Event prompting method, apparatus, device, and storage medium

Abstract

The embodiment of the application provides an event prompting method, device and equipment and a storage medium, the method comprises the following steps: if a pet image after a pet is inoculated with a vaccine is received, acquiring the associated pet image and pet information of the pet; acquiring the state feature of the pet according to the pet image and the associated pet image of the pet, and acquiring the preset state feature of the vaccine adverse reaction event according to the pet information and the vaccine information of the inoculated vaccine; if the state feature of the pet and the preset state feature are matched successfully, it is determined that the pet has the vaccine adverse reaction event; and sending the prompt information of the vaccine adverse reaction event to the object corresponding to the pet. By adopting the embodiment of the application, the accuracy of judging adverse reactions and the effectiveness of state monitoring can be improved.

Description

Technical Field

[0001] This application relates to the field of Internet technology, and in particular to an event notification method, apparatus, device, and storage medium. Background Technology

[0002] With economic development, more and more people are keeping pets. Pets need to receive different vaccines at different stages, and reactions may occur to varying degrees after vaccination. Different pets may experience different reactions, and severe adverse reactions can be life-threatening. Pet owners usually judge the situation based on their pet's condition or consult professionals for assessment. However, human judgment involves subjective factors, and different pets may react differently, leading to the possibility of misjudgment. Summary of the Invention

[0003] This application provides an event notification method, apparatus, device, and storage medium. After a pet is vaccinated, the method determines whether the pet has experienced an adverse vaccine reaction by using the status characteristics obtained from the current pet image and associated pet images. This can improve the accuracy of adverse reaction detection and the effectiveness of status monitoring.

[0004] This application provides an event notification method, comprising: if a pet image after vaccination is received, obtaining associated pet images and pet information; obtaining pet status features based on the pet image and associated pet images, and obtaining preset status features of adverse vaccine reaction events based on the pet information and vaccination information; if the pet status features match the preset status features, determining that the pet has experienced an adverse vaccine reaction event; and sending a notification message about the adverse vaccine reaction event to the corresponding object. Thus, by determining whether a pet has experienced an adverse vaccine reaction event through status features obtained from the current pet image and associated pet images after vaccination, the accuracy of adverse reaction detection and the effectiveness of status monitoring can be improved.

[0005] In one possible example, obtaining a pet's state characteristics based on a pet image and associated pet images includes: obtaining a correlation value between the pet image and associated pet images; obtaining first state data of the pet based on the pet image, and obtaining second state data of the pet based on the associated pet images; and fusing the first and second state data based on the correlation value to obtain the pet's state characteristics. Thus, fusing the first state data obtained from the pet image and the second state data obtained from the associated pet image based on the correlation value can improve the accuracy of obtaining the pet's state characteristics, which is beneficial for improving the accuracy of determining whether an adverse reaction has occurred.

[0006] In one possible example, obtaining the correlation value between the pet's image and related pet images includes: obtaining scene data and / or physiological parameters for both the pet's image and related pet images; and obtaining the correlation value between the pet's image and related pet images based on the scene data and / or physiological parameters. This improves the accuracy of obtaining the correlation value, which in turn enhances the accuracy of determining whether an adverse reaction has occurred.

[0007] In one possible example, after obtaining the pet's status characteristics based on the pet's image and associated pet images, the process further includes updating the pet's status characteristics based on physiological parameters. This can further improve the accuracy of the status characteristics, which is beneficial for improving the accuracy of determining whether an adverse reaction has occurred.

[0008] In one possible example, before sending the adverse vaccine reaction notification to the pet, the process includes: obtaining the risk level of the adverse vaccine reaction based on the pet's condition; obtaining precautions for the adverse vaccine reaction based on the risk level; and generating the notification message based on the precautions. This allows for the generation of notification messages based on the risk level, improving the accuracy and effectiveness of the precautions.

[0009] In one possible example, after determining the risk level of an adverse vaccine reaction based on the pet's condition, the process includes: if the risk level is higher than a preset level, sending a call request to the pet's corresponding hospital, instructing the hospital to provide medical resources. This improves the hospital's emergency response speed and enhances the effectiveness of condition monitoring.

[0010] In one possible example, before sending a call request to the pet's corresponding hospital, the process includes: obtaining the pet's location, insurance information, and medical history; determining the priority of each of the multiple hospitals corresponding to the pet's location based on the pet's insurance information and medical history; and determining the corresponding hospital based on the hospital priority. In this way, determining the hospital corresponding to the call request based on hospital priority can improve the efficiency and effectiveness of emergency response.

[0011] One embodiment of this application provides an event notification device, including:

[0012] The communication unit is used to receive images of the pet.

[0013] The processing unit is used to obtain the pet's status features based on the pet's pet image and associated pet images, and to obtain the preset status features of adverse vaccine reaction events based on the pet's information and the vaccine information. If the pet's status features match the preset status features, it is determined that the pet has experienced an adverse vaccine reaction event.

[0014] The communication unit is also used to send alerts about adverse vaccine reaction events to the corresponding pet.

[0015] One aspect of this application provides a computer device, including a memory and a processor connected to the memory. The memory stores a computer program, and the processor invokes the computer program to cause the computer device to execute the method provided in one aspect of this application.

[0016] One aspect of this application provides a computer-readable storage medium. This computer-readable storage medium stores a computer program adapted to be loaded and executed by a processor, causing a computer device having a processor to perform the method provided in one aspect of this application.

[0017] According to one aspect of this application, a computer program product is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method provided in the above aspect.

[0018] In this embodiment, if a pet image after vaccination is received, the associated pet image and pet information are obtained. Then, the pet's status features are obtained based on the pet image and associated pet images, and preset status features for adverse vaccine reaction events are obtained based on the pet information and vaccination information. If the pet's status features match the preset status features, an adverse vaccine reaction event is determined. In other words, after a pet is vaccinated, determining whether an adverse vaccine reaction event has occurred by using the status features obtained from the current pet image and associated pet images improves the accuracy of adverse reaction detection. After determining that an adverse vaccine reaction event has occurred, a notification message can be sent to the corresponding entity, improving the effectiveness of status monitoring. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of a network architecture provided in an embodiment of this application;

[0021] Figure 2This is a schematic diagram of an event notification scenario provided in an embodiment of this application;

[0022] Figure 3 A flowchart illustrating an event notification method provided in an embodiment of this application;

[0023] Figure 4 This is a schematic diagram illustrating a scenario for uploading pet images, provided as an embodiment of this application.

[0024] Figure 5 A flowchart illustrating a state feature recognition method provided in an embodiment of this application;

[0025] Figure 6 A schematic diagram illustrating another event notification scenario provided in an embodiment of this application;

[0026] Figure 7 This is a schematic diagram of the structure of an event notification device provided in an embodiment of this application;

[0027] Figure 8 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0028] This application does not limit the type of pet, and may include common pets such as cats, dogs, birds, and turtles, as well as less common pets such as chickens, pigs, snakes, lizards, geckos, and lions. In the embodiments of this application, pet information may include the pet's name, nose print, and other identifying information, as well as pet attributes such as breed, age, sex, skin color, and fur color. Pet information may also include historical medical records, vaccination records, and insurance information.

[0029] The pet's medical history records information on each visit, including details for each visit. This information may include the type of visit, current medical history, past medical history, physical examination data, and diagnostic information. It may also include the hospital visited and follow-up information; there are no specific limitations. The vaccination history records the pet's vaccination status, including whether any vaccines were administered and whether any adverse reactions occurred. The insurance information describes any insurance policies the pet has purchased, including the insurance name, policy number, insurance company, insured, beneficiary, coverage, terms and conditions, premium amount, and claims instructions; there are no specific limitations on this information.

[0030] Furthermore, pet information may also include the pet's preference characteristics, such as dietary characteristics, daily routine characteristics, exercise preferences, health status, etc., without limitation.

[0031] This application does not limit the object corresponding to the pet; it can be the pet's owner or caretaker, etc. The number of objects corresponding to a pet can be one, two, or more. In the embodiments of this application, object information can include object attributes. These object attributes can include basic information such as the object's identification information (e.g., name, identity identifier, account identifier, etc.), age, gender, occupation, and address. They can also include the object's social data, such as social relationships online or in real life. Object attributes may also include tags for the object, such as hobbies and behavioral habits.

[0032] Object information can also be categorized by time of occurrence into real-time data and historical data. Real-time data can include relevant data from the user terminal currently being used by the object, such as currently searched keywords and browsed content. Historical data can include the object's previous shopping records and browsing history from other user terminals. By leveraging historical data, the object's preference characteristics can be obtained, allowing for the determination of whether to send corresponding push notifications based on whether there is a match between the data characteristics of the real-time scenario and the object's preference characteristics.

[0033] Pet information and / or object information can be uploaded to a server for storage or stored on a blockchain. The blockchain referred to in this application is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Essentially, a blockchain is a decentralized database, a chain of data blocks linked using cryptographic methods. Each data block contains information about a batch of network transactions, used to verify the validity of the information (anti-counterfeiting) and generate the next block. A blockchain can include an underlying blockchain platform, a platform product service layer, and an application service layer. Thus, by distributing data storage through the blockchain, data security can be ensured while enabling data sharing between different platforms.

[0034] This application does not limit the scenarios for storing pet information and / or object information. It can be used for scenarios such as pets visiting hospitals, receiving vaccinations, grooming, undergoing physical examinations, handling hospitalization procedures, applying for insurance, and obtaining identity information. It is understood that after storing pet and object information, information about the pet can be pushed to the target based on this information, improving the accuracy of the pushed pet information.

[0035] It should be noted that the specific implementation of this application may involve data of users, enterprises, institutions, etc. When the above embodiments of this application are applied to specific products or technologies, permission or consent from users, enterprises, institutions, etc. is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0036] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0037] Please see Figure 1 , Figure 1 This is a schematic diagram of a network architecture provided in an embodiment of this application. Figure 1 As shown, this network architecture may include a server 10d and a user terminal cluster. The user terminal cluster may include one or more user terminals; the number of user terminals is not limited here. Figure 1 As shown, the user terminal cluster may specifically include user terminal 10a, user terminal 10b, and user terminal 10c, etc.

[0038] Among them, server 10d can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0039] User terminals 10a, 10b, and 10c can all include: smartphones, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices (such as smartwatches and smart bracelets), smart voice interaction devices, smart home appliances (such as smart TVs), and in-vehicle devices, as well as other electronic devices with video / image playback functions.

[0040] like Figure 1 As shown, user terminals 10a, 10b, and 10c can each connect to server 10d via a network, enabling data interaction between each user terminal and server 10d. For example, a first object may send its own information to server 10d via user terminal 10a, while a second object may receive a push message from server 10d via user terminal 10b. Another example is server 10d sending a vaccination notification to a target object via user terminal 10a.

[0041] The following example uses user terminal 10a. Please refer to [link / reference]. Figure 2, Figure 2 This is a schematic diagram illustrating an event notification scenario provided in an embodiment of this application. For example... Figure 2 As shown, the pet can upload a pet image 201 via user terminal 10a. Then, server 10d can obtain the pet's associated pet image and pet information, and determine whether the pet has experienced an adverse vaccine reaction based on the pet image 201, the associated pet image, and the pet information. If so, a notification message about the adverse vaccine reaction is sent to user terminal 10a.

[0042] The associated pet image may include any historical image of the pet, or it may include historical images of the pet before the pet image 201 was vaccinated, or it may include historical images of the pet after the last vaccination of the same type of vaccine, etc., without limitation.

[0043] The application does not limit the types of adverse reactions that occur in pets in relation to adverse vaccine events. These reactions may include depression, difficulty breathing, severe vomiting, swollen eyes that cannot be opened, skin rashes (or hives), loss of appetite, lethargy, and redness and swelling at the injection site.

[0044] It should be noted that the scenario illustrations above are for illustrative purposes only. In reality, the corresponding pet user can also upload the pet's physiological parameters. These physiological parameters can include measured data such as body temperature, heart rate, water intake, urine output, respiration, pulse, and blood pressure. Physiological parameters can also be based on data derived from the pet's outward appearance, such as mood, appetite, and sleep duration; there are no restrictions on this.

[0045] The event notification method provided in the embodiments of this application is described in detail below. Please refer to... Figure 3 , Figure 3 This is a flowchart illustrating an event notification method provided in an embodiment of this application. The method can be executed by an event notification device or a computer device, which can be a server (e.g., Figure 1 The corresponding embodiment is a server 10d), or a user terminal (e.g., Figure 1 This could refer to any user terminal in the user terminal cluster shown, or a computer program (including program code), etc. Figure 3 As shown, the method includes the following steps S301 to S304, wherein:

[0046] S301: If a pet image after vaccination is received, obtain the pet's associated pet image and pet information.

[0047] The pet images, associated pet images, and pet information are as described above or below, and will not be repeated here. The pets involved in this application are those that have completed vaccination. There is no limitation on the time period for receiving pet images after vaccination; it can be any time period, such as one day, 8 hours, 12 hours, etc., or at preset fixed intervals, such as every half hour, every hour, etc. For example, every 5 minutes for the first 30 minutes, and every half hour thereafter. It is understood that dangerous adverse reactions are likely to occur in the first 30 minutes after vaccination, hence the use of shorter time intervals to acquire pet images. Slightly longer time intervals can then be used to acquire pet images, thus improving the effectiveness of monitoring by acquiring pet images based on dynamic time intervals.

[0048] In one possible example, the time information for uploading the pet image is determined based on the pet's associated pet image and / or pet information; a push notification corresponding to the time information is sent to the object corresponding to the pet.

[0049] The time information can include the time or time interval at which the pet image was uploaded. The push notification can indicate a specific time or time range. It can be understood that the associated pet image is a previously uploaded pet image that reflects the pet's condition. Pet information can be used to determine the response of different types of pets to vaccinations. Therefore, in this example, the time information for uploading the pet image can be determined based on the pet's associated pet image and / or pet information, and a push notification corresponding to that time information can be sent to the corresponding recipient, allowing the recipient to upload pet images based on the time or time interval specified in the push notification.

[0050] For example, please refer to Figure 4 , Figure 4 This is a schematic diagram illustrating a scenario for uploading pet images, provided as an embodiment of this application. Figure 4 As shown, server 10d can send a push notification to user terminal 10a with the time information corresponding to the time of uploading the pet image, so that user terminal 10a displays "Please upload pet image within 5 minutes". Object 101 can upload pet image 201 on the upload page 200 of user terminal 10a and click upload component 202 to upload, so that server 10d receives the pet image 201 after the pet has been vaccinated. If object 101 clicks cancel component 203, the upload of pet image 201 is canceled, and other pet images can be uploaded, or no more pet images can be uploaded.

[0051] Pet images can be taken and uploaded by the pet's owner or captured by surveillance cameras. Alternatively, pet images can be extracted from surveillance camera videos and then filtered to remove incomplete images and retain clear ones, which improves the accuracy of pet image analysis.

[0052] Linking pet images and pet information can be done based on nasal print features extracted from pet images. This application does not limit the method for recognizing nasal print features; the pet image can be input into a nasal print recognition platform, which will then output nasal print features. The nasal print recognition platform can first preprocess the pet image, such as image denoising, image correction, image enhancement, and feature incompleteness correction. Then, it sequentially performs border detection on the preprocessed image to obtain the nasal print image, and then performs feature extraction on the nasal print image to obtain the nasal print features. The border detection can be implemented using multiple border detection models, and the feature extraction can be implemented using multiple feature extraction models, with each border detection model having a corresponding feature extraction model. Thus, using multiple models for nasal print feature recognition can improve the accuracy of nasal print feature recognition. Before preprocessing, the pet image can also be verified for authenticity, i.e., liveness detection, to confirm whether the pet in the pet image is a real pet.

[0053] S302: Obtain the pet's status characteristics based on the pet's pet image and associated pet images, and obtain the preset status characteristics of adverse vaccine reaction events based on the pet's information and the vaccine information.

[0054] S303: If the pet's status characteristics successfully match the preset status characteristics, then it is determined that the pet has experienced an adverse reaction to the vaccine.

[0055] In this embodiment, adverse reactions in vaccine adverse reaction events may include lethargy, difficulty breathing, severe vomiting, swollen eyes that cannot be opened, skin rashes (or hives), loss of appetite, drowsiness, and swelling at the injection site. The state characteristics and preset state characteristics may include the following categories: mental state characteristics, gastrointestinal state characteristics, skin state characteristics, etc., which are not limited here. It is understood that if a pet experiences an adverse reaction, it may exhibit the state characteristics of the adverse reaction. This application matches the pet's state characteristics with the preset state characteristics of vaccine adverse reaction events; if the match is successful, it is determined that the pet has experienced a vaccine adverse reaction event.

[0056] Vaccine information may include the vaccine manufacturer, vaccine type (e.g., attenuated virus vaccine and inactivated vaccine), number of vaccinations, target population, recommended vaccination time, and adverse reactions. It is understood that different pets may react differently to the same vaccine. Therefore, in this embodiment, obtaining preset state characteristics of adverse vaccine reaction events based on pet information and vaccination information can improve the accuracy of determining whether an adverse reaction has occurred. Specifically, state characteristics corresponding to one or more of the pet's breed, age, and pre-vaccination physiological parameters can be found in the vaccination information regarding the state characteristics of adverse vaccine reaction events and used as preset state characteristics for adverse vaccine reaction events.

[0057] This application does not limit the method for obtaining the pet's state features. The state features of the pet image and associated pet images can be obtained separately before data fusion. Alternatively, a state recognition model can be pre-trained, and the pet image and associated pet images can be input into this model to obtain the pet's state features. This state recognition model can be unsupervised learning based on contrastive predictive coding (CPC) technology.

[0058] State recognition models can include feature recognition networks and feature learning networks. Feature recognition networks can include deep residual networks (ResNet), which address the degradation problem of deep networks through residual learning, allowing for the training of even deeper networks. Feature learning networks can include recurrent neural networks (RNNs), used to predict the state information of the next time step based on previous state information. Specifically, this can include long short-term memory networks (LSTM), which can solve the problem of long-term dependencies.

[0059] For example, please refer to Figure 5 , Figure 5 This is a flowchart illustrating a state feature recognition method provided in an embodiment of this application. Figure 5 As shown, the pet image and associated pet image are input into the feature recognition network to obtain the first state feature corresponding to the pet image and the second state feature corresponding to the associated pet image. The first and second state features are then input into the feature learning network to obtain the pet's state features, and the state features for the next time step can also be obtained.

[0060] Furthermore, the pet image and associated pet images can be divided into images of different body parts, such as face images and limb images. The face image can be further divided into eye images, nose images, mouth images, etc. Images of different body parts can be input into a feature recognition network to obtain the state features of different parts in a single image. Then, the state features of different parts in a single image are input into a feature learning network to learn the state features of the pet image and associated pet images. This improves the accuracy of feature recognition and can also be used to predict the state features at the next moment. If there are multiple associated pet images, the second state features of the associated pet images can be obtained sequentially in chronological order. Optionally, the number of associated pet images can be a fixed value, such as 5. In this way, a certain number of associated pet images and pet images can be used to determine the pet's state features and predict the state features at the next moment, which helps improve the accuracy and efficiency of judging adverse reactions.

[0061] In one possible example, the step of obtaining the pet's state features based on the pet's pet image and associated pet images may include the following steps: obtaining the association value between the pet's pet image and associated pet images; obtaining the pet's first state data based on the pet's pet image, and obtaining the pet's second state data based on the pet's associated pet images; and fusing the first state data and the second state data based on the association value to obtain the pet's state features.

[0062] The correlation value between a pet image and associated pet images describes the degree of association between them. This can be determined by the similarity value between the pet image and associated pet images. Alternatively, in one possible example, the method for obtaining the correlation value between a pet image and associated pet images may include the following steps: obtaining scene data and / or physiological parameters between the pet image and associated pet images; and obtaining the correlation value between the pet image and associated pet images based on the scene data and / or physiological parameters.

[0063] The scene data may include the time of capturing the pet image and related pet images, the angle at which the pet was captured, and the camera equipment used. Physiological parameters can be referred to above or below, and will not be repeated here. The correlation value can be obtained based on the difference in scene data and / or the parameters of the physiological parameters. The difference in scene data may include the time interval between capturing the pet image and related pet images. This time interval can be obtained by the difference in time between capturing the pet image and related pet images, or by multiplying a preset time interval between pet images by the number of images between the pet image and related pet images.

[0064] It is understandable that the closer the scene data or physiological parameters are, the more reliable the associated pet images become. In this example, obtaining the correlation value between the pet image and the associated pet image based on the scene data and / or physiological parameters of the pet image and the associated pet image can improve the accuracy of obtaining the correlation value, which is beneficial to improving the accuracy of judging whether an adverse reaction has occurred.

[0065] In this embodiment of the application, the first state data and the second state data are the state data corresponding to the pet image and the associated pet image, respectively, and may include the aforementioned state features (such as...). Figure 5 The data refers to the first and second state features shown, or the data corresponding to the state features. The dimensions corresponding to the state features of the first and second state data can be the same, such as the mental dimension, skin dimension, etc. The following pet image is used as an example. In one possible example, a method for obtaining the first state data of a pet based on a pet image may include the following steps: obtaining the pet's action data, expression data, and color data from the pet image; obtaining the pet's mental state data from the action data and expression data; and obtaining the pet's skin state data from the color data.

[0066] Motion data can be obtained from the pet's body movements in pet images. Facial expression data can be obtained from the pet's facial images, specifically from the nasal print features in the pet's images, such as the texture features of the nose itself and the micro-expressions corresponding to the texture features produced by micro-movements. Color data can be determined from the fur color and facial color in the pet images. Mental state data can be obtained from the amplitude of movements corresponding to the motion data and the emotion vectors corresponding to the facial expression data. Skin condition data can be obtained from areas of abnormal color in the color data. It can be understood that extracting images or image data related to state data from pet images can improve the accuracy of obtaining state data, which is beneficial for improving the accuracy of judging whether adverse reactions have occurred. Furthermore, health status data can be determined based on mental state data and skin condition data. That is, determining health status data based on the mapping relationship between mental state and health status, and between skin condition and health status, can improve the accuracy of judging adverse reactions.

[0067] This application does not limit the method for fusing the first and second state data using correlation values. The weights of the first and second state data can be determined separately using the correlation values. For example, the larger the correlation value, the closer the weights of the first and second state data are. The smaller the correlation value, the greater the weight of the first state data compared to the weight of the second state data. The state features corresponding to the first and second state data are then weighted separately to obtain the pet's state features. Alternatively, the product of the correlation value and the state features corresponding to the second state data can be obtained, and then added to the state features corresponding to the first state data to obtain the pet's state features.

[0068] It is understandable that fusing the first state data obtained from the pet image based on the correlation value and the second state data obtained from the associated pet image can improve the accuracy of obtaining the pet's state characteristics, which is beneficial to improving the accuracy of judging whether an adverse reaction has occurred.

[0069] In one possible example, after obtaining the pet's status features based on the pet's pet image and associated pet images, the process also includes updating the pet's status features based on physiological parameters.

[0070] Physiological parameters reflect a pet's state and can be used to update the pet's state characteristics. This application does not limit the method for updating the pet's state characteristics. Reference state characteristics corresponding to the physiological parameters can be obtained based on the mapping relationship between the physiological parameters and various state characteristics. The state characteristics are then updated based on the reference state characteristics. For example, sub-features not included in the state characteristics (such as heart rate and blood pressure) can be added, while sub-features already included in the state characteristics (such as emotional characteristics and skin characteristics) can be weighted. This can further improve the accuracy of the state characteristics, which is beneficial for improving the accuracy of judging whether adverse reactions have occurred.

[0071] S304: Send a notification message about an adverse vaccine reaction event to the pet's corresponding object.

[0072] In this embodiment, notification information regarding adverse vaccine reactions can be sent to the pet's corresponding recipient via SMS, email, or app push notifications. This application does not limit the content of the notification information, which may include alarm information about the adverse vaccine reaction, emergency handling procedures, and precautions. The alarm information informs the recipient that the pet has experienced an adverse vaccine reaction. The emergency handling procedures inform the recipient how to handle the adverse reaction, such as taking the pet to a veterinary hospital and minimizing outings. The precautions inform the recipient of necessary precautions, such as avoiding bathing, avoiding contact with sick individuals, providing extra care, and avoiding external stressors.

[0073] In one possible example, before step S304, the following steps may also be included: obtaining the risk level of the adverse vaccine reaction event based on the pet's condition characteristics; obtaining precautions for the adverse vaccine reaction event based on the risk level; and generating a prompt message for the adverse vaccine reaction event based on the precautions.

[0074] The hazard level describes the extent to which adverse vaccine events affect a pet's life. It can be determined by the corresponding hazard level for specific characteristics, such as an unstable hazard level for mental state, a gastrointestinal hazard level for the number of vomiting episodes, and an itching hazard level for the area of ​​itchy skin.

[0075] In this example, the risk level of an adverse vaccine reaction is determined based on the pet's condition. Then, precautions are derived based on the risk level, allowing for the generation of warning messages. This method of generating warning messages based on risk levels improves the accuracy and effectiveness of these warnings.

[0076] In one possible example, after obtaining the risk level of adverse vaccine reaction events based on the pet's condition characteristics, the following steps are also included: if the risk level is greater than a preset level, a call request is sent to the pet's corresponding hospital.

[0077] The call request is used to instruct the hospital to provide medical resources, such as dispatching an ambulance, assigning doctors and nurses, and reserving medical equipment, etc., and is not limited here. This application does not limit the hospital for the pet, and can be a hospital near the pet, a hospital that can be reimbursed by insurance, a frequently visited hospital, a hospital with a high rating, or a hospital without a queue, etc.

[0078] In one possible example, before sending a call request to the hospital corresponding to the pet, the process includes: obtaining the pet's location, insurance information, and medical history; determining the priority of each of the multiple hospitals corresponding to the pet's location based on the pet's insurance information and medical history; and determining the hospital corresponding to the pet based on the hospital's priority.

[0079] Here, "Pet Location" refers to the pet's current location, which can be a specific location or a regional area. The multiple hospitals corresponding to the pet's location can be hospitals within a regional area, or hospitals within a certain time range (e.g., 30 minutes). Insurance information and historical medical records can be referenced above and are not limited here. "Priority" describes the order in which hospitals process call requests; that is, the higher the priority, the greater the likelihood of going to a hospital. Priority is calculated by weighting the distance between the pet and the hospital, whether the hospital supports insurance reimbursement, and whether the pet has previously been treated at another hospital.

[0080] Understandably, in this example, determining the priority of the hospital corresponding to the pet's location based on the pet's insurance information and historical medical records, and then determining the hospital corresponding to the call request based on the hospital's priority, can improve the efficiency and effectiveness of emergency treatment.

[0081] This application does not limit the preset level; it can be a fixed level, or it can be determined based on the type of vaccine administered, or it can be determined based on factors such as the distance between the pet and its owner. It is understood that different vaccines have different adverse reaction effects, and determining the preset level based on the type of vaccine administered can improve the accuracy of calling a veterinary clinic.

[0082] For example, please refer to Figure 6 , Figure 6 This is a schematic diagram illustrating another event notification scenario provided in an embodiment of this application. For example... Figure 6 As shown, Figure 6 As shown, the pet can upload a pet image 201 via user terminal 10a. Then, server 10d can obtain the pet's status characteristics based on the pet image 201 and associated pet images. If the pet's status characteristics match the preset status characteristics of an adverse vaccine reaction event, then the pet is confirmed to have experienced an adverse vaccine reaction. Server 10d can also obtain the risk level of the adverse vaccine reaction event based on the pet's status characteristics. If the risk level is greater than the preset level, a warning message indicating the adverse vaccine reaction event based on the risk level can be sent to user terminal 10a, and a call request can be sent to hospital 202.

[0083] It should be noted that, Figure 6 This is a procedure performed when the pet is outside of a hospital. If the pet is currently in a hospital, the corresponding hospital is the one where the pet is currently located, and the call request is used to instruct the specific department, doctor, or nurse in the hospital to perform the procedure to handle the pet's adverse reaction.

[0084] exist Figure 3 In the method shown, if a pet image after vaccination is received, the associated pet image and pet information are obtained. Then, the pet's status characteristics are obtained based on the pet image and associated pet images, and preset status characteristics for adverse vaccine reaction events are obtained based on the pet information and vaccination information. If the pet's status characteristics match the preset status characteristics, an adverse vaccine reaction event is determined. In other words, determining whether a pet has experienced an adverse vaccine reaction event by using the status characteristics obtained from the current pet image and associated pet images after vaccination improves the accuracy of adverse reaction detection. After determining that an adverse vaccine reaction event has occurred, a notification message can be sent to the corresponding entity, improving the effectiveness of status monitoring.

[0085] The methods of the embodiments of this application have been described in detail above, and the apparatus of the embodiments of this application is provided below.

[0086] Please see Figure 7 , Figure 7 This is a schematic diagram of an event notification device provided in an embodiment of this application. Figure 7 As shown, the event notification device includes a processing unit 701 and a communication unit 702, wherein:

[0087] Communication unit 702 is used to receive pet images of the pet;

[0088] The processing unit 701 is used to obtain the status features of the pet based on the pet image and associated pet image, and to obtain the preset status features of the adverse vaccine reaction event based on the pet information and the vaccine information of the vaccination; if the status features of the pet match the preset status features, it is determined that the pet has experienced an adverse vaccine reaction event.

[0089] The communication unit 702 is also used to send a notification message about the adverse reaction event of the vaccine to the object corresponding to the pet.

[0090] In one possible example, the processing unit 701 is specifically used to obtain the association value between the pet image of the pet and the associated pet image; obtain the first state data of the pet based on the pet image of the pet, and obtain the second state data of the pet based on the associated pet image of the pet; and perform fusion processing on the first state data and the second state data based on the association value to obtain the state features of the pet.

[0091] In one possible example, the processing unit 701 is specifically used to acquire scene data and / or physiological parameters of the pet image and associated pet image of the pet, respectively; and to acquire the correlation value between the pet image and associated pet image of the pet based on the scene data and / or physiological parameters.

[0092] In one possible example, the processing unit 701 is also configured to update the pet's state characteristics based on the physiological parameters.

[0093] In one possible example, the processing unit 701 is further configured to obtain the risk level of the adverse vaccine reaction event based on the pet's state characteristics; obtain precautions for the adverse vaccine reaction event based on the risk level; and generate a prompt message for the adverse vaccine reaction event based on the precautions.

[0094] In one possible example, the communication unit 702 is also configured to send a call request to the hospital corresponding to the pet if the danger level is greater than a preset level, the call request being used to instruct the hospital to provide medical resources.

[0095] In one possible example, the processing unit 701 is further configured to obtain the pet's location, insurance information, and historical medical records; determine the priority of each hospital among multiple hospitals corresponding to the pet's location based on the pet's insurance information and historical medical records; and determine the hospital corresponding to the pet based on the hospital's priority.

[0096] Please refer to Figure 8 , Figure 8 This is a schematic diagram of a computer device provided in an embodiment of this application. The computer device 800 includes a processor 801, a communication interface 802, and a memory 803. The processor 801, the communication interface 802, and the memory 803 can be interconnected via a bus 805 or other means. Figure 7 The functions implemented by the processing unit 701 shown can be implemented by one or more processors 801. Figure 7 The functions implemented by the communication unit 702 shown can be realized through the communication interface 802.

[0097] The processor 801 includes one or more processors, such as one or more central processing units (CPUs). When the processor 801 is a CPU, the CPU can be a single-core CPU or a multi-core CPU. In this embodiment, the processor 801 is used to control the computer device 800. Figure 3 The example shown.

[0098] The communication interface 802 is used to enable communication with other devices. For example, if the computer device 800 is a user terminal, the communication interface 802 can enable communication between the user terminal and devices such as servers; if the computer device 800 is a server, the communication interface 802 can enable communication between the server and devices such as user terminals.

[0099] The memory 803 includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or compact disc read-only memory (CD-ROM), and is used to store related instructions and data.

[0100] In this embodiment, memory 803 stores computer program 804, which includes program instructions. Processor 801 is configured to invoke the program instructions. The program includes instructions for performing the following steps:

[0101] If an image of a pet after vaccination is received, then the associated pet image and pet information are obtained.

[0102] Based on the pet image and associated pet image, obtain the pet's status characteristics; based on the pet information and the vaccine information, obtain the preset status characteristics of the adverse vaccine reaction event.

[0103] If the pet's status characteristics successfully match the preset status characteristics, then it is determined that the pet has experienced an adverse vaccine reaction event;

[0104] Send a notification message about the adverse vaccine reaction event to the object corresponding to the pet.

[0105] In one possible example, regarding the acquisition of the pet's status characteristics based on the pet's pet image and associated pet images, the instructions in the program are specifically used to perform the following operations:

[0106] Obtain the association value between the pet image and the associated pet image;

[0107] The first state data of the pet is obtained based on the pet image of the pet, and the second state data of the pet is obtained based on the pet's associated pet image;

[0108] The first state data and the second state data are fused based on the association value to obtain the state characteristics of the pet.

[0109] In one possible example, regarding the acquisition of the association value between the pet image and the associated pet image, the instructions in the program are specifically used to perform the following operations:

[0110] Obtain the pet image and associated pet image scene data and / or physiological parameters of the pet respectively;

[0111] Based on the scene data and / or physiological parameters, obtain the correlation value between the pet image and associated pet images.

[0112] In one possible example, after obtaining the pet's status characteristics based on the pet image and associated pet images, the instructions in the program are also used to perform the following operations:

[0113] The pet's condition characteristics are updated based on the physiological parameters.

[0114] In one possible example, before sending the notification message about the adverse vaccine reaction event to the object corresponding to the pet, the instructions in the program are also used to perform the following operations:

[0115] The risk level of the adverse vaccine reaction event is determined based on the pet's condition characteristics.

[0116] Based on the stated risk level, obtain precautions for adverse events related to the vaccine.

[0117] The system generates a notification message for the adverse reaction event of the vaccine based on the aforementioned precautions.

[0118] In one possible example, after determining the risk level of the adverse vaccine reaction event based on the pet's condition characteristics, the instructions in the program are also used to perform the following operations:

[0119] If the danger level is greater than a preset level, a call request is sent to the hospital corresponding to the pet, and the call request is used to instruct the hospital to provide medical resources.

[0120] In one possible example, before sending the call request to the hospital corresponding to the pet, the instructions in the program are also used to perform the following operations:

[0121] Obtain the pet's location, insurance information, and medical history;

[0122] Based on the pet's insurance information and historical medical records, the priority of each hospital among multiple hospitals corresponding to the pet's location is determined;

[0123] The appropriate hospital for the pet is determined based on the hospital's priority.

[0124] This application embodiment also provides a computer-readable storage medium storing a computer program executed by the aforementioned event notification device. The computer program includes program instructions, which, when executed by a processor, enable the execution of the aforementioned event notification device. Figure 3 The description of the event notification method in the corresponding embodiments will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be repeated. For technical details not disclosed in the computer-readable storage medium embodiments related to this application, please refer to the description of the method embodiments of this application. As an example, program instructions can be deployed and executed on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network. These multiple computing devices distributed across multiple locations and interconnected via a communication network can constitute a blockchain system.

[0125] Furthermore, it should be noted that this application also provides a computer program product or computer program, which may include computer instructions, which may be stored in a computer-readable storage medium. The processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor may execute the computer instructions, causing the computer device to perform the aforementioned actions. Figure 3 The description of the event notification method in the corresponding embodiments is already provided and will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be repeated. For technical details not disclosed in the computer program products or computer program embodiments related to this application, please refer to the description of the method embodiments of this application.

[0126] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0127] The steps in the method of this application embodiment can be adjusted, combined, or deleted according to actual needs.

[0128] The modules in the device of this application embodiment can be merged, divided, and deleted according to actual needs.

[0129] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, ROM, RAM, EPROM, or CD-ROM, etc.

[0130] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.

Claims

1. An event notification method, characterized in that, include: If an image of a pet after vaccination is received, then the associated pet image and pet information are obtained. Based on the pet image and associated pet image of the pet, obtain the status characteristics of the pet; based on the pet information and the vaccine information of the vaccinated pet, obtain the preset status characteristics of adverse vaccine reaction events. If the pet's status characteristics successfully match the preset status characteristics, then it is determined that the pet has experienced an adverse vaccine reaction event; Send a notification message about the adverse reaction to the vaccine to the object corresponding to the pet, where the object corresponding to the pet is the pet's owner or caretaker; The step of obtaining the pet's state features based on the pet image and associated pet images includes: Obtain the association value between the pet image and the associated pet image; The first state data of the pet is obtained based on the pet image of the pet, and the second state data of the pet is obtained based on the pet's associated pet image; The first state data and the second state data are fused based on the association value to obtain the state features of the pet. The step of obtaining the association value between the pet image and the associated pet image includes: Obtain the pet image and associated pet image scene data and / or physiological parameters of the pet respectively; Based on the scene data and / or physiological parameters, obtain the correlation value between the pet image and associated pet images.

2. The method as described in claim 1, characterized in that, After obtaining the pet's status features based on the pet image and associated pet images, the method further includes: The pet's condition characteristics are updated based on the physiological parameters.

3. The method as described in claim 1 or 2, characterized in that, Before sending the notification message about the adverse vaccine reaction event to the object corresponding to the pet, the method further includes: The risk level of the adverse vaccine reaction event is determined based on the pet's condition characteristics. Based on the stated risk level, obtain precautions for adverse events related to the vaccine. The system generates a notification message for the adverse reaction event of the vaccine based on the aforementioned precautions.

4. The method as described in claim 3, characterized in that, After obtaining the risk level of the adverse vaccine reaction event based on the pet's condition characteristics, the method further includes: If the danger level is greater than a preset level, a call request is sent to the hospital corresponding to the pet, and the call request is used to instruct the hospital to provide medical resources.

5. The method as described in claim 4, characterized in that, Before sending the call request to the hospital corresponding to the pet, the method further includes: Obtain the pet's location, insurance information, and medical history; Based on the pet's insurance information and historical medical records, the priority of each hospital among multiple hospitals corresponding to the pet's location is determined; The appropriate hospital for the pet is determined based on the hospital's priority.

6. An event notification device, characterized in that, Includes units for performing the method according to any one of claims 1 to 5.

7. A computer device, characterized in that, It includes a memory and a processor; the memory is connected to the processor, the memory is used to store a computer program, and the processor is used to invoke the computer program so that the computer device performs the method of any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted to be loaded and executed by a processor to cause a computer device having the processor to perform the method of any one of claims 1 to 5.

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