An AI intelligent family care method and device, computer equipment and storage medium

Abstract

The application discloses an AI intelligent family care method and device, computer equipment and a storage medium, the method comprises the following steps: collecting video data; storing and analyzing the video data; performing data analysis and arrangement according to the video data analysis result to obtain an abnormal conclusion; and prompting according to the abnormal conclusion. The AI intelligent family care method provided in the embodiment of the application can realize pre-prevention and timely processing by analyzing and processing the video data, identifying and pushing the prompt of specific events in milliseconds.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology, and in particular to an AI-powered smart home care method, device, computer equipment, and storage medium. Background Technology

[0002] In daily life, caring for vulnerable groups such as children, the elderly, and the sick is not only a reflection of family responsibility but also a crucial component of social civilization and the public health system. Existing home care equipment consists of traditional security cameras, fixed to the ceiling or corners, capturing audio and video through microphones and lenses. These are then provided via mobile apps for real-time preview, cloud playback, or motion detection alarms. However, traditional security cameras merely serve the roles of "recording images" and "collecting evidence afterward." Users must constantly monitor the screen and review recordings afterward, which is both time-consuming and prone to missing crucial intervention times. They cannot proactively identify anomalies, predict risks, or provide timely intervention. Even uploading data to the cloud for analysis and returning the results locally still affects timeliness, falling far short of the true care needs of "real-time monitoring and proactive prevention." Summary of the Invention

[0003] This invention provides an AI-powered smart home care method, device, computer equipment, and storage medium to address the technical problem that existing technologies cannot intelligently identify abnormal events and thus cannot meet the true care needs of real-time protection and proactive prevention.

[0004] This invention provides an AI-powered smart home care method, comprising: Collect video data; The video data is stored and analyzed; Based on the video data analysis results, data analysis and organization were performed to arrive at anomaly conclusions; A prompt will be given based on the aforementioned abnormal conclusion.

[0005] Preferably, the step of acquiring video data includes: the SOC module acquiring video data recorded by multiple cameras through a router or switch network.

[0006] Preferably, the step of storing and analyzing the video data includes: The SOC module stores the video data in the storage module; The video is analyzed by different modules based on the amount of information contained within it.

[0007] Preferably, the step of analyzing the video using different modules based on the amount of information in the video includes: When the SOC module detects no human figures in the video, then only the SOC module needs to analyze the video data. When the video data contains complex scenes, a large number of human figures, or requires analysis by a large AI model, the video data is sent to the edge data module for analysis.

[0008] Preferably, the step of analyzing and organizing the data based on the video data analysis results to obtain anomaly conclusions includes: The edge computing module performs data analysis and processing using a large AI model. If a specific event is identified, the abnormal conclusion is drawn. The edge computing module sends the abnormal conclusions to the SOC module.

[0009] Preferably, the specific event includes at least one of the following: someone falls, a child cries, or a room catches fire.

[0010] Preferably, the step of providing a prompt based on the abnormal conclusion includes: The SOC module provides the abnormal conclusion notification via the network; The notifications may include reporting to the app, receiving an app push notification, or being contacted by phone.

[0011] This invention also provides an AI-powered smart home monitoring device, comprising: a SOC module, an edge computing module, a storage module, multiple cameras, and a switch or router, wherein: The SOC module is used to collect video data; the multiple cameras record video, and the SOC module collects the video data recorded by the multiple cameras through the switch or router; The SOC module is also used to store and analyze the video data; when the video data has a complex scene, a large number of human figures, or requires analysis by a large AI model, the SOC module processes the content in the video into image content and transmits it to the edge computing module for analysis. The edge computing module is used to analyze and organize the data based on the video data analysis results to obtain anomaly conclusions; The SOC module is also used to provide prompts based on the abnormal conclusions.

[0012] This invention also provides a computer device, including 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 above-described AI smart home care method.

[0013] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned AI-powered smart home care method.

[0014] The present invention provides an AI-powered smart home care method, device, computer equipment, and storage medium that analyzes and processes video data to identify and push notifications for specific events at the millisecond level, enabling proactive prevention and timely handling. Attached Figure Description

[0015] 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.

[0016] Figure 1 This is a schematic diagram of an application environment for an AI-powered smart home care method according to an embodiment of the present invention; Figure 2 This is a flowchart of an AI-powered smart home care method according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an AI smart home care device according to an embodiment of the present invention; Figure 4 This is a schematic diagram of a computer device according to an embodiment of the present invention. Detailed Implementation

[0017] 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.

[0018] The AI-powered smart home care method provided in this invention can be applied to, for example... Figure 1 The application environment is shown. Specifically, this AI smart home care method is applied in an AI smart home care device, which includes, as shown in the example... Figure 1 The diagram illustrates a client and server. The client and server communicate over a network to achieve millisecond-level identification and push notifications for specific events, enabling proactive prevention and timely handling. The client, also known as the user terminal, refers to the program that provides local services to the client, 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 implemented using a standalone server or a server cluster consisting of multiple servers.

[0019] In one embodiment, such as Figure 2 As shown, an AI-powered smart home care method is provided, which is then applied to... Figure 1 Taking the server in the example, the following steps are included: S1: Acquire video data. For example, multiple cameras record video, and the SOC module acquires the video data recorded by the multiple cameras through a router or switch network.

[0020] S2: Store and analyze the video data. For example, the SOC module stores the video data in a storage module, such as a local hard drive, i.e., a local private cloud. Preferably, different modules can analyze the video based on the amount of information in it. For example, assuming the SOC module has a computing power of 6 TOPS and the edge computing module has a computing power of 30 TOPS, when analyzing images in the video, since the SOC module's computing power is much smaller than the edge computing module's, the SOC module's computing power is prioritized. Specifically, when the SOC module detects no human figures in the video, only the 6 TOPS computing power of the SOC module is needed, and the 30 TOPS computing power of the edge computing module is not required, thus saving power and energy. When the video data contains complex scenes, a large number of human figures, or requires analysis using a large AI model, the SOC module processes the video content into image content and transmits the data to the edge computing module for analysis via a gigabit Ethernet port or PCIe interface.

[0021] S3: Based on the video data analysis results, perform data analysis and organization to obtain an anomaly conclusion. Preferably, the edge computing module performs data analysis and organization using an AI large model. If a specific event is identified, the anomaly conclusion is drawn. The edge computing module sends the anomaly conclusion to the SOC module. The specific event includes at least one of the following: someone falls, a child cries, or a room catches fire, etc.

[0022] S4: Provide a notification based on the aforementioned anomaly conclusion. Specifically, the SOC module provides the anomaly conclusion notification via the network, including reporting to the APP, sending an APP push notification, or making a phone call, etc.

[0023] 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.

[0024] This invention provides an AI-powered smart home care method that analyzes and processes video data to identify and push notifications for specific events at the millisecond level, enabling proactive prevention and timely handling.

[0025] In one embodiment, an AI smart home care device 100 is provided, which corresponds one-to-one with the AI ​​smart home care method described in the above embodiments. As shown in Figure X, the AI ​​smart home care device 100 includes a SOC module 101, an edge computing module 102, a storage module 103, a multi-camera 201, and a switch or router 201. Detailed descriptions of each functional module are as follows: The SOC module 101 is used to acquire video data. For example, the multi-camera 201 records video, and the SOC module acquires the video data recorded by the multi-camera 201 through the switch or router 202. For example, the SOC module 101 can be a heterogeneous SOC, integrating a CPU, GPU, and CPU within the same package and sharing memory.

[0026] The SOC module 101 is also used for storing and analyzing the video data. Specifically, the SOC module 101 stores the video data in the storage module 103, such as a local hard drive, i.e., a local private cloud. The storage module 103 may include an M.2 HDD with eMMC and PCIe interfaces, and a hard drive with a SATA interface, and can be configured for NVR continuous write storage and NAS file sharing. Preferably, when no human figures are found in the video, the SOC module 101 is used for analysis. This saves power consumption and energy. When the video data has a complex scene, a large number of human figures, or requires analysis using a large AI model, the SOC module 101 processes the content in the video into image content and transmits it to the edge computing module 102 for analysis. The edge computing module 102 can communicate with the SOC module 101 through a gigabit PHY to perform local large model inference and model self-training, achieving zero manual data annotation.

[0027] The edge computing module 102 is used to analyze and organize the video data based on the analysis results to obtain anomaly conclusions. Preferably, the edge computing module 102 performs data analysis and organization using an AI large model. If a specific event is identified, the anomaly conclusion is sent to the SOC module. The specific event includes at least one of the following: someone falls, a child cries, or a room catches fire. The edge computing module 102 also includes a model self-training engine, used to generate pseudo-labels on unlabeled video data and iteratively update the local large model to achieve pre-event risk prediction.

[0028] The SOC module 101 is also used to provide a notification based on the anomaly conclusion. Specifically, the SOC module 101 provides the notification via the network, and the notification may include reporting to the APP, sending an APP push notification, or making a telephone call, etc.

[0029] Specific limitations regarding AI-powered smart home monitoring devices can be found in the above description of AI-powered smart home monitoring methods, and will not be repeated here. Each module in the aforementioned AI-powered smart home monitoring 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, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0030] This invention provides an AI-powered smart home monitoring device that analyzes and processes video data to identify and push notifications for specific events at the millisecond level, enabling proactive prevention and timely handling.

[0031] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4 As 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 stored in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements an AI-powered smart home care method.

[0032] 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 AI ​​smart home care method described in the above embodiment, for example... Figure 2 S1-S4, as shown, will not be described again here to avoid repetition. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in this embodiment of the AI ​​smart home care device, for example... Figure 3 The functions of the SOC module 101 shown are not described again here to avoid repetition.

[0033] 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 AI ​​smart home care method described in the above embodiment, for example... Figure 2 S1-S4, as shown, will not be repeated here to avoid repetition. Alternatively, when the computer program is executed by the processor, it implements the functions of each module / unit in this embodiment of the AI ​​smart home care device, for example... Figure 3The functions of the SOC module 101 shown are not described again here to avoid redundancy. The computer-readable storage medium can be non-volatile or volatile.

[0034] 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.

[0035] 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.

[0036] 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 AI-powered smart home care method, characterized in that, include: Collect video data; The video data is stored and analyzed; Based on the video data analysis results, data analysis and organization were performed to arrive at anomaly conclusions; A prompt will be given based on the aforementioned abnormal conclusion.

2. The AI-powered smart home care method as described in claim 1, characterized in that, The steps for acquiring video data include: The SOC module collects video data recorded by multiple cameras through a router or switch network.

3. The AI-powered smart home care method as described in claim 1, characterized in that, The steps of storing and analyzing the video data include: The SOC module stores the video data in the storage module; The video is analyzed by different modules based on the amount of information contained within it.

4. The AI-powered smart home care method as described in claim 3, characterized in that, The steps of analyzing the video using different modules based on the amount of information in it include: When the SOC module detects no human figures in the video, then only the SOC module needs to analyze the video data. When the video data contains complex scenes, a large number of human figures, or requires analysis by a large AI model, the video data is sent to the edge data module for analysis.

5. The AI-powered smart home care method as described in claim 4, characterized in that, The step of analyzing and organizing the video data based on the analysis results to obtain anomaly conclusions includes: The edge computing module performs data analysis and processing using a large AI model. If a specific event is identified, the abnormal conclusion is drawn. The edge computing module sends the abnormal conclusions to the SOC module.

6. The AI-powered smart home care method as described in claim 5, characterized in that, The specific event includes at least one of the following: someone falls, a child cries, or a room catches fire.

7. The AI-powered smart home care method as described in claims 5-6, characterized in that, The step of providing a prompt based on the abnormal conclusion includes: The SOC module provides the abnormal conclusion notification via the network; The notifications may include reporting to the app, receiving an app push notification, or being contacted by phone.

8. An AI-powered smart home care device, characterized in that, include: This includes SOC modules, edge computing modules, storage modules, multi-camera systems, switches or routers, among which: The SOC module is used to collect video data; the multiple cameras record video, and the SOC module collects the video data recorded by the multiple cameras through the switch or router; The SOC module is also used to store and analyze the video data; when the video data has a complex scene, a large number of human figures, or requires analysis by a large AI model, the SOC module processes the content in the video into image content and transmits it to the edge computing module for analysis. The edge computing module is used to analyze and organize the data based on the video data analysis results to obtain anomaly conclusions; The SOC module is also used to provide prompts based on the abnormal conclusions.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the AI ​​smart home care 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 the processor, it implements the AI ​​smart home care method as described in any one of claims 1 to 7.

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