user's location information with the comprehensive disaster warning range. If it is detected that the user is within the comprehensive disaster warning range, the user's life and health are threatened to a greater extent, and a first personalized risk avoidance prompt information is generated. The first personalized risk avoidance prompt information is mainly used to assist the user in determining a more targeted risk avoidance plan based on their own location information and personal status, including but not limited to generating at least one of a distress signal, a risk avoidance route, and a risk avoidance strategy. If it is detected that the user is outside the comprehensive disaster warning range, the user's life and health are threatened to a low degree, and different preventive measures suggestions need only be generated based on the distance between the user and the warning range. At the same time, the diffusion trend of the comprehensive disaster warning range can be generated to facilitate users to understand the changes in the disaster situation in a timely manner.

[0056] It can be seen that in this embodiment, different strategies are used to generate different personalized prompt information through the positional relationship between the user positioning information and the comprehensive disaster warning range. This can avoid excessive calculations and prompts, improve computing efficiency, and save computing resources while ensuring the accuracy and effectiveness of the warning prompts.

[0057] The disaster warning information includes the disaster type, disaster occurrence range, and disaster level.

[0058] In some embodiments, determining the comprehensive disaster warning range based on the disaster prompt information specifically includes the following steps a to d:

[0059] Step a: determining a first warning range according to the disaster occurrence range and the disaster level of each disaster type.

[0060] In some embodiments, determining the first warning range according to the disaster occurrence range and the disaster level of each disaster type includes the following steps a1 to a3:

[0061] Step a1, determining the expansion method of the warning range and the range correction coefficient according to the disaster type;

[0062] Step a2, determining a range expansion coefficient according to the disaster level;

[0063] Step a3: determining the first warning range according to the disaster occurrence range, the expansion mode, the range correction coefficient, and the range expansion coefficient.

[0064] Among them, the type of disaster determines how the warning range expands. For example, earthquakes expand in concentric circles with the epicenter as the center, floods expand in strips along the river banks, typhoons expand in fans on both sides of the path, and wildfires expand in fans along the wind.

[0065] Different disasters have different propagation patterns or diffusion patterns, requiring adjustments to the direction or scale of expansion based on their physical characteristics. The range expansion coefficient is a spatial correction factor related to the disaster propagation pattern, reflecting the collective characteristics of the disaster's spread (e.g., circular, banded, fan-shaped, etc.). For example, for earthquakes, the warning area would be expanded by a factor of 1.8 from the disaster site, based on the range expansion coefficient (e.g., 1.8). For floods, the warning area would be expanded by a factor of 1.5 from the disaster site to the banks and / or downstream of the river, based on the range expansion coefficient (e.g., 1.5).

[0066] The higher the disaster level, the greater the destructive power or impact of the disaster, and the base range needs to be expanded proportionally. The range expansion coefficient is an intensity amplification factor related to the energy, duration, or potential destructive power of the disaster. The larger its value, the wider the disaster threat range needs to be covered. For example, for earthquakes, the greater the magnitude (the higher the level), the wider the range of seismic waves propagation, and the larger the area affected by secondary disasters (such as landslides and aftershocks). For typhoons, the higher the level (such as super typhoons), the further the coverage of storm surges, strong winds, and heavy rains will extend outward. For floods, the more the water level exceeds the warning line (the higher the level), the risk of dam failure or inundation may expand exponentially.

[0067] The first warning range is calculated using the following formula:

[0068] The first warning range = disaster occurrence range × range correction coefficient × range expansion coefficient.

[0069] In addition, the first warning range can be modified based on terrain factors, population density, and infrastructure impact.

[0070] It can be seen that in this embodiment, the calculation method of the disaster warning range converts the physical characteristics of the disaster (such as energy intensity and propagation mode) into quantifiable spatial expansion parameters, thereby approximating the diffusion process of the real disaster in terms of geometry and coverage, thereby improving the accuracy of the warning range.

[0071] Step b: When it is detected that a disaster type exists and the disaster level is lower than a preset level, the first warning range is determined as the comprehensive disaster warning range.

[0072] When there is only one type of disaster and the disaster level is low, the possibility of causing secondary disasters is low. Directly determining the comprehensive disaster warning range as the first warning range can reduce the computing power of smart wearable devices, eliminate the complex process of multi-disaster superposition analysis, respond quickly when a disaster occurs, shorten the response time, and avoid delaying the warning prompt due to waiting for secondary disaster assessment.

[0073] Step c: When a disaster type is detected and the disaster level is higher than the preset level, the scope of secondary disasters that may be caused is determined based on the disaster occurrence scope and the disaster level; the comprehensive disaster warning scope is determined based on the secondary disaster scope and the first warning scope.

[0074] When there is only one type of disaster but the disaster level is high, it is easy to cause other secondary disasters. Therefore, smart wearable devices need to further evaluate the scope of possible secondary disasters based on the scope of the disaster and the disaster level, and comprehensively determine the comprehensive disaster warning scope based on the secondary disaster scope and the first warning scope to avoid missing the scope of secondary disasters and make the comprehensive disaster warning scope more comprehensive.

[0075] Step d: Detecting the presence of at least two disaster types, determining the scope of secondary disasters that may be caused based on the disaster occurrence scope and disaster level of the at least two disaster types; obtaining the interaction coefficient between the at least two disaster types, wherein the interaction coefficient is used to characterize the degree of enhancement or weakening between the at least two disaster types; and correcting the first warning scope based on the secondary disaster scope and the interaction coefficient to obtain the comprehensive disaster warning scope.

[0076] When there are at least two types of disasters, other secondary disasters are likely to occur, and at least two types of disasters may also enhance or weaken each other. Therefore, it is necessary to comprehensively consider the scope of secondary disasters that may be caused and the interaction coefficient between at least two types of disasters. The first warning scope can be corrected by the secondary disaster scope and the interaction coefficient to obtain the comprehensive disaster warning scope. This not only improves the accuracy and comprehensiveness of the warning, but also promotes the paradigm shift of disaster management from "single disaster response" to "systematic defense."

[0077] In some embodiments, determining the scope of possible secondary disasters according to the disaster occurrence scope and the disaster level includes the following steps c1 to c5:

[0078] Step c1, obtaining environmental data within the disaster occurrence range, wherein the environmental data at least includes terrain data;

[0079] Step c2, determining the type of secondary disaster that may be caused based on the disaster occurrence range and the environmental data;

[0080] Step c3, determining the probability of a secondary disaster causing the secondary disaster type according to the disaster level;

[0081] Step c4, determining a secondary disaster expansion coefficient according to the disaster level and the environmental data;

[0082] Step c5: determining the scope of the secondary disaster according to the disaster occurrence scope, the disaster level, the probability of the secondary disaster and the secondary disaster expansion coefficient.

[0083] The scope of secondary disasters is calculated according to the following formula:

[0084] A2=λ×A1×α×β+ε

[0085] Where A2 represents the scope of the secondary disaster, A1 represents the scope of the disaster, α represents the probability of a secondary disaster, and β represents the secondary disaster expansion coefficient. The probability of a secondary disaster, α, is positively correlated with the disaster level. λ and ε are function adjustment factors and are constants.

[0086] Before executing the above steps c1 to c5, a first mapping relationship between the disaster level and the probability of secondary disasters being triggered needs to be established.

[0087] For example, see Table 1 below, which is a mapping table of earthquake and landslide probabilities.

[0088]

[0089] Determining the secondary disaster expansion coefficient based on the disaster level and the environmental data includes: the environmental data including terrain data, and assigning a secondary disaster expansion coefficient based on the terrain data and the disaster level. For example, when the slope is greater than 25°, the secondary disaster expansion coefficient β is 1.8, and when the rock and soil type is a loose sedimentary layer, β is 1.5.

[0090] For example, assume a magnitude 7 earthquake occurs with an epicenter radius of 10 kilometers. If the terrain data near the epicenter is mountainous, it is easy to cause landslides. According to Table 1 above, the probability of a disaster level 7 causing a landslide is 60%. The secondary disaster expansion coefficient is determined to be 1.8, then the secondary disaster range = λ×10×0.6×1.8+ε.

[0091] In some embodiments, the comprehensive disaster warning range is determined based on the secondary disaster range and the first warning range, and the comprehensive disaster warning range is calculated using the following formula:

[0092] A 综合 =A1∪A2

[0093] Among them, A 综合 represents the comprehensive disaster warning range, A1 represents the disaster range, A2 represents the secondary disaster range, and “∪” represents the union operation.

[0094] In some embodiments, the first warning range is corrected according to the secondary disaster range and the interaction coefficient to obtain the comprehensive disaster warning range, including: correcting the first warning range of each disaster type according to the interaction coefficient to obtain the second warning range; and performing superposition analysis on the secondary disaster range and the second warning range to generate the comprehensive disaster warning range.

[0095] For each disaster, the first warning range is modified according to the interaction coefficient with other disasters to obtain the second warning range, which is calculated by the following formula:

[0096]

[0097] in, represents the second warning range of the jth disaster type, represents the first warning range of the jth disaster type, A j represents the disaster range of the jth disaster type, W ji It represents the interaction coefficient between the j-th disaster type and the i-th disaster type, j≠i.

[0098] This formula shows that the second warning range of the jth disaster type The first warning range of this disaster type , the scope of the disaster type and all other disaster types according to their respective interaction coefficients W for the jth disaster type. ji The result of the union operation is that it comprehensively considers the superposition effect of other disasters on the impact range of the j-th disaster, and can more accurately reflect the actual impact area of ​​the disaster when multiple disasters occur simultaneously.

[0099] Among them, if at least two disaster types meet the secondary disaster conditions, a secondary disaster range A will be generated. k , a superposition analysis is performed on the secondary disaster range and the second warning range to generate the comprehensive disaster warning range, including:

[0100] The second warning range of the at least two disaster types and the secondary disaster range are combined to generate the comprehensive disaster warning range. The specific formula is as follows:

[0101]

[0102] Among them, A 综合 Indicates the scope of comprehensive disaster warning, Indicates the second warning range of the jth disaster type, the value range of j is [1, N], N is the total number of disaster types, B kis the scope of secondary disasters, K represents the highest disaster level among at least two disaster types that cause secondary disasters, ω is the dynamic expansion factor, β is the level correction factor, the higher the disaster level, the more significant the scope expansion, G j is the disaster level of the jth disaster type.

[0103] Among them, the dynamic expansion factor ,in, It represents the mean of the total disaster level. The mean disaster level is obtained by dividing the sum of the disaster levels of all disaster types that have occurred by the number of disaster types that have occurred. Then it is divided by the highest disaster level that causes secondary disasters to compress the mean disaster level into the interval [0,1]. The closer the mean of the total disaster level is to 1, the higher the overall intensity of the disaster.

[0104] For example, assuming that the earthquake T1 disaster level G1 = 5, the first warning range A1 is obtained according to the above embodiment. （1） = S1. Flood T2 disaster level G2 = 7, according to the above embodiment, the first warning range A2 is obtained. （1） =S2.

[0105] Earthquakes themselves can trigger landslides. In areas where earthquakes and floods interact, the likelihood of landslides increases significantly. The interaction coefficient between earthquakes and floods, W, is 12 =+1.2.

[0106] The second warning range of earthquake disaster is: A1 （2） =A1 （1） ∪(A1×W 12 ) = S1∪1.2×S1;

[0107] The second warning area for flood disasters is: A2 （2） =A2 （1） ∪(A2×W 12 ) = S2∪1.2×S2;

[0108] Assuming that the landslide range B7 = S3, the disaster comprehensive warning range A 综合 = (S1∪S2)∪S3×(1+β·(5+7) / (2×7)=(S1∪S2)∪S3×(1+0.86×β).

[0109] In some embodiments, the step of determining the scope of possible secondary disasters based on the disaster occurrence scope and disaster level of the at least two disaster types includes the following steps d1 to d6:

[0110] Step d1, obtaining the overlapping area of ​​the disaster occurrence ranges of the at least two disaster types;

[0111] Step d2: The disaster type with the highest disaster level in the overlapping area is regarded as the primary disaster, and the remaining disaster types are regarded as secondary disasters;

[0112] Step d3, determining the type of secondary disaster that may be caused based on the primary disaster and the secondary disaster;

[0113] Step d4, determining whether a trigger condition of a corresponding secondary disaster type is met based on the disaster level of the primary disaster, the disaster level of the secondary disaster, and the environmental data of the overlapping area;

[0114] Step d5: If the conditions are met, the secondary disaster type is determined, and the secondary disaster level is obtained according to the disaster level of the primary disaster and the disaster level of the secondary disaster; and the scope of the secondary disaster is determined according to the secondary disaster level and the overlapping area.

[0115] Step d6: If not satisfied, it is determined that the secondary disaster type does not occur, and the secondary disaster range is 0.

[0116] The environmental data includes at least terrain data, and may also include population data, infrastructure data, etc.

[0117] Among them, secondary disasters include at least one. Different levels of primary disasters and secondary disasters may trigger different types of secondary disasters. Generally speaking, the higher the disaster level of the primary disaster and the secondary disaster, the greater the possibility of triggering secondary disasters and the greater the level of secondary disasters. However, it is also necessary to consider the environmental data of overlapping areas. For example, under the dual effects of earthquakes and floods, secondary disasters such as mudslides and landslides are very likely to occur in mountainous areas, but if in plains, the possibility of mudslides and landslides is greatly reduced, and the possibility of floods is greater.

[0118] It can be seen that in this embodiment, based on the disaster levels of the primary disaster and the secondary disaster in combination with the surrounding environmental characteristics, it is possible to determine whether the triggering conditions for the generation of a secondary disaster are met. When the triggering conditions are met, the secondary disaster level is determined based on the disaster levels of the primary disaster and the secondary disaster, and the secondary disaster range is determined based on the secondary disaster level and the overlapping range area; when the triggering conditions are not met, the secondary disaster range is directly determined to be 0, which balances the comprehensiveness and efficiency of the calculation results.

[0119] In some embodiments, the physiological characteristic information includes the user's basic disease information and physical strength data, the user group characteristics include whether they carry children, elderly people, and pets, and the status of the personal equipment includes whether they carry emergency supplies; the first personalized risk avoidance prompt information is generated based on at least one of the user status information, the disaster type, the disaster occurrence range, and the environmental data near the positioning information, including: determining the user's mobility based on the basic disease information, and determining the user's movement speed based on the physical strength data; detecting that the user has the ability to move and the movement speed is greater than a preset speed; generating at least one risk avoidance route based on the disaster type and the environmental data; determining the restrictions on the risk avoidance route and the degree of influence on the movement speed based on the user group characteristics; determining the user's autonomous survival time based on the status of the personal equipment; selecting a target risk avoidance route from the at least one risk avoidance route based on the movement speed, the restrictions, the degree of influence, and the autonomous survival time, and the first personalized risk avoidance prompt information includes the target risk avoidance route.

[0120] Among them, the underlying disease information is used to characterize the user's ability to move. For example, if the user has no underlying disease that affects walking, he or she has the ability to move. If the user has underlying diseases that affect walking, such as lower limb dysfunction, severe arthritis patients, vegetative state, etc., he or she does not have the ability to move.

[0121] Among them, physical strength data can be obtained through smart wearable devices, such as the user's daily fitness data, walking, running data, endurance, maximum exercise heart rate, etc., which are used to determine the user's movement speed when a disaster occurs. People with better physical strength move faster, and people with poor physical strength move slower.

[0122] Among them, user group characteristics are used to characterize the positive or negative restrictions on the speed of movement. For example, when users carry the elderly or children with them, it will restrict the choice of risk avoidance routes and have a negative effect on slowing down the speed of movement.

[0123] Among them, the status of personal equipment is used to represent the user's autonomous survival time. If the user carries emergency supplies, such as food, water, first aid kits, etc., the user's autonomous survival time will be relatively longer, and there may be more flexibility in choosing an evacuation route, such as choosing a route that is slightly farther but safer.

[0124] Among them, a more specific prompt scheme is determined according to the user's ability to move and the speed of movement. Specifically, if the user is not able to move, the smart wearable device generates a distress signal based on the user's location information and sends a distress signal to the server so that external rescue personnel can rescue the user in time. If the user is able to move, but the speed of movement cannot keep up with the evasion speed, it is mainly recommended that the user stay near the original place and find shelter. The smart wearable device generates detailed evasion operations based on the user's location information and the surrounding environment. If the user is able to move and the speed of movement is normal, the main recommendation at this time is to generate an evasion route. The smart wearable device generates at least one evasion route based on the user's location data and nearby terrain data, the scope of the disaster, and the type of disaster. The most suitable target evasion route is selected from at least one route based on the user's speed of movement, restrictions, the degree of impact on the speed of movement, and the autonomous survival time.

[0125] Among them, one possible implementation method is to quantify the user's action speed, restrictions, the degree of influence on the action speed, and the autonomous survival time, and calculate the user's survival probability on each evasion route. At least one evasion route corresponds to at least one survival probability, and the evasion route corresponding to the maximum probability is selected from at least one survival probability as the target evasion route.

[0126] In some embodiments, after determining the user's mobility based on the underlying disease information and determining the user's movement speed based on the physical strength data, the method further includes: detecting that the user is not capable of movement, generating a distress signal based on the positioning information, and sending the distress signal to the server, and the first personalized risk avoidance prompt information includes the distress signal; detecting that the user is capable of movement and the movement speed is less than the preset speed, obtaining the user's environmental data, generating the risk avoidance operation based on the disaster type and the environmental data, and the first personalized risk avoidance prompt information includes the risk avoidance operation.

[0127] For example, assuming the disaster is a typhoon and flood, and the user lives on the 19th floor, if the user is within the comprehensive disaster warning range and the user is unable to move, the user's location information can be obtained through the smart wearable device, a distress signal is generated, and a distress signal is sent to the emergency contact and the external emergency rescue server. At this time, the first prompt interface of the smart wearable device is as follows: Figure 7 As shown, the first prompt interface 7 includes disaster prompt content 71, distress signal content 72, and successful sending prompt content 73.

[0128] If the user is within the comprehensive warning range, has the ability to move, and moves at an abnormally slow speed, the second prompt interface of the smart wearable device will be as follows: Figure 8As shown, the second prompt interface 8 includes the first disaster details 81 and the risk avoidance operation prompt 82, wherein the first disaster details 81 includes information such as the disaster type, disaster level, disaster occurrence range, disaster comprehensive warning range, and user's current location, wherein the risk avoidance operation prompt 82 includes: closing all doors and windows, preparing emergency supplies, and hiding in the corners of indoor load-bearing walls or bathrooms away from windows.

[0129] If the user is within the comprehensive warning range, has the ability to move, and moves at a normal speed, the third prompt interface of the smart wearable device will be as follows: Figure 9 As shown, the third prompt interface 9 includes the second disaster details 91 and the evacuation route 92, wherein the second disaster details 91 includes information such as the disaster type, disaster level, disaster occurrence range, disaster comprehensive warning range, and user's current location. When the user clicks on the evacuation route 92, a specific navigation interface 93 is displayed to guide the user to move to a safe location.

[0130] If the user is outside the comprehensive warning range, the fourth prompt interface of the smart wearable device is as follows: Figure 10 As shown, the fourth prompt interface 10a includes the third disaster details 10a1 and preventive risk avoidance suggestions 10a2, wherein the third disaster details 10a1 includes information such as disaster type, disaster level, disaster occurrence range, disaster comprehensive warning range, and user's current location, and the preventive risk avoidance suggestions 10a2 provide prompts based on specific floors and locations.

[0131] Specifically, gradient prompt content is formed according to the distance between the user and the comprehensive warning range.

[0132] For example, in the critical buffer layer (0-3 km from the boundary), the system displays the dynamic trend of disaster spread, annotates the real-time distance curve between the user's location and the disaster boundary, and displays preventive measures based on the user's environment (such as the environment and floor). For example, in the event of a flood, users in low-lying areas and on lower floors are prompted to take flood prevention measures, and in the event of a tornado, users on higher floors are prompted to take protective measures such as reinforcing doors and windows.

[0133] The secondary impact layer (3-10 km from the boundary) shows the dynamic trend of disaster spread and marks the real-time distance change curve between the user's location and the disaster boundary.

[0134] The outer observation layer (more than 10 kilometers from the border) establishes a disaster information briefing module (update frequency / impact scope / casualties), connects to the official press conference live broadcast channel, and provides a disaster status query portal for different areas.

[0135] Step S504: display the personalized risk avoidance prompt information on the display interface of the smart wearable device.

[0136] As can be seen, in the embodiment of the present application, the smart wearable device receives disaster warning information from the server; obtains the user's location information, and obtains user status information, which includes at least one of physiological characteristics, user group characteristics, and the status of personal equipment; generates personalized risk avoidance warning information for the user based on the disaster warning information, location information, and user status information; and displays the personalized risk avoidance warning information on the display interface of the smart wearable device. Therefore, in the present application, by having the user carry the smart wearable device, the smart wearable device generates personalized risk avoidance warning information adapted to the user's current status based on conventional disaster warning information and the user's personal information, thereby improving the pertinence and effectiveness of disaster warnings.

[0137] The above mainly introduces the solution of the embodiment of the present application from the perspective of the execution process of the method side. It is understandable that, in order to realize the above functions, the server includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment provided herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in a hardware or computer software driven hardware manner depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0138] The embodiments of the present application can divide the server into functional units according to the above method examples. For example, each functional unit can be divided according to each function, or two or more functions can be integrated into a processing module. The above integrated units can be implemented in the form of hardware or in the form of software program modules. It should be noted that the division of units in the embodiments of the present application is schematic and is only a logical functional division. In actual implementation, other division methods can be used.

[0139] In the case of integrated units, see Figure 11 , Figure 11 This is a functional unit block diagram of a device for processing emergency disaster information provided in an embodiment of the present application, which is applied to a smart wearable device in an emergency disaster system. The emergency disaster system includes the smart wearable device and a server. The processing device 110 includes:

[0140] The receiving unit 1101 is configured to receive disaster warning information from the server; obtain user location information; and obtain user status information, wherein the user status information includes at least one of physiological characteristic information, user group characteristics, and portable equipment status;

[0141] The processing unit 1102 is configured to generate personalized risk avoidance prompt information for the user based on the disaster prompt information, the positioning information, and the user status information; and to display the personalized risk avoidance prompt information on the display interface of the smart wearable device.

[0142] As can be seen, in the embodiment of the present application, the smart wearable device receives disaster warning information from the server; obtains the user's location information, and obtains user status information, which includes at least one of physiological characteristics, user group characteristics, and the status of personal equipment; generates personalized risk avoidance warning information for the user based on the disaster warning information, location information, and user status information; and displays the personalized risk avoidance warning information on the display interface of the smart wearable device. Therefore, in the present application, by having the user carry the smart wearable device, the smart wearable device generates personalized risk avoidance warning information adapted to the user's current status based on conventional disaster warning information and the user's personal information, thereby improving the pertinence and effectiveness of disaster warnings.

[0143] In some embodiments, the disaster warning information includes the disaster type, disaster occurrence range, and disaster level. The processing unit 1102 generates personalized risk avoidance warning information for the user based on the disaster warning information, the positioning information, and the user status information, including: determining the disaster comprehensive warning range based on the disaster warning information; comparing the positioning information with the boundary data of the disaster comprehensive warning range to determine whether the user is within the disaster comprehensive warning range; if it is detected that the positioning information is within the disaster comprehensive warning range, then generating a first personalized risk avoidance prompt information based on at least one of the user status information, the disaster type, the disaster occurrence range, and the environmental data near the positioning information, the first personalized risk avoidance prompt information includes at least one of a distress signal, an avoidance route, and an avoidance operation; if it is detected that the positioning information is not within the disaster comprehensive warning range, then generating a second personalized risk avoidance prompt information based on the distance between the positioning information and the comprehensive warning range, the second personalized risk avoidance prompt information including at least one of the diffusion trend dynamics of the disaster comprehensive warning range and preventive measures recommendations.

[0144] In some embodiments, the processing unit 1102 determines the comprehensive disaster warning range based on the disaster prompt information, including: determining a first warning range based on the disaster occurrence range and the disaster level of each disaster type; when it is detected that there is a disaster type and the disaster level is lower than the preset level, the first warning range is determined as the comprehensive disaster warning range; when it is detected that there is a disaster type and the disaster level is higher than the preset level, the range of secondary disasters that may be caused is determined based on the disaster occurrence range and the disaster level; the comprehensive disaster warning range is determined based on the secondary disaster range and the first warning range; when it is detected that there are at least two disaster types, the range of secondary disasters that may be caused is determined based on the disaster occurrence range and the disaster level of the at least two disaster types; obtaining the interaction coefficient between the at least two disaster types, the interaction coefficient is used to characterize the degree of enhancement or weakening between the at least two disaster types; correcting the first warning range based on the secondary disaster range and the interaction coefficient to obtain the comprehensive disaster warning range.

[0145] In some embodiments, the processing unit 1102 corrects the first warning range according to the secondary disaster range and the interaction coefficient to obtain the comprehensive disaster warning range, including: correcting the first warning range of each disaster type according to the interaction coefficient to obtain the second warning range; performing superposition analysis on the secondary disaster range and the second warning range to generate the comprehensive disaster warning range.

[0146] In some embodiments, the processing unit 1102 determines the scope of secondary disasters that may be caused based on the disaster occurrence scope and disaster level of the at least two disaster types, including: obtaining the overlapping area of ​​the disaster occurrence scope of the at least two disaster types; taking the disaster type with the largest disaster level in the overlapping area as the main disaster, and taking the remaining disaster types as secondary disasters; determining the type of secondary disaster that may be caused based on the main disaster and the secondary disaster; determining whether the triggering conditions of the corresponding secondary disaster type are met based on the disaster level of the main disaster, the disaster level of the secondary disaster, and the environmental data of the overlapping area; if met, determining that the secondary disaster type is generated, and obtaining the secondary disaster level based on the disaster level of the main disaster and the disaster level of the secondary disaster; determining the scope of the secondary disaster based on the secondary disaster level and the overlapping area; if not met, determining that the secondary disaster type is not generated, and the scope of the secondary disaster is 0.

[0147] In some embodiments, the physiological characteristic information includes the user's basic disease information and physical strength data, the user group characteristics include whether they carry children, elderly people, and pets, and the status of the personal equipment includes whether they carry emergency supplies; the processing unit 1102 generates a first personalized risk avoidance prompt information based on at least one of the user status information, the disaster type, the disaster occurrence range, and the environmental data near the positioning information, including: determining the user's mobility based on the basic disease information, and determining the user's movement speed based on the physical strength data; detecting that the user has the ability to move and the movement speed is greater than a preset speed; generating at least one risk avoidance route based on the disaster type and the environmental data; determining the restrictions on the risk avoidance route and the degree of influence on the movement speed based on the user group characteristics; determining the user's autonomous survival time based on the status of the personal equipment; selecting a target risk avoidance route from the at least one risk avoidance route based on the movement speed, the restrictions, the degree of influence, and the autonomous survival time, and the first personalized risk avoidance prompt information includes the target risk avoidance route.

[0148] In some embodiments, after the processing unit 1102 determines the user's ability to move based on the underlying disease information and determines the user's movement speed based on the physical strength data, the processing unit 1102 is also used to: detect that the user is not able to move, generate a distress signal based on the positioning information, and send the distress signal to the server, and the first personalized risk avoidance prompt information includes the distress signal; detect that the user is able to move and the movement speed is less than the preset speed, obtain the user's environmental data, and generate the risk avoidance operation based on the disaster type and the environmental data, and the first personalized risk avoidance prompt information includes the risk avoidance operation.

[0149] An embodiment of the present application provides a computer-readable storage medium having a computer program / instruction stored thereon. When the computer program / instruction is executed by a processor, the steps of the method described in any possible embodiment are implemented.

[0150] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0151] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0152] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0153] The units described above 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 according to actual needs to achieve the purpose of the solution of this embodiment.

[0154] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0155] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory and includes a number of instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the above-mentioned methods in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program code.

[0156] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by a program instructing related hardware. The program can be stored in a computer-readable memory, which may include a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0157] The above is a detailed introduction to the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for those skilled in the art, according to the idea of ​​the present application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for processing emergency disaster information, characterized in that: A smart wearable device is applied to an emergency disaster system, wherein the emergency disaster system includes the smart wearable device and a server, and the method includes: receiving disaster prompt information from the server, wherein the disaster prompt information includes disaster type, disaster occurrence range, and disaster level; Obtaining the user's location information and user status information, including physiological characteristics, user group characteristics, and the status of personal equipment; physiological characteristics are used to characterize the user's mobility and speed, user group characteristics are used to characterize the degree of positive or negative impact on the speed of movement, and personal equipment status is used to characterize the user's time to survive alone; generating personalized risk avoidance reminder information for the user according to the disaster reminder information, the positioning information, and the user status information; Displaying the personalized risk avoidance prompt information on the display interface of the smart wearable device; The generating of the user's personalized risk avoidance reminder information according to the disaster reminder information, the positioning information, and the user status information includes: Determine a first warning range according to the disaster occurrence range and the disaster level of each disaster type; When a disaster type is detected and the disaster level is lower than a preset level, the first warning range is determined as a comprehensive disaster warning range; When a disaster type is detected and the disaster level is higher than the preset level, the scope of the secondary disaster caused is determined based on the disaster occurrence range and the disaster level; and the comprehensive disaster warning range is determined based on the secondary disaster range and the first warning range; detecting the presence of at least two disaster types, determining the scope of secondary disasters caused by the at least two disaster types based on their scopes and levels; obtaining an interaction coefficient between the at least two disaster types, the interaction coefficient being used to characterize the degree of enhancement or weakening between the at least two disaster types; and revising the first warning scope based on the secondary disaster scope and the interaction coefficient to obtain the comprehensive disaster warning scope. Comparing the positioning information with the boundary data of the comprehensive disaster warning range to determine whether the user is within the comprehensive disaster warning range; If it is detected that the positioning information is within the comprehensive disaster warning range, a first personalized risk avoidance prompt information is generated based on at least one of the user status information, the disaster type, the disaster occurrence range, and environmental data near the positioning information. The first personalized risk avoidance prompt information includes at least one of a distress signal, a risk avoidance route, and a risk avoidance operation.

2. The method according to claim 1, characterized in that After determining whether the user is within the comprehensive disaster warning range, the method further includes: If it is detected that the positioning information is not within the comprehensive disaster warning range, a second personalized risk avoidance prompt information is generated based on the distance between the positioning information and the comprehensive warning range, and the second personalized risk avoidance prompt information includes at least one of the diffusion trend dynamics of the comprehensive disaster warning range and preventive measures recommendations.

3. The method according to claim 1, characterized in that The step of correcting the first warning range according to the secondary disaster range and the interaction coefficient to obtain the comprehensive disaster warning range includes: Correcting the first warning range of each disaster type according to the interaction coefficient to obtain a second warning range; An overlay analysis is performed on the secondary disaster range and the second warning range to generate the comprehensive disaster warning range.

4. The method according to claim 1, wherein The scope of secondary disasters caused by the at least two types of disasters is determined based on their occurrence scope and disaster levels, including: Obtaining an overlapping area of ​​disaster occurrence ranges of the at least two disaster types; The disaster type with the highest disaster level in the overlapping area is regarded as the primary disaster, and the remaining disaster types are regarded as secondary disasters; Determining the type of secondary disaster caused according to the primary disaster and the secondary disaster; Determining whether a trigger condition of a corresponding secondary disaster type is met according to the disaster level of the primary disaster, the disaster level of the secondary disaster, and environmental data of the overlapping area; If the conditions are met, the secondary disaster type is determined to have occurred, and the secondary disaster level is obtained according to the disaster level of the primary disaster and the disaster level of the secondary disaster; and the scope of the secondary disaster is determined according to the secondary disaster level and the overlapping area; If not, it is determined that the secondary disaster type will not be generated, and the secondary disaster range is 0.

5. The method according to claim 1, wherein The physiological characteristic information includes the user's basic disease information and physical strength data; the user group characteristics include whether they are carrying children, elderly people, and pets; the portable equipment status includes whether they are carrying emergency supplies; The generating of the first personalized risk avoidance prompt information according to at least one of the user status information, the disaster type, the disaster occurrence range, and environmental data near the positioning information includes: determining the user's mobility based on the underlying disease information, and determining the user's movement speed based on the physical strength data; detecting that the user has mobility and that the mobility speed is greater than a preset speed; generating at least one evacuation route according to the disaster type and the environmental data; Determining restrictions on the risk avoidance route and the degree of impact on the action speed based on the user group characteristics; Determining the autonomous survival time of the user according to the status of the portable equipment; A target evasion route is selected from the at least one evasion route according to the action speed, the restriction condition, the impact degree and the autonomous survival time, and the first personalized evasion prompt information includes the target evasion route.

6. The method according to claim 5, characterized in that After determining the user's mobility based on the underlying disease information and determining the user's movement speed based on the physical strength data, the method further includes: detecting that the user is unable to move, generating a distress signal according to the positioning information, and sending the distress signal to the server, wherein the first personalized risk avoidance prompt information includes the distress signal; It is detected that the user has the ability to move and the movement speed is less than the preset speed, the environmental data of the user is obtained, and the risk avoidance operation is generated according to the disaster type and the environmental data. The first personalized risk avoidance prompt information includes the risk avoidance operation.

7. A device for processing emergency disaster information, characterized in that: A smart wearable device used in an emergency disaster system, wherein the emergency disaster system includes the smart wearable device and a server, and the device includes: a receiving unit configured to receive disaster warning information from the server, the disaster warning information including disaster type, disaster occurrence range, and disaster level; and obtain user location information and user status information, the user status information including physiological characteristic information, user group characteristics, and portable equipment status; the physiological characteristic information is used to characterize the user's mobility and speed, the user group characteristics are used to characterize the degree of positive or negative impact on the speed of movement, and the portable equipment status is used to characterize the user's independent survival time; a processing unit, configured to generate personalized risk avoidance prompt information for the user based on the disaster prompt information, the positioning information, and the user status information; and display the personalized risk avoidance prompt information on a display interface of the smart wearable device; In terms of generating personalized risk avoidance prompt information for the user based on the disaster prompt information, the positioning information, and the user status information, the processing unit is further configured to: The first warning range is determined according to the disaster occurrence range and the disaster level of each disaster type; when it is detected that there is a disaster type and the disaster level is lower than the preset level, the first warning range is determined as the comprehensive disaster warning range; when it is detected that there is a disaster type and the disaster level is higher than the preset level, the secondary disaster range caused is determined according to the disaster occurrence range and the disaster level; the comprehensive disaster warning range is determined according to the secondary disaster range and the first warning range; when it is detected that there are at least two disaster types, the secondary disaster range caused is determined according to the disaster occurrence range and disaster level of the at least two disaster types; the interaction coefficient between the at least two disaster types is obtained, and the The interaction coefficient is used to characterize the degree of enhancement or weakening between the at least two disaster types; the first warning range is corrected according to the secondary disaster range and the interaction coefficient to obtain the comprehensive disaster warning range; the positioning information is compared with the boundary data of the comprehensive disaster warning range to determine whether the user is within the comprehensive disaster warning range; when it is detected that the positioning information is within the comprehensive disaster warning range, the first personalized risk avoidance prompt information is generated according to at least one of the user status information, the disaster type, the disaster occurrence range, and the environmental data near the positioning information, and the first personalized risk avoidance prompt information includes at least one of a distress signal, a risk avoidance route, and a risk avoidance operation.

8. A disaster emergency system, characterized in that: The method comprises a smart wearable device and a server, wherein the smart wearable device is used to execute the method according to any one of claims 1 to 6.

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