An insurance service method, apparatus, device, and medium

Abstract

This invention discloses an insurance service method, apparatus, equipment, and medium, comprising: inputting user response data to fall injury events, support data for daily care events, and environmental data of the modified environment into a risk assessment module of a target service decision model; outputting a harm coefficient representing the severity of the fall injury, a stress coefficient representing the degree of stress on the user's care, and a risk coefficient representing the degree of risk of the modified environment through the risk assessment module; and inputting the harm coefficient, stress coefficient, risk technology, response data, support data, and environmental data into a service decision module of the target service decision model; and triggering insurance services for the fall injury event, daily care events, and modified environment through the service decision module. This invention can be applied to home-based elderly care scenarios in the financial insurance field, realizing adaptive insurance services based on the user's actual situation, improving the efficiency and reliability of insurance services, and enhancing the user experience.

Description

Technical Field

[0001] This invention relates to the fields of data processing technology and financial insurance, and in particular to an insurance service method, apparatus, equipment and medium. Background Technology

[0002] In recent years, with the continuous improvement of residents' risk awareness and insurance demand, insurance services have been widely used in areas such as old-age security and health care. Traditional insurance service models mainly rely on users to initiate insurance services independently after a risk event occurs. This model has inherent defects such as delayed response and passive service, making it difficult to meet the real-time protection needs of an aging society, resulting in a disconnect between insurance services and actual needs. For example, in home-based elderly care scenarios, elderly users may face the risk of falls due to failure to promptly detect hidden dangers in their home environment, or experience health deterioration due to insufficient care resources. However, traditional insurance mechanisms cannot dynamically adjust protection plans or proactively trigger intervention, which not only increases the payout pressure on insurance companies but also reduces the user's insurance service experience.

[0003] Therefore, optimizing the insurance service process to improve the user's insurance service experience has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides an insurance service method, apparatus, device, and medium to address the problem of how to optimize the insurance service process and improve the user's insurance service experience.

[0005] An insurance service method includes: Acquire user response data for fall injury events, support data for daily care events, and environmental data of the modified environment in which the user is located; The response data, the support data, and the environmental data are input into the risk assessment module of the target service decision model. The risk assessment module outputs a harm coefficient representing the severity of the fall injury event, a stress coefficient representing the level of care pressure on the user, and a risk coefficient representing the level of risk of the modified environment. The injury coefficient, the stress coefficient, the risk technology, the response data, the support data, and the environmental data are input into the service decision module of the target service decision model. The service decision module then triggers insurance services for the fall injury event, the daily care event, and the modified environment.

[0006] An insurance service device, comprising: The data acquisition module is used to acquire user response data for fall injury events, support data for daily care events, and environmental data of the modified environment in which the user is located. The risk assessment module is used to input the response data, the support data, and the environmental data into the risk assessment module of the target service decision model. The risk assessment module outputs a harm coefficient representing the severity of the fall injury event, a stress coefficient representing the degree of care pressure on the user, and a risk coefficient representing the degree of risk of the modified environment. The service decision module is used to input the injury coefficient, the stress coefficient, the risk technology, the response data, the support data, and the environmental data into the service decision module of the target service decision model, and trigger insurance services for the fall injury event, the daily care event, and the modified environment through the service decision module.

[0007] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the aforementioned insurance service method.

[0008] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned insurance service method.

[0009] The aforementioned insurance service method, device, computer equipment, and storage medium input user response data to fall injury events, support data for daily care events, and environmental data of the modified environment into the risk assessment module of the target service decision model. The output is a harm coefficient representing the severity of the fall injury event, a stress coefficient representing the degree of stress on the user's care, and a risk coefficient representing the degree of risk of the modified environment. The harm coefficient, stress coefficient, risk technology, response data, support data, and environmental data are then input into the service decision module of the target service decision model to trigger insurance services for fall injury events, daily care events, and modified environments.

[0010] Among them, the target service decision model identifies the risk coefficient at the corresponding time based on user response data to fall injury events, support data for daily care events, and environmental data of the modified environment. This achieves multi-dimensional and dynamic risk assessment, and automatically triggers corresponding insurance services based on the risk coefficient and the above data. This realizes adaptive insurance services based on the user's actual situation, avoids the passive response defects of traditional insurance, improves the efficiency and reliability of insurance services, and enhances the user experience. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of an application environment for an insurance service method according to an embodiment of the present invention; Figure 2 This is a flowchart of an insurance service method according to an embodiment of the present invention; Figure 3 This is another flowchart of an insurance service method according to one embodiment of the present invention; Figure 4 This is another flowchart of an insurance service method according to one embodiment of the present invention; Figure 5 This is a schematic diagram of an insurance service device according to an embodiment of the present invention; Figure 6 This is a schematic diagram of a computer device according to an embodiment of the present invention. Detailed Implementation

[0013] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0014] The insurance service method provided in this embodiment of the invention can be applied to, for example... Figure 1 The application environment is shown. Specifically, this insurance service method is applied in a home-based elderly care system, which includes, for example, Figure 1 The diagram illustrates a client and server that communicate over a network to optimize the insurance service process and improve the user experience. The client, also known as the user terminal, is the program that provides local services to the customer, corresponding to the server. The client can be installed on, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be a standalone server or a server cluster consisting of multiple servers.

[0015] For example, in the home-based elderly care scenario within the financial insurance field, the insurance service method of this invention can intelligently analyze elderly users' response data during falls (such as heart rate, blood oxygen, and emergency measures taken), support data during daily care (such as health monitoring and outdoor behavior records generated during care), and environmental data related to environmental modifications (such as the physical state and environmental parameters of various devices in the modified environment). This automatically triggers corresponding insurance services for emergency care, respite care, and modifications, achieving adaptive insurance services based on the actual situation of elderly users. This avoids the passive response defects of traditional insurance, improves the efficiency and reliability of insurance services, and enhances the home-based elderly care experience.

[0016] In one embodiment, such as Figure 2 As shown, an insurance service method is provided, which is applied to... Figure 1 Taking the server in the example, the following steps are included: Step S201: Obtain user response data for fall injury events, support data for daily care events, and environmental data of the modified environment.

[0017] Step S202: Input the response data, support data, and environmental data into the risk assessment module of the target service decision model. The risk assessment module outputs the injury coefficient representing the severity of the fall injury event, the stress coefficient representing the degree of care pressure on users, and the risk coefficient representing the degree of risk of environmental modification.

[0018] In this embodiment, a fall injury event can refer to an accidental fall caused by a user's loss of balance or external force. Response data can refer to the user's physiological indicators and emergency response records at the time of the fall, such as the user's heart rate, blood oxygen, and emergency measures taken when the fall injury event is triggered. Daily care events can refer to the situation where the user is cared for in their daily life. Supporting data can refer to the health monitoring and behavior record data generated when the user is cared for in their daily life, such as the duration of time the user is away from home and heart rate variability when being cared for. Modified environment can refer to a living or activity space that is adjusted and optimized for specific needs. Environmental data can refer to the physical state and environmental parameters of various devices in the modified environment, such as the pressure and tilt angle of the modified devices in the modified environment, and the temperature and humidity in the modified environment.

[0019] The target service decision model can refer to a neural network model that has been trained to predict insurance service triggers. This model, once trained, can trigger corresponding insurance services based on user response data, support data, and environmental data. The risk assessment module can refer to a module that predicts the degree of risk of fall injury events, daily care events, and environmental modifications based on response data, support data, and environmental data.

[0020] Specifically, response data such as blood oxygen, fall acceleration, and emergency measures taken by the user at the time of a fall can be obtained based on terminal devices such as accelerometers and smart bracelets. Support data such as heart rate and number of outings during daily care can be obtained based on terminal devices such as smart bracelets and magnetic induction counters. Environmental data such as pressure, tilt angle, temperature, and humidity of the modified equipment in the modified environment can be obtained based on terminal devices such as pressure sensors, three-axis gyroscopes, and temperature and humidity sensors. The response data, support data, and environmental data are input into the risk assessment module of the target service decision model. The risk assessment module calculates and outputs the injury coefficient representing the severity of the fall injury event, the pressure coefficient representing the stress on the user's care, and the risk coefficient representing the risk level of the modified environment.

[0021] Step S203: Input the injury coefficient, stress coefficient, risk technology, response data, support data, and environmental data into the service decision module of the target service decision model, and trigger insurance services for fall injury events, daily care events, and environmental modification through the service decision module.

[0022] In this embodiment, the service decision module can refer to a module that triggers response insurance services based on injury coefficient, stress coefficient, risk technology, response data, support data, and environmental data. The insurance service can refer to an insurance protection plan matched according to the user's injury coefficient, stress coefficient, risk technology, response data, support data, and environmental data. For example, emergency rescue and medical reimbursement services corresponding to emergency insurance triggered for fall injury events, temporary nursing support and health management services corresponding to respite insurance triggered for daily care events, and age-friendly modification subsidies and equipment maintenance services corresponding to modification insurance triggered for environmental modification.

[0023] Specifically, the injury coefficient, stress coefficient, risk technology, response data, support data, and environmental data are input into the service decision module of the target service decision model. The service decision module then triggers insurance services for fall injury events, daily care events, and environmental modifications.

[0024] In this embodiment, the target service decision model identifies the risk coefficient for the corresponding time based on the user's response data to fall injury events, support data for daily care events, and environmental data of the modified environment. This achieves multi-dimensional and dynamic risk assessment, and automatically triggers corresponding insurance services based on the risk coefficient and the above data. This realizes adaptive insurance services based on the user's actual situation, avoids the passive response defects of traditional insurance, improves the efficiency and reliability of insurance services, and enhances the user experience.

[0025] In one embodiment, such as Figure 3 As shown, an insurance service method is provided. In step S202 above, response data is input into the risk assessment module of the target service decision model, and the risk assessment module outputs a damage coefficient characterizing the severity of the fall injury event. The method includes the following steps: Step S301: Determine the user's acceleration and blood oxygen from the response data when the fall injury event was triggered.

[0026] Step S302: Input acceleration and blood oxygen into the risk assessment module, and output the damage coefficient through the risk assessment module.

[0027] Specifically, the injury coefficient characterizes the severity of injury from a fall injury event. The calculation formula can be: , ,in, Let g be acceleration, g be gravity, and b be blood oxygen. The weight is assigned based on the user's historical medical records, and increases with the severity of the historical medical records.

[0028] Optionally, the supporting data is input into the risk assessment module of the target service decision model, and the risk assessment module outputs a stress coefficient that characterizes the degree of care stress on the user, including: determining the user's heart rate variability and care duration from the supporting data, inputting the heart rate variability and care duration into the risk assessment module, and outputting the stress coefficient through the risk assessment module.

[0029] Specifically, wavelet denoising is performed on the user's historical heart rate variability (HRV) data. The root mean square of successive differences (RMSSD) is extracted from the processed data. Based on the extracted RMSSD, a historical stress baseline is calculated (e.g., the average of the RMSSDs of adjacent heart rate intervals at rest over seven consecutive days at 8 AM). The user's current RMSSD and the duration of continuous care received prior to this are then used to obtain a stress coefficient representing the level of caregiving stress for the user. Wherein, the current RMSSD is the standard deviation of the current adjacent heartbeat interval, and the baseline RMSSD is the historical stress baseline. The weight is assigned based on the duration of continuous care the user has received previously, and increases with the duration of care.

[0030] Optionally, environmental data is input into the risk assessment module of the target service decision model, and the risk assessment module outputs a risk coefficient that characterizes the degree of risk of environmental modification. This includes: determining the modification time and number of anomalies of the modified equipment in the modified environment from the environmental data, inputting the modification time and number of anomalies of the modified equipment in the modified environment into the risk assessment module, and outputting the risk coefficient through the risk assessment module.

[0031] Specifically, the risk coefficient characterizes the degree of environmental risk associated with the modification. Where n is the number of equipment malfunctions during the modification, and t is the modification duration. It is a time-degradation factor that decreases as the modification time increases.

[0032] In this embodiment, by calculating the severity of fall injury events, the stress coefficient representing the degree of care pressure on the user, and the risk coefficient representing the degree of risk of environmental modification, based on the user's acceleration and blood oxygenation at the time of fall, the user's heart rate variability and care duration while being cared for, and the modification time and number of anomalies of the modified equipment in the user's environment, a quantitative assessment of user fall injury events, daily care stress, and environmental risks is achieved. This improves the objectivity and accuracy of risk assessment, provides a data foundation for triggering adaptive insurance services based on the user's actual situation, improves the efficiency and reliability of insurance services, and enhances the user experience.

[0033] In one embodiment, such as Figure 4 As shown, an insurance service method is provided. In step S203 above, the injury coefficient, stress coefficient, risk technology, response data, support data, and environmental data are input into the service decision module of the target service decision model. The service decision module triggers insurance services for fall injury events, daily care events, and environmental modifications, including the following steps: Step S401: Determine the user's blood oxygen and emergency response actions when the fall injury event was triggered from the response data.

[0034] Step S402: Input the injury coefficient, blood oxygen, and emergency response operation into the service decision module, and trigger the insurance service corresponding to the emergency insurance through the service decision module.

[0035] For example, if the injury coefficient exceeds a preset threshold, or if the user manually calls for help when falling and their blood oxygen level is below a preset value, the insurance service corresponding to Level A emergency insurance will be activated. The system will automatically call for help, send the injury coefficient and the user's medical history, and plan a route to the hospital. If the injury coefficient does not exceed the preset threshold, the insurance service corresponding to Level B emergency insurance will be activated, such as conducting online video consultations and calling nearby medical personnel for home visits.

[0036] Optionally, the injury coefficient, stress coefficient, risk technology, response data, support data, and environmental data are input into the service decision module of the target service decision model. The service decision module triggers insurance services for fall injury events, daily care events, and environmental modifications. This includes: determining the user's time spent away from home from the support data, inputting the stress coefficient and time spent away from home into the service decision module, and triggering the insurance services corresponding to respite insurance through the service decision module.

[0037] For example, if the stress level exceeds a preset threshold and the duration of time spent away from home exceeds a preset value, the insurance service corresponding to the respite insurance will be triggered, a nearby contracted nursing facility will be located and matched, the service fee will be calculated, and the final payment will be triggered after the service is completed.

[0038] Optionally, the injury coefficient, stress coefficient, risk technology, response data, support data, and environmental data are input into the service decision module of the target service decision model. The service decision module triggers insurance services for fall injury events, daily care events, and environmental modifications. This includes: determining the stress, humidity, and tilt of the modified equipment in the modified environment from the environmental data; inputting the risk coefficient, the stress, humidity, and tilt of the modified equipment in the modified environment into the service decision module; and triggering the corresponding insurance services for the modification insurance through the service decision module.

[0039] For example, if the risk factor exceeds a preset threshold, and the pressure, humidity, and tilt angle of the modified equipment in the modified environment exceed preset values, the insurance service corresponding to the modification insurance will be triggered. The insurance amount of the modification insurance will be adjusted according to the pressure, humidity, and tilt angle of the modified equipment, and the adjusted insurance amount will be pushed to the user.

[0040] In this embodiment, by intelligently triggering graded insurance services (such as A / B level emergency insurance, shortness of breath insurance, and modification insurance) based on injury coefficient, stress coefficient, risk coefficient, and multi-dimensional dynamic data (such as blood oxygen, emergency response, duration of absence, and equipment status), adaptive insurance services based on the user's actual situation are realized. This avoids the passive response defects of traditional insurance, improves the efficiency and reliability of insurance services, and enhances the user experience.

[0041] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0042] In one embodiment, an insurance service device is provided, which corresponds one-to-one with the insurance service method described in the above embodiments. For example... Figure 5 As shown, the insurance service device includes a data acquisition module 51, a risk assessment module 52, and a risk assessment module 53. Detailed descriptions of each functional module are as follows: The data acquisition module 51 is used to acquire user response data to fall injury events, support data for daily care events, and environmental data of the modified environment in which the user is located. The risk assessment module 52 is used to input the response data, the support data and the environmental data into the risk assessment module of the target service decision model, and output the injury coefficient representing the degree of injury of the fall injury event, the stress coefficient representing the degree of care pressure on the user, and the risk coefficient representing the degree of risk of the modified environment through the risk assessment module. The service decision module 53 is used to input the injury coefficient, the stress coefficient, the risk technology, the response data, the support data, and the environmental data into the service decision module of the target service decision model, and trigger insurance services for the fall injury event, the daily care event, and the modified environment through the service decision module.

[0043] Optionally, the aforementioned risk assessment module 52 includes: The first determining unit is used to determine, from the response data, the user's acceleration and blood oxygen at the time the fall injury event was triggered; The first calculation unit is used to input the acceleration and blood oxygen into the risk assessment module, and output the injury coefficient through the risk assessment module.

[0044] Optionally, the aforementioned risk assessment module 52 includes: The second determining unit is used to determine the user's heart rate variability and the duration of care for the user from the supporting data; The second calculation unit is used to input the heart rate variability and the care duration into the risk assessment module, and output the stress coefficient through the risk assessment module.

[0045] Optionally, the aforementioned risk assessment module 52 includes: The third determining unit is used to determine the modification duration and number of anomalies of the modified equipment in the modified environment from the environmental data. The third calculation unit is used to input the modification time and number of anomalies of the modified equipment in the modified environment into the risk assessment module, and output the risk coefficient through the risk assessment module.

[0046] Optionally, the aforementioned service decision module 53 includes: The fourth determining unit is used to determine, from the response data, the user's blood oxygen and emergency response operation when the fall injury event was triggered; The first triggering unit is used to input the injury coefficient, the blood oxygen, and the emergency response operation into the service decision module, and trigger the insurance service corresponding to the emergency insurance through the service decision module.

[0047] Optionally, the aforementioned service decision module 53 includes: The fifth determining unit is used to determine the user's outing duration from the supporting data; The second triggering unit is used to input the pressure coefficient and the support data into the service decision module, and trigger the insurance service corresponding to the respite service insurance through the service decision module.

[0048] Optionally, the aforementioned service decision module 53 includes: The sixth determining unit is used to determine the pressure, humidity, and tilt degree of the modified equipment in the modified environment from the environmental data; The third triggering unit is used to input the risk coefficient, the pressure, humidity and tilt of the modified equipment in the modified environment into the service decision module, and trigger the insurance service corresponding to the modification insurance through the service decision module.

[0049] Specific limitations regarding the insurance service device can be found in the limitations of the insurance service method described above, and will not be repeated here. Each module in the aforementioned insurance service device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0050] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6As shown. The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores user response data to fall injury events, support data for daily care events, and environmental data of the modified environment. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements an insurance service method.

[0051] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the insurance service method described in the above embodiments, for example... Figure 2 As shown in S201-S203, or Figures 3 to 4 As shown, to avoid repetition, it will not be described again here. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in this embodiment of the insurance service device, for example, Figure 5 The functions of the data acquisition module 51, risk assessment module 52, and risk assessment module 53 shown are not described again here to avoid duplication.

[0052] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When executed by a processor, the computer program implements the insurance service method described in the above embodiment, for example... Figure 2 As shown in S201-S203, or Figures 3 to 4 As shown, to avoid repetition, it will not be described again here. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in this embodiment of the insurance service device, for example, Figure 5 The functions of the data acquisition module 51, risk assessment module 52, and risk assessment module 53 shown are not described again here to avoid duplication.

[0053] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0054] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0055] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. An insurance service method, characterized in that, include: Acquire user response data for fall injury events, support data for daily care events, and environmental data of the modified environment in which the user is located; The response data, the support data, and the environmental data are input into the risk assessment module of the target service decision model. The risk assessment module outputs a harm coefficient representing the severity of the fall injury event, a stress coefficient representing the level of care pressure on the user, and a risk coefficient representing the level of risk of the modified environment. The injury coefficient, the stress coefficient, the risk technology, the response data, the support data, and the environmental data are input into the service decision module of the target service decision model. The service decision module then triggers insurance services for the fall injury event, the daily care event, and the modified environment.

2. The insurance service method according to claim 1, characterized in that, The step of inputting the response data into the risk assessment module of the target service decision model, and outputting a damage coefficient characterizing the severity of the fall injury event through the risk assessment module, includes: From the response data, determine the user's acceleration and blood oxygen levels at the time the fall injury event was triggered; The acceleration and blood oxygen levels are input into the risk assessment module, which then outputs the damage coefficient.

3. The insurance service method according to claim 1, characterized in that, The step of inputting the supporting data into the risk assessment module of the target service decision model, and outputting a stress coefficient representing the degree of care stress on the user through the risk assessment module, includes: From the supporting data, the user's heart rate variability and the duration of care for the user are determined; The heart rate variability and the duration of care are input into the risk assessment module, and the stress coefficient is output through the risk assessment module.

4. The insurance service method according to claim 1, characterized in that, The step of inputting the environmental data into the risk assessment module of the target service decision model, and outputting a risk coefficient characterizing the degree of risk of the modified environment through the risk assessment module, includes: From the environmental data, determine the modification time and number of anomalies of the modified equipment in the modified environment; The modification time and number of anomalies of the modified equipment in the modified environment are input into the risk assessment module, and the risk assessment module outputs the risk coefficient.

5. The insurance service method according to claim 1, characterized in that, The process of inputting the injury coefficient, stress coefficient, risk technology, response data, support data, and environmental data into the service decision module of the target service decision model, and triggering insurance services for the fall injury event, the daily care event, and the modified environment through the service decision module, includes: From the response data, determine the user's blood oxygen and emergency response actions at the time the fall injury event was triggered; The injury coefficient, blood oxygen level, and emergency response operation are input into the service decision module, which then triggers the insurance service corresponding to the emergency medical insurance.

6. The insurance service method according to claim 1, characterized in that, The process of inputting the injury coefficient, stress coefficient, risk technology, response data, support data, and environmental data into the service decision module of the target service decision model, and triggering insurance services for the fall injury event, the daily care event, and the modified environment through the service decision module, includes: The duration of the user's absence is determined from the supporting data; The pressure coefficient and the travel information are input into the service decision module, which then triggers the insurance service corresponding to the respite service insurance.

7. The insurance service method according to claim 1, characterized in that, The process of inputting the injury coefficient, stress coefficient, risk technology, response data, support data, and environmental data into the service decision module of the target service decision model, and triggering insurance services for the fall injury event, the daily care event, and the modified environment through the service decision module, includes: From the environmental data, determine the pressure, humidity, and tilt of the modified equipment in the modified environment; The risk coefficient, the pressure, humidity, and tilt of the modified equipment in the modified environment are input into the service decision module, and the insurance service corresponding to the modification insurance is triggered through the service decision module.

8. An insurance service device, characterized in that, include: The data acquisition module is used to acquire user response data for fall injury events, support data for daily care events, and environmental data of the modified environment in which the user is located. The risk assessment module is used to input the response data, the support data, and the environmental data into the risk assessment module of the target service decision model. The risk assessment module outputs a harm coefficient representing the severity of the fall injury event, a stress coefficient representing the degree of care pressure on the user, and a risk coefficient representing the degree of risk of the modified environment. The service decision module is used to input the injury coefficient, the stress coefficient, the risk technology, the response data, the support data, and the environmental data into the service decision module of the target service decision model, and trigger insurance services for the fall injury event, the daily care event, and the modified environment through the service decision module.

9. A computer device, characterized in that, The computer device includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the insurance service method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the insurance service method as described in any one of claims 1 to 7.

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