Emergency disaster information processing method and device

Abstract

The invention provides an emergency disaster information processing method and device, and belongs to the technical field of a data processing system or method specially suitable for administrative, commercial, financial, management, supervision or prediction purposes in a new generation of information technology. An intelligent wearable device receives disaster prompt information from a server; positioning information of a user is obtained, user state information is obtained, and the user state information comprises at least one of physiological feature information, user group features and carry-on equipment states; generating personalized risk avoiding prompt information of the user according to the disaster prompt information, the positioning information and the user state information; and displaying the personalized risk avoiding prompt information on a display interface of the intelligent wearable device. Therefore, according to the disaster early warning method and device, the intelligent wearable device is carried by the user, the intelligent wearable device generates the personalized risk avoiding prompt information matched with the current state of the user according to the conventional disaster prompt information and the personal information of the user, and the pertinence and effectiveness of disaster early warning are improved.

Description

Technical Field

[0001] This application belongs to the technical field of data processing systems or methods specifically applicable to administrative, commercial, financial, management, supervision, or prediction purposes in the new generation of information technology, and particularly relates to a method and device for processing emergency disaster information. Background Art

[0002] Currently, the disaster warning systems usually use general algorithms to send roughly the same warning information and risk avoidance measures to all users within a certain area, and it is difficult to provide personalized risk avoidance prompt content for users. Moreover, in reality, disasters often do not occur alone, and there may be situations where multiple disasters occur simultaneously, such as earthquakes triggering fires, mudslides accompanied by floods, etc. However, the existing system algorithms and models have deficiencies in analyzing the impact on individual users and targeted risk avoidance measures in multi-disaster scenarios, and cannot accurately provide users with comprehensive risk avoidance prompts in complex disaster situations. Summary of the Invention

[0003] This application provides a method and device for processing emergency disaster information. By having users carry smart wearable devices, the smart wearable devices generate personalized risk avoidance prompt information adapted to the current state of the users based on conventional disaster prompt information and the personal information of the users, improving the pertinence and effectiveness of disaster warnings.

[0004] In a first aspect, this application provides a method for processing emergency disaster information, 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 method includes: receiving disaster prompt information from the server; obtaining the positioning information of the user, and obtaining user status information, where 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 prompt information for the user according to the disaster prompt information, the positioning information, and the user status information; and displaying the personalized risk avoidance prompt information on the display interface of the smart wearable device.

[0005] In some embodiments, the disaster warning information includes the disaster type, the disaster occurrence range, and the disaster level. Generating the personalized disaster 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 according to 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; when it is detected that the positioning information is within the comprehensive disaster warning range, generating a first personalized disaster avoidance warning 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, where the first personalized disaster avoidance warning information includes at least one of a distress signal, an evacuation route, and disaster avoidance operations; when it is detected that the positioning information is not within the comprehensive disaster warning range, generating a second personalized disaster avoidance warning information based on the distance between the positioning information and the comprehensive warning range, where the second personalized disaster avoidance warning information includes at least one of the diffusion trend dynamics of the comprehensive disaster warning range and preventive measure suggestions.

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

[0007] In some embodiments, correcting the first warning range according to the range of possible secondary disasters 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; performing superposition analysis on the range of possible secondary disasters and the second warning range to generate the comprehensive disaster warning range.

[0008] In some embodiments, determining the range of possible secondary disasters based on the disaster occurrence range and disaster level of the at least two types of disasters includes: obtaining the overlapping area of the disaster occurrence ranges of the at least two types of disasters; taking the disaster type with the highest disaster level in the overlapping area as the primary disaster, and taking the remaining disaster types as secondary disasters; determining the possible types of secondary disasters based on the primary disaster and the secondary disasters; determining whether the trigger conditions for the corresponding types of secondary disasters are met according to the disaster level of the primary disaster, the disaster level of the secondary disasters, and the environmental data of the overlapping area; if met, determining that the type of secondary disaster is generated, and obtaining the secondary disaster level based on the disaster level of the primary disaster and the disaster level of the secondary disasters; determining the range of the secondary disaster according to the secondary disaster level and the overlapping area; if not met, determining that the type of secondary disaster is not generated, and the range of the secondary disaster is 0.

[0009] In some embodiments, the physiological characteristic information includes the user's underlying disease information and physical strength data, the user group characteristics include whether there are children, the elderly, and pets, and the status of the portable equipment includes whether emergency supplies are carried; generating the first personalized hazard avoidance prompt information according to at least one of the user status information, the type of disaster, the disaster occurrence range, and the environmental data near the positioning information includes: determining the user's mobility according to the underlying disease information, and determining the user's movement speed according to the physical strength data; detecting that the user has mobility and the movement speed is greater than a preset speed; generating at least one hazard avoidance route according to the type of disaster and the environmental data; determining the restriction conditions for the hazard avoidance route and the influence degree on the movement speed according to the user group characteristics; determining the user's independent survival duration according to the status of the portable equipment; selecting a target hazard avoidance route from the at least one hazard avoidance route according to the movement speed, the restriction conditions, the influence degree, and the independent survival duration, and the first personalized hazard avoidance prompt information includes the target hazard avoidance route.

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

[0011] Second aspect, the present application provides a processing device for emergency disaster information, which is applied to an intelligent wearable device in an emergency disaster system. The emergency disaster system includes the intelligent wearable device and a server. The device includes: a receiving unit for receiving disaster prompt information from the server; and obtaining the positioning information of the user, and obtaining the user status information, where the user status information includes at least one of physiological characteristic information, user group characteristics, and the status of the equipment carried with the user; a processing unit for generating personalized risk avoidance prompt information for the user according to the disaster prompt information, the positioning information, and the user status information; and displaying the personalized risk avoidance prompt information on the display interface of the intelligent wearable device.

[0012] Third aspect, the present application provides an emergency disaster system, including an intelligent wearable device and a server. The intelligent wearable device is used to execute the step instructions in any one of the methods in the first aspect.

[0013] Fourth aspect, the present application provides a server, including a processor and a memory. The memory includes one or more programs, and the one or more programs are called by the processor to execute the step instructions in any one of the methods in the first aspect.

[0014] It can be seen that in the embodiments of the present application, the intelligent wearable device receives disaster prompt information from the server; obtains the positioning information of the user, and obtains the user status information, where the user status information includes at least one of physiological characteristic information, user group characteristics, and the status of the equipment carried with the user; generates personalized risk avoidance prompt information for the user according to the disaster prompt information, the positioning information, and the user status information; and displays the personalized risk avoidance prompt information on the display interface of the intelligent wearable device. Therefore, in the present application, by the user carrying the intelligent wearable device, the intelligent wearable device generates personalized risk avoidance prompt information adapted to the current status of the user according to the conventional disaster prompt information and the personal information of the user, improving the pertinence and effectiveness of disaster warning. Description of the Drawings

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required to be used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to these drawings.

[0016] Figure 1 It is a schematic diagram of the scenario of the emergency disaster system provided by the embodiments of the present application; Figure 2 It is a schematic diagram of the scenario of another emergency disaster system provided by the embodiments of the present application; Figure 3Schematic diagram of the structure of the server provided by the embodiment of the present application; Figure 4 Schematic diagram of the structure of the smart wearable device provided by the embodiment of the present application; Figure 5 Flow schematic diagram of a method for processing emergency disaster information provided by the embodiment of the present application; Figure 6 Conventional earthquake early warning prompt interface provided by the embodiment of the present application; Figure 7 Schematic diagram of the first prompt interface provided by the embodiment of the present application; Figure 8 Schematic diagram of the second prompt interface provided by the embodiment of the present application; Figure 9 Schematic diagram of the third prompt interface provided by the embodiment of the present application; Figure 10 Schematic diagram of the fourth prompt interface provided by the embodiment of the present application; Figure 11 Functional unit block diagram of a device for processing emergency disaster information provided by the embodiment of the present application. Detailed implementation manners

[0017] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0018] The terms "first", "second", etc. in the specification and claims of the present application and the above accompanying drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but in some embodiments also includes steps or units not listed, or in some embodiments also includes other steps or units inherent to these processes, methods, products or devices.

[0019] References to "embodiments" in this specification mean that the specific features, structures, or characteristics described in connection with the embodiments can be included in at least one embodiment of the present application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment each time, nor are they independent or alternative embodiments mutually exclusive of other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0020] The "and / or" in the embodiments of the present application describes the association relationship of 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; B exists alone. Among them, A and B can be singular or plural.

[0021] In the embodiments of the present application, the symbol " / " can represent that the objects before and after are in an "or" relationship. Additionally, the symbol " / " can also represent a division sign, that is, perform a division operation. For example, A / B can represent A divided by B.

[0022] The "at least one (item)" or its similar expression in the embodiments of the present application refers to any combination of these items, including any combination of a single item (item) or plural items (items), which means one or more, and multiple means two or more. For example, at least one (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.

[0023] The "equal to" in the embodiments of the present application can be used in combination with "greater than" and is applicable to the technical solutions adopted when it is greater than, or can also be used in combination with "less than" and is applicable to the technical solutions adopted when it is less than. When "equal to" is used in combination with "greater than", it is not used in combination with "less than"; when "equal to" is used in combination with "less than", it is not used in combination with "greater than".

[0024] Current disaster warning systems usually use general algorithms to send roughly the same warning information and risk avoidance measures to all users within a certain area. Exemplarily, see Figure 6 , Figure 6 FIG. 6 is a conventional earthquake warning prompt interface provided by an embodiment of the present application. As shown in Figure 6 FIG. 6, the earthquake warning prompt interface 6 includes the location of the disaster occurrence, the magnitude, the felt intensity, the distance between the current user and the epicenter, and prompt information, such as "Please stay calm, stay away from hanging objects, do not take the elevator, and you can choose to take shelter in the nearby life triangle area or open space."

[0025] It can be seen that the above-mentioned disaster warning content is difficult to provide personalized risk avoidance warning content for users. In reality, disasters often do not occur alone, and there may be situations where multiple disasters occur simultaneously, such as earthquakes triggering fires, debris flows accompanied by floods, etc. However, the existing system's algorithms and models have deficiencies in analyzing the impact on individual users and targeted risk avoidance measures in multi-disaster scenarios, and cannot accurately provide users with comprehensive risk avoidance warnings in complex disaster situations.

[0026] To solve the above technical problems, this application provides a method and device for processing emergency disaster information. By having users wear intelligent wearable devices, the intelligent wearable devices generate personalized risk avoidance warning information adapted to the user's current state based on conventional disaster warning information and the user's personal information, improving the pertinence and effectiveness of disaster warnings.

[0027] The following uses specific embodiments to elaborate in detail on the technical solutions of this application and how the technical solutions of this application solve the above technical problems. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The following will describe the embodiments of this application with reference to the accompanying drawings.

[0028] Please refer to Figures 1 - 2 , the emergency disaster system 1 includes a server 10, an intelligent wearable device 20 worn by the user, and an intelligent gateway 30.

[0029] In some embodiments, when the public network communication system can be used normally, the server 10 is directly communicatively connected to the intelligent wearable device 20, as Figure 1 shown.

[0030] In some embodiments, when the server 10 and the intelligent wearable device 20 cannot be connected, for example, due to address disasters damaging the signal base station, making the intelligent wearable device 20 unable to communicate with the server 10, see Figure 2 , an intelligent gateway 30 is set, and the intelligent wearable device 20 communicates with the server 10 through the intelligent gateway 30.

[0031] Among them, the server 10 can specifically include a server responsible for data processing on the side of the network platform that can implement 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, the number of servers 10 is not specifically limited. Or, it can also 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 Network (CDN), and big data and artificial intelligence platforms.

[0032] Specifically, see Figure 3 , Figure 3 , which is a schematic structural diagram of the server provided by the embodiment of the present application. As Figure 3 shown, the server 10 includes a processor 11, a memory 13, a communication interface 12, and one or more programs 131. Among them, the one or more programs 131 are stored on the memory 13 and are configured to be executed by the above-mentioned processor 11. The one or more programs 131 include instructions for executing any step in the following method embodiments.

[0033] Among them, the smart wearable device 20 may include a front-end device applied to the user side that can implement functions such as positioning, data collection, and data transmission. It can be a user device such as a mobile phone with positioning function, a handheld device, or a wearable device. Preferably, Figure 1 as shown in

[0034] Specifically, 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 acquire the positioning information of the user; the user information acquisition module 202 is used to acquire the user status information, and the user status information includes but is not limited to physiological characteristic information, user group characteristics, and status of carried equipment. Among them, the physiological characteristic information includes but is not limited to the user's underlying disease information and physical strength data, the user group characteristics include but are not limited to whether carrying children, the elderly, or pets, and the status of carried equipment includes but is not limited to whether carrying emergency supplies. The above-mentioned user status information can be input into the smart wearable device 20 in advance by the user according to their own situation through voice or text, or can be obtained by the user's authorization according to the user's identity information from the corresponding information database, such as obtaining the user's medical record information through the user's identity information. Of course, the above-mentioned user status information can also be input through other suitable methods, and the present application does not make specific limitations on this.

[0035] The smart wearable device 20 also includes various application program interfaces (APIs) 203 to interact with other systems. For example, obtain meteorological data from the meteorological department through API interface 1, obtain real-time disaster data from the emergency management department through API interface 2, and obtain terrain environment data of the geographic information system and satellite remote sensing data platform through API interface 3, etc.

[0036] The smart wearable device 20 also includes a controller 204, and the controller 204 is used to execute the step instructions of any one of the methods described in the following method embodiments.

[0037] Please refer to Figure 5 , Figure 5 , which is a schematic flowchart of a method for processing emergency disaster information provided by the embodiment of the present application, applied to such as Figure 1The intelligent wearable device shown, the method includes the following steps S501 - step S504: Step S501, receive disaster prompt information from the server.

[0038] Among them, the disaster prompt information here is the common disaster prompt information in the prior art. Exemplarily, the disaster prompt information includes, but is not limited to, information such as disaster type, disaster occurrence range, and disaster level.

[0039] Step S502, obtain the positioning information of the user, and obtain the user status information.

[0040] Among them, the user status information includes at least one of physiological characteristic information, user group characteristics, and status of personal equipment.

[0041] Among them, the physiological characteristic information is used to characterize the user's mobility and movement speed, the user group characteristics are used to characterize the positive or negative influence degree on the movement speed, and the status of personal equipment is used to characterize the user's independent survival time.

[0042] Step S503, generate personalized risk avoidance prompt information for the user according to the disaster prompt information, the positioning information, and the user status information.

[0043] In some embodiments, the disaster prompt information includes disaster type, disaster occurrence range, and disaster level. The generating of the personalized risk avoidance prompt information for the user according to the disaster prompt information, the positioning information, and the user status information includes: determining the comprehensive disaster warning range according to the disaster prompt 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, generate 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 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 risk avoidance operations; if it is detected that the positioning information is not within the comprehensive disaster warning range, generate the second personalized risk avoidance prompt information according to 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 measure suggestions.

[0044] Among them, after the smart wearable device determines the comprehensive disaster warning range according to the disaster prompt information, it compares the user's location information with the boundary of the comprehensive disaster warning range. If it detects that the user is within the comprehensive disaster warning range, the threat level to the user's life and health is relatively high at this time, and then 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 the user's 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 detects that the user is outside the comprehensive disaster warning range, the threat level to the user's life and health is low at this time, and only different preventive measure suggestions need to be generated according to the distance gradient between the user and the warning range. At the same time, the diffusion trend dynamics of the comprehensive disaster warning range can be generated to facilitate the user to timely understand the changes in the disaster situation.

[0045] It can be seen that in this embodiment, different strategies are used to generate different personalized prompt information based on the positional relationship between the user's location information and the comprehensive disaster warning range, which can not only ensure the accuracy and effectiveness of the warning prompt, but also avoid excessive calculation and prompt, improve the calculation efficiency and save computing resources.

[0046] Among them, the disaster prompt information includes the disaster type, the disaster occurrence range, and the disaster level.

[0047] In some embodiments, for determining the comprehensive disaster warning range according to the disaster prompt information, the following specific steps a-step d are included: Step a, determining a first warning range according to the disaster occurrence range and the disaster level of each disaster type.

[0048] 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-step a3: Step a1, determining the expansion method and range correction coefficient of the warning range according to the disaster type; Step a2, determining the range expansion coefficient according to the disaster level; Step a3, determining the first warning range according to the disaster occurrence range, the expansion method, the range correction coefficient, and the range expansion coefficient.

[0049] Among them, the disaster type determines the range expansion method of the warning range. For example, for an earthquake, it expands in concentric circles with the epicenter as the center; for a flood, it expands in a band along the river bank; for a typhoon, it expands in a fan shape on both sides of the path; for a wildfire, it expands in a fan shape along the wind direction.

[0050] Among them, different disasters have different propagation modes or diffusion laws, and the expansion direction or proportion needs to be adjusted according to their physical characteristics. The range expansion coefficient is a spatial correction factor related to the disaster propagation mode, reflecting the collective characteristics of the disaster diffusion (such as circular, belt-shaped, fan-shaped, etc.). For example, for earthquakes, the expansion of concentric circles with the epicenter as the center, then the warning range is expanded 1.8 times outward from the disaster occurrence range as the center according to the range expansion coefficient (such as 1.8); for floods, the warning range is expanded 1.5 times from the disaster occurrence range to the banks and / or downstream of the river according to the range expansion coefficient (such as 1.5).

[0051] Among them, the higher the disaster level, the stronger the destructive power or impact of the disaster, and the basic 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 threat range of the disaster needs to be covered. For example, for earthquakes, the larger the magnitude (the higher the level), the wider the propagation range of seismic waves, and the larger the affected area of ​​secondary disasters (such as landslides and aftershocks). For typhoons, the higher the level (such as super typhoons), the farther 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 breach or flooded area may expand exponentially.

[0052] The first warning range is calculated by the following formula: The first warning range = disaster occurrence range × range correction coefficient × range expansion coefficient.

[0053] In addition, the first warning range can be modified based on terrain factors, population density, and infrastructure impacts.

[0054] 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.

[0055] 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.

[0056] 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 calculation amount 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 delays in warning prompts due to waiting for secondary disaster assessments.

[0057] Step c, when it is detected that there is a type of disaster and the disaster level is higher than the preset level, determine the range of possible secondary disasters based on the disaster occurrence range and the disaster level; determine the comprehensive disaster warning range based on the range of secondary disasters and the first warning range.

[0058] When there is only one type of disaster but the disaster level is high, it is easy to trigger other secondary disasters at this time. Therefore, the intelligent wearable device needs to further evaluate the range of possible secondary disasters based on the disaster occurrence range and the disaster level, and comprehensively determine the comprehensive disaster warning range based on the range of secondary disasters and the first warning range, so as to avoid missing the range of secondary disasters and make the comprehensive disaster warning range more comprehensive.

[0059] Step d, when it is detected that there are at least two types of disasters, determine the range of possible secondary disasters based on the disaster occurrence ranges and disaster levels of the at least two types of disasters; obtain the interaction coefficient between the at least two types of disasters, where the interaction coefficient is used to characterize the enhancement degree or weakening degree between the at least two types of disasters; correct the first warning range according to the range of secondary disasters and the interaction coefficient to obtain the comprehensive disaster warning range.

[0060] When there are at least two types of disasters, it is easy to trigger other secondary disasters at this time, and there may also be a mutual enhancement or mutual weakening effect between the at least two types of disasters. Therefore, it is necessary to comprehensively consider the range of possible secondary disasters and the interaction coefficient between the at least two types of disasters, and correct the first warning range through the range of secondary disasters and the interaction coefficient to obtain the comprehensive disaster warning range, which not only improves the accuracy and comprehensiveness of the warning, but also promotes the paradigm shift of disaster management from "single disaster type response" to "systematic defense".

[0061] In some embodiments, determining the range of possible secondary disasters based on the disaster occurrence range and the disaster level includes the following steps c1-step c5: Step c1, obtain the environmental data within the disaster occurrence range, where the environmental data at least includes terrain data; Step c2, determine the type of possible secondary disasters based on the disaster occurrence range and the environmental data; Step c3, determine the probability of secondary disaster occurrence for triggering the type of secondary disaster based on the disaster level; Step c4, determine the secondary disaster expansion coefficient based on the disaster level and the environmental data; Step c5, determine the range of secondary disasters based on the disaster occurrence range, the disaster level, the probability of secondary disaster occurrence, and the secondary disaster expansion coefficient.

[0062] Among them, the range of secondary disasters is calculated according to the following formula: A2 = λ × A1 × α × β + ε Among them, A2 represents the range of secondary disasters, A1 represents the range of the disaster occurrence, α represents the triggering probability of secondary disasters, β represents the expansion coefficient of secondary disasters, and the triggering probability α of secondary disasters has a positive correlation with the disaster level. λ and ε are function adjustment factors and are constants.

[0063] Among them, before performing the above steps c1 - c5, it is also necessary to establish a first mapping relationship between the disaster level and the triggering probability of secondary disasters.

[0064] Exemplarily, as shown in Table 1 below, Table 1 is a mapping table of earthquakes and landslide probabilities.

[0065] Among them, determining the secondary disaster expansion coefficient according to the disaster level and the environmental data includes: the environmental data includes terrain data, and the secondary disaster expansion coefficient is assigned based on the terrain data and the disaster level. For example, when the slope is greater than 25°, the secondary disaster expansion coefficient β = 1.8, and when the rock and soil type is loose sediment layer, β = 1.5.

[0066] Exemplarily, assume that 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 trigger a landslide. According to Table 1 above, the probability of a landslide triggered by a disaster level of 7 is 60%. Determine that the secondary disaster expansion coefficient is 1.8, then the range of secondary disasters = λ × 10 × 0.6 × 1.8 + ε.

[0067] In some embodiments, the comprehensive disaster warning range is determined according to the range of secondary disasters and the first warning range, and the comprehensive disaster warning range is calculated through the following formula: A 综合 = A 1 ∪ A 2 Among them, A 综合 represents the comprehensive disaster warning range, A 1 represents the disaster range, A 2 represents the range of secondary disasters, and "∪" represents the union operation.

[0068] In some embodiments, modifying the first warning range according to the range of secondary disasters and the interaction coefficient to obtain the comprehensive disaster warning range includes: modifying the first warning range of each disaster type according to the interaction coefficient to obtain a second warning range; performing a superposition analysis on the range of secondary disasters and the second warning range to generate the comprehensive disaster warning range.

[0069] Among them, for each disaster, its first warning range is corrected according to the interaction coefficient with other disasters to obtain the second warning range, which is calculated by the following formula:

[0070] Among them, represents the second warning range of the j-th disaster type, represents the first warning range of the j-th disaster type, A j represents the disaster range of the j-th disaster type, W ji represents the interaction coefficient between the j-th disaster type and the i-th disaster type, j≠i.

[0071] This formula indicates that the second warning range of the j-th disaster type is obtained from the first warning range of this disaster type , the disaster range of this disaster type and the union operation of all other disaster types according to their respective interaction coefficients W ji with respect to the j-th disaster type. That is, it comprehensively considers the superposition effect of other disasters on the influence range of the j-th disaster, and can more accurately reflect the actual affected area of the disaster in the case of multiple disasters occurring simultaneously.

[0072] Among them, if at least two disaster types meet the conditions for secondary disasters, a secondary disaster range A k will be generated. Then, superimposed analysis is performed on the secondary disaster range and the second warning range to generate the comprehensive disaster warning range, including: The second warning ranges 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:

[0073] Among them, A 综合 represents the comprehensive disaster warning range, represents the second warning range of the j-th disaster type, and the value range of j is [1, N], where N is the total number of disaster types. B k is the secondary disaster range, K represents the highest disaster level among at least two disaster types that trigger secondary disasters, ω is the dynamic expansion factor, β is the level correction factor, and the higher the disaster level, the more significant the range expansion. G j is the disaster level of the j-th disaster type.

[0074] Among them, the dynamic expansion factor , where, Denote the average total disaster level. The average disaster level is obtained by dividing the sum of the disaster levels of all occurred disaster types by the number of occurred disaster types, and then dividing by the highest disaster level that triggers secondary disasters to compress the average disaster level within the range of [0, 1]. The closer the average total disaster level is to 1, the higher the overall intensity of the disaster.

[0075] Exemplarily, assume that the disaster level G1 of earthquake T1 is 5, and the first warning range A 1 （1） = S1 is obtained according to the above embodiment. The disaster level G2 of flood T2 is 7, and the first warning range A 2 （1） = S2 is obtained according to the above embodiment.

[0076] The earthquake itself can trigger landslides, and the possibility of landslides increases significantly in the common action area of the earthquake and the flood. The interaction coefficient W 12 = +1.2.

[0077] Then the second warning range of the earthquake disaster is: A 1 （2） = A 1 （1） ∪ (A 1 × W 12 ) = S 1 ∪ 1.2 × S 1 ; The second warning range of the flood disaster is: A 2 （2） = A 2 （1） ∪ (A 2 × W 12 ) = S 2 ∪ 1.2 × S 2 ; Assume that the landslide range B 7 = S3, then the comprehensive disaster warning range A 综合 = (S 1 ∪ S 2 ) ∪ S 3 × (1 + β · (5 + 7) / (2 × 7) = (S 1 ∪ S 2 ) ∪ S 3 × (1 + 0.86 × β).

[0078] In some embodiments, determining the range of possible secondary disasters according to the disaster occurrence ranges and disaster levels of the at least two disaster types includes the following steps d1 - step d6: Step d1, obtain the overlapping area of the disaster occurrence ranges of the at least two disaster types; Step d2: Regarding the disaster type with the highest disaster level within the overlapping area as the primary disaster, and regarding the remaining disaster types as secondary disasters; Step d3: Determining the types of possible secondary disasters based on the primary disaster and the secondary disasters; Step d4: Determining whether the trigger conditions for the corresponding types of secondary disasters are met based on the disaster level of the primary disaster, the disaster level of the secondary disasters, and the environmental data of the overlapping area; Step d5: If the conditions are met, determining that the type of secondary disaster occurs, obtaining the secondary disaster level based on the disaster level of the primary disaster and the disaster level of the secondary disasters; determining the secondary disaster scope based on the secondary disaster level and the overlapping area; Step d6: If the conditions are not met, determining that the type of secondary disaster does not occur, and the secondary disaster scope is 0.

[0079] Among them, the environmental data includes at least topographic data, and may also include population data, infrastructure data, etc.

[0080] Among them, there is at least one secondary disaster. Different levels of primary disasters and secondary disasters may trigger different types of secondary disasters. Generally speaking, the higher the disaster levels of the primary disaster and the secondary disasters, the greater the possibility of triggering secondary disasters, and the higher the secondary disaster level. However, it is also necessary to consider the environmental data of the overlapping area. For example, under the dual action of an earthquake and a flood, debris flows, landslides and other secondary disasters are extremely likely to occur in mountainous areas, but if it is in a plain, the possibility of debris flows and landslides is greatly reduced, and the possibility of flood disasters is greater.

[0081] It can be seen that in this embodiment, based on the disaster levels of the primary disaster and the secondary disasters combined with the surrounding environmental characteristics, it can be determined whether the trigger conditions for the occurrence of secondary disasters are met. When the trigger conditions are met, the secondary disaster level is determined based on the disaster levels of the primary disaster and the secondary disasters, and the secondary disaster scope is determined based on the secondary disaster level and the overlapping area; when the trigger conditions are not met, it is directly determined that the secondary disaster scope is 0, balancing the comprehensiveness and efficiency of the calculation results.

[0082] In some embodiments, the physiological characteristic information includes the user's underlying disease information and physical strength data, the user group characteristics include whether the user is accompanied by children, the elderly, or pets, and the status of the portable equipment includes whether emergency supplies are carried; generating the first personalized hazard avoidance prompt information according to at least one of the user status information, the type of disaster, the scope of the disaster occurrence, and the environmental data near the positioning information includes: determining the user's mobility according to the underlying disease information, and determining the user's movement speed according to the physical strength data; detecting that the user has mobility and the movement speed is greater than a preset speed; generating at least one hazard avoidance route according to the type of disaster and the environmental data; determining the restriction conditions for the hazard avoidance route and the degree of influence on the movement speed according to the user group characteristics; determining the user's independent survival duration according to the status of the portable equipment; selecting a target hazard avoidance route from the at least one hazard avoidance route according to the movement speed, the restriction conditions, the degree of influence, and the independent survival duration, and the first personalized hazard avoidance prompt information includes the target hazard avoidance route.

[0083] Among them, the underlying disease information is used to characterize the user's mobility. For example, if the user has no underlying disease affecting walking, then the user has mobility. If the user has underlying diseases affecting walking, such as lower limb dysfunction, severe arthritis patients, vegetative patients, etc., then the user does not have mobility.

[0084] Among them, the physical strength data can be obtained through smart wearable devices. For example, the user's usual fitness data, walking, running data, endurance, maximum exercise heart rate, etc. are obtained, which are used to determine the user's movement speed during a disaster. The better the physical strength, the faster the movement speed, and the worse the physical strength, the slower the movement speed.

[0085] Among them, the user group characteristics are used to characterize the positive or negative restrictions on the movement speed. For example, when the user is accompanied by the elderly or children, it will generate restriction conditions for the selection of the hazard avoidance route and have a negative slowing effect on the movement speed.

[0086] Among them, the status of the portable equipment is used to characterize the user's independent survival duration. If the user carries emergency supplies such as food, water, first aid kits, etc., the user's independent survival duration will be relatively long, and there may be more flexibility in the selection of the hazard avoidance route. For example, a route that is slightly farther away but safer can be selected.

[0087] Among them, a more specific prompt scheme is determined according to the user's mobility and movement speed. Specifically, if the user does not have mobility, the smart wearable device generates a distress signal based on the user's location information and sends the distress signal to the server so that external rescue personnel can rescue the user in a timely manner. If the user has mobility but the movement speed cannot keep up with the risk avoidance speed, it is mainly recommended that the user stay near the original place to find a shelter, and the smart wearable device generates detailed risk avoidance operations based on the user's location information and the surrounding environment. If the user has mobility and the movement speed is normal, the main recommendation at this time is to generate a risk avoidance route. The smart wearable device generates at least one risk avoidance route based on the user's positioning data, nearby terrain data, disaster occurrence range, and disaster type, and selects the most suitable target risk avoidance route from at least one route according to the user's movement speed, limiting conditions, degree of influence on the movement speed, and independent survival duration.

[0088] Among them, a possible implementation method is that the user's movement speed, limiting conditions, degree of influence on the movement speed, and independent survival duration can be quantified, the survival probability of the user on each risk avoidance route is calculated, at least one risk avoidance route corresponds to at least one survival probability, and the risk avoidance route corresponding to the maximum probability is selected from at least one survival probability as the target risk avoidance route.

[0089] In some embodiments, after determining the user's mobility according to the underlying disease information and determining the user's movement speed according to the physical data, the method further includes: detecting that the user does not have mobility, generating a distress signal according to the positioning information, and sending the distress signal to the server, where the first personalized risk avoidance prompt information includes the distress signal; detecting that the user has mobility and the movement speed is less than the preset speed, obtaining the user's environmental data, and generating the risk avoidance operation according to the disaster type and the environmental data, where the first personalized risk avoidance prompt information includes the risk avoidance operation.

[0090] Exemplarily, assuming that the disasters are typhoon and flood, and the user lives on the 19th floor of a high-rise building. If the user is within the comprehensive disaster warning range and the user does not have mobility, the smart wearable device can obtain the user's location information, generate a distress signal, and send the distress signal to its emergency contacts and the external emergency rescue server. At this time, the first prompt interface of the smart wearable device is as Figure 7 shown. The first prompt interface 7 includes disaster prompt content 71, distress signal content 72, and successful sending prompt content 73.

[0091] If the user is within the comprehensive warning range, the user has mobility, and the movement speed is extremely slow, at this time, the second prompt interface of the smart wearable device is as Figure 8As shown, the second prompt interface 8 includes the first disaster details content 81 and the hazard avoidance operation prompt 82. The first disaster details content 81 includes information such as the type of disaster, the level of disaster, the scope of disaster occurrence, the comprehensive disaster warning scope, and the user's current location. Among them, the hazard avoidance operation prompt 82 includes: closing all doors and windows, preparing emergency supplies, and taking shelter in the corner of the interior load-bearing wall away from the window or the bathroom.

[0092] If the user is within the comprehensive warning range, the user has the ability to move, and the movement speed is normal. At this time, the third prompt interface of the smart wearable device is as Figure 9 shown. The third prompt interface 9 includes the second disaster details content 91 and the hazard avoidance route 92. The second disaster details content 91 includes information such as the type of disaster, the level of disaster, the scope of disaster occurrence, the comprehensive disaster warning scope, and the user's current location. When the user clicks on the hazard avoidance route 92, a specific navigation interface 93 is displayed to guide the user to transfer to a safe location.

[0093] If the user is outside the comprehensive warning range, at this time, the fourth prompt interface of the smart wearable device is as Figure 10 shown. The fourth prompt interface 10a includes the third disaster details content 10a1 and the preventive hazard avoidance advice 10a2. The third disaster details content 10a1 includes information such as the type of disaster, the level of disaster, the scope of disaster occurrence, the comprehensive disaster warning scope, and the user's current location. The preventive hazard avoidance advice 10a2 is prompted according to the specific floor and location.

[0094] Specifically, gradient prompt content is formed according to the distance of the user from the comprehensive warning range.

[0095] For example, in the critical buffer layer (0 - 3 kilometers from the boundary), display the dynamic trend of disaster spread, mark the real-time distance change curve between the user's location and the disaster boundary, and display preventive measure suggestions according to the user's environment (such as the location environment, the floor where the user is located) (for example, when a flood occurs, prompt flood prevention measures for users in low-lying areas and low floors, and when a tornado occurs, prompt protective measures for strengthening doors and windows for users on high floors); In the secondary impact layer (3 - 10 kilometers from the boundary), display the dynamic trend of disaster spread, mark the real-time distance change curve between the user's location and the disaster boundary.

[0096] In the peripheral observation layer (more than 10 kilometers from the boundary), establish a disaster information briefing module (update frequency / impact scope / casualty situation), access the live broadcast channel of the official press conference, and provide an inquiry entrance for the disaster status in different regions, etc.

[0097] Step S504, display the personalized hazard avoidance prompt information on the display interface of the smart wearable device.

[0098] It can be seen that in the embodiments of the present application, the smart wearable device receives disaster warning information from the server; obtains the user's location information, and obtains the user status information, where the user status information includes at least one of physiological characteristic information, user group characteristics, and the status of the equipment carried with the user; generates personalized disaster avoidance warning information for the user according to the disaster warning information, location information, and user status information; and displays the personalized disaster avoidance warning information on the display interface of the smart wearable device. Therefore, in the present application, by the user wearing the smart wearable device, the smart wearable device generates personalized disaster avoidance warning information adapted to the user's current status according to the conventional disaster warning information and the user's personal information, improving the pertinence and effectiveness of disaster warning.

[0099] The above mainly introduces the solution of the embodiments of the present application from the perspective of the execution process on the method side. It can be understood that in order for the server to implement the above functions, it includes the corresponding hardware structure and / or software module for executing 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 embodiments provided in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0100] The embodiments of the present application can divide the functions of the server according to the above method examples. For example, each function unit can be divided corresponding to each function, or two or more functions can be integrated into one processing module. The above integrated unit can be implemented in the form of hardware or in the form of a software program module. It should be noted that the division of units in the embodiments of the present application is illustrative, only a logical function division, and there can be other division methods in actual implementation.

[0101] In the case of adopting an integrated unit, please refer to Figure 11 , Figure 11 which is a functional unit block diagram of a processing device for emergency disaster information provided by the embodiments of the present application, applied to a smart wearable device in an emergency disaster system, where the emergency disaster system includes the smart wearable device and a server, and the processing device 110 includes: A receiving unit 1101, configured to receive disaster warning information from the server; and obtain the user's location information, and obtain the user status information, where the user status information includes at least one of physiological characteristic information, user group characteristics, and the status of the equipment carried with the user; A processing unit 1102, configured to generate personalized hazard avoidance prompt information for the user according to the hazard prompt information, the positioning information, and the user status information; and display the personalized hazard avoidance prompt information on a display interface of the smart wearable device.

[0102] It can be seen that in the embodiments of the present application, the smart wearable device receives hazard prompt information from the server; obtains the positioning information of the user, and obtains the user status information, where the user status information includes at least one of physiological characteristic information, user group characteristics, and the status of the equipment carried with the user; generates personalized hazard avoidance prompt information for the user according to the hazard prompt information, the positioning information, and the user status information; and displays the personalized hazard avoidance prompt information on the display interface of the smart wearable device. Therefore, in the present application, by the user wearing the smart wearable device, the smart wearable device generates personalized hazard avoidance prompt information adapted to the current status of the user according to the conventional hazard prompt information and the personal information of the user, improving the pertinence and effectiveness of hazard warning.

[0103] In some embodiments, the hazard prompt information includes a hazard type, a hazard occurrence range, and a hazard level. The processing unit 1102 generates the personalized hazard avoidance prompt information for the user according to the hazard prompt information, the positioning information, and the user status information, including: determining a comprehensive hazard warning range according to the hazard prompt information; comparing the positioning information with the boundary data of the comprehensive hazard warning range to determine whether the user is within the comprehensive hazard warning range; if it is detected that the positioning information is within the comprehensive hazard warning range, generating first personalized hazard avoidance prompt information according to at least one of the user status information, the hazard type, the hazard occurrence range, and the environmental data near the positioning information, where the first personalized hazard avoidance prompt information includes at least one of a distress signal, an evacuation route, and hazard avoidance operations; if it is detected that the positioning information is not within the comprehensive hazard warning range, generating second personalized hazard avoidance prompt information according to the distance between the positioning information and the comprehensive warning range, where the second personalized hazard avoidance prompt information includes at least one of the diffusion trend dynamics of the comprehensive hazard warning range and preventive measure suggestions.

[0104] In some embodiments, the processing unit 1102 determines the comprehensive disaster warning range according to the disaster prompt information, including: determining a first warning range according to the disaster occurrence range and the disaster level of each disaster type; when it is detected that there is one type of disaster and the disaster level is lower than the preset level, determining the first warning range as the comprehensive disaster warning range; when it is detected that there is one type of disaster and the disaster level is higher than the preset level, determining the range of possible secondary disasters according to the disaster occurrence range and the disaster level; determining the comprehensive disaster warning range according to the range of secondary disasters and the first warning range; when it is detected that there are at least two types of disasters, determining the range of possible secondary disasters according to the disaster occurrence ranges and disaster levels of the at least two types of disasters; obtaining the interaction coefficient between the at least two types of disasters, where the interaction coefficient is used to characterize the enhancement degree or weakening degree between the at least two types of disasters; and modifying the first warning range according to the range of secondary disasters and the interaction coefficient to obtain the comprehensive disaster warning range.

[0105] In some embodiments, the processing unit 1102 modifies the first warning range according to the range of secondary disasters and the interaction coefficient to obtain the comprehensive disaster warning range, including: modifying the first warning range of each disaster type according to the interaction coefficient to obtain a second warning range; and performing superposition analysis on the range of secondary disasters and the second warning range to generate the comprehensive disaster warning range.

[0106] In some embodiments, the processing unit 1102 determines the range of possible secondary disasters according to the disaster occurrence ranges and disaster levels of the at least two types of disasters, including: obtaining the overlapping area of the disaster occurrence ranges of the at least two types of disasters; taking the disaster type with the highest disaster level in the overlapping area as the main disaster, and taking the remaining disaster types as secondary disasters; determining the possible secondary disaster types according to the main disaster and the secondary disasters; determining whether the trigger conditions for the corresponding secondary disaster types are met according to the disaster level of the main disaster, the disaster level of the secondary disasters, and the environmental data of the overlapping area; if so, determining that the secondary disaster types are generated, and obtaining the secondary disaster level according to the disaster level of the main disaster and the disaster level of the secondary disasters; determining the range of secondary disasters according to the secondary disaster level and the overlapping area; if not, determining that the secondary disaster types are not generated, and the range of secondary disasters is 0.

[0107] In some embodiments, the physiological characteristic information includes the user's underlying disease information and physical strength data, the user group characteristics include whether carrying children, the elderly, or pets, and the status of the portable equipment includes whether carrying emergency supplies; the processing unit 1102 generates a first personalized hazard avoidance prompt message according to at least one of the user status information, the type of the disaster, the scope of the disaster occurrence, and the environmental data near the positioning information, including: determining the user's mobility according to the underlying disease information, and determining the user's movement speed according to the physical strength data; detecting that the user has mobility and the movement speed is greater than a preset speed; generating at least one hazard avoidance route according to the type of the disaster and the environmental data; determining the restriction conditions for the hazard avoidance route and the influence degree on the movement speed according to the user group characteristics; determining the user's independent survival duration according to the status of the portable equipment; and selecting a target hazard avoidance route from the at least one hazard avoidance route according to the movement speed, the restriction conditions, the influence degree, and the independent survival duration, and the first personalized hazard avoidance prompt message includes the target hazard avoidance route.

[0108] In some embodiments, after the processing unit 1102 determines the user's mobility according to the underlying disease information and determines the user's movement speed according to the physical strength data, the processing unit 1102 is further configured to: detect that the user does not have mobility, generate a distress signal according to the positioning information, and send the distress signal to the server, and the first personalized hazard avoidance prompt message includes the distress signal; detect that the user has mobility and the movement speed is less than the preset speed, obtain the user's environmental data, and generate the hazard avoidance operation according to the type of the disaster and the environmental data, and the first personalized hazard avoidance prompt message includes the hazard avoidance operation.

[0109] An embodiment of the present application provides a computer-readable storage medium, on which a computer program / instructions is stored, and when the computer program / instructions is executed by a processor, the steps of the method according to any possible embodiment are implemented.

[0110] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps may be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0111] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0112] In several embodiments provided by the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the above-mentioned division of units is only a logical function division. In actual implementation, there may be other division methods. For example, 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 displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical or other forms.

[0113] The units described above as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0114] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0115] 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, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the above method in each embodiment of the present application. And the aforementioned memory includes: various media such as USB flash drives, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0116] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program, and this program can be stored in a computer-readable memory. The memory may include: a flash drive, a read-only memory (abbreviation: ROM), a random access memory (abbreviation: RAM), a magnetic disk, an optical disk, etc.

[0117] The above has introduced the embodiments of the present application in detail. Specific examples are used in this article to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A method for processing emergency disaster information, characterized in that: A smart wearable device applied to an emergency disaster system, wherein the emergency disaster system comprises the smart wearable device and a server, and the method comprises: Receiving disaster warning information from the server; Acquire the user's location information, and acquire the user's status information, wherein the user's status information includes at least one of physiological characteristic information, user group characteristics, and portable equipment status; Generate personalized risk avoidance reminder information for the user according to the disaster reminder information, the positioning information, and the user status information; The personalized risk avoidance prompt information is displayed on the display interface of the smart wearable device.

2. The method according to claim 1, characterized in that The disaster warning information includes the disaster type, disaster occurrence range, and disaster level. The generating of the personalized risk avoidance warning information of the user according to the disaster warning information, the positioning information, and the user status information includes: Determine the comprehensive disaster warning scope according to 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; When it is detected that the positioning information is within the comprehensive disaster warning range, 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 environmental data near the positioning information, wherein the first personalized risk avoidance prompt information includes at least one of a distress signal, a risk avoidance route, and a risk avoidance operation; If it is detected that the positioning information is not within the comprehensive disaster warning range, second personalized risk avoidance prompt information is generated based on the distance between the positioning information and the comprehensive disaster 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 2, characterized in that Determining the comprehensive disaster warning scope according to the disaster prompt 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 the 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 that may be caused is determined according to the disaster occurrence scope and the disaster level; the comprehensive disaster warning scope is determined according to the secondary disaster scope and the first warning scope; At least two disaster types are detected, and the scope of secondary disasters that may be caused is determined according to the disaster occurrence scope and disaster level of the at least two disaster types; an interaction coefficient between the at least two disaster types is obtained, and 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.

4. The method according to claim 3, 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.

5. The method according to claim 3, characterized in that: The determining of the scope of the secondary disasters that may be caused according to the scope of occurrence and the disaster level of the at least two types of disasters includes: 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 that may be 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 be generated, and the secondary disaster level is obtained according to the disaster level of the primary disaster and the disaster level of the secondary disaster; the secondary disaster range is determined according to the secondary disaster level and the overlapping area; If not satisfied, it is determined that the secondary disaster type will not be generated, and the secondary disaster range is 0.

6. The method according to claim 2, characterized in that The physiological characteristic information includes the basic disease information and physical strength data of the user, the user group characteristics include whether the user carries children, the elderly, and pets, and the portable equipment status includes whether the user carries emergency supplies; 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, including: Determine the user's mobility according to the underlying disease information, and determine the user's movement speed according to the physical strength data; It is detected that the user has the ability to move, and the moving speed is greater than a preset speed; Generate at least one evacuation route according to the disaster type and the environmental data; Determining restriction conditions on the risk avoidance route and the degree of influence on the action speed according to the user group characteristics; Determining the autonomous survival time of the user according to the status of the portable equipment; A target risk avoidance route is selected from the at least one risk avoidance route according to the action speed, the restriction condition, the impact degree and the autonomous survival time, and the first personalized risk avoidance prompt information includes the target risk avoidance route.

7. The method according to claim 6, characterized in that After determining the user's mobility according to the underlying disease information and determining the user's motion speed according to the physical strength data, the method further includes: detecting that the user is unable to act, 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 moving speed is less than the preset speed, the environmental data of the user is obtained, the risk avoidance operation is generated according to the disaster type and the environmental data, and the first personalized risk avoidance prompt information includes the risk avoidance operation.

8. A device for processing emergency disaster information, characterized in that: A smart wearable device applied to an emergency disaster system, wherein the emergency disaster system comprises the smart wearable device and a server, and the device comprises: A receiving unit, configured to receive disaster warning information from the server; and obtain user location information and user status information, wherein the user status information includes at least one of physiological characteristic information, user group characteristics, and portable equipment status; A processing unit is used to generate personalized risk avoidance prompt information for the user according to the disaster prompt information, the positioning information, and the user status information; and display the personalized risk avoidance prompt information on the display interface of the smart wearable device.

9. A disaster emergency system, characterized in that: It comprises a smart wearable device and a server, wherein the smart wearable device is used to execute the step instructions in the method as described in any one of claims 1-7.

10. A server, characterized in that: The method comprises 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 according to any one of claims 1 to 7.

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