Life record and health assistance AI diary generation method and system for old people, electronic equipment and readable storage medium

Abstract

The invention belongs to the technical field of artificial intelligence and smart old-age care, and particularly discloses a life record and health assistance AI diary generation method and system for old people, electronic equipment and a readable storage medium, and the method comprises the following steps: S1, extracting EXIF metadata of a digital image, and generating a standardized data structure; s2, identifying and extracting key information of the digital image, and fusing and identifying an object identification result and character information in the digital image; s3, constructing a time stamp based on EXIF metadata and a space-time matrix of a fusion recognition result, and forming a space-time matrix data structure; s4, generating a Prompt based on the space-time matrix data structure, user habits and constraint conditions; s5, generating a Prompt-based diary content, wherein the Prompt-based diary content is used for evaluating daily activity levels, dietary habits and social interaction conditions of the old; and S6, based on the digital image and the diary content, forming a diary for the user to download and view or share to family members, friends and medical staff.

Description

Technical Field

[0001] This invention belongs to the fields of artificial intelligence and smart elderly care technology, specifically relating to a method, system, electronic device, and readable storage medium for generating AI diaries for elderly people's life records and health assistance. Background Technology

[0002] With the rapid development of artificial intelligence technology, especially breakthroughs in computer vision, natural language processing, and speech recognition, AI has been widely applied in various scenarios such as healthcare, smart assistants, and daily life tracking. In the context of an aging society, using AI technology to improve the quality of life for the elderly has become a research hotspot. For example, image recognition-based smart photo album systems, voice input-based calendar recording tools, and health monitoring platforms combined with wearable devices have gradually entered home and community application scenarios. These technologies not only improve the efficiency of information acquisition but also provide new solutions for cognitive assistance and health management for the elderly.

[0003] However, existing technologies still have many shortcomings, making it difficult to meet the personalized needs of the elderly in terms of life recording and health assistance. First, most log applications still rely on users manually inputting text, which poses a high barrier to entry for the elderly with declining memory and limited operational abilities, making it difficult to form a continuous recording habit. Second, although some methods have automated image recognition and text generation, the generated content lacks timeline integration and emotional expression, failing to form a coherent and reviewable life record. Third, existing methods generally do not combine the generated content with health status analysis, lacking systematic tracking and data-driven management of key indicators such as the elderly's daily behavior patterns, emotional changes, and social interactions, thus limiting their practical application value in health management. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a method, system, electronic device, and readable storage medium for generating AI diaries for elderly people's daily life records and health assistance.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution: The first aspect of this invention provides a method for generating an AI-powered diary for elderly people's daily life and health, comprising the following steps: S1. Preprocess the acquired digital image, extract the EXIF ​​metadata of the digital image, and generate a standardized data structure.

[0006] Users can upload multiple digital images of daily life through the system interface. These digital images are photos and support formats such as JPEG and PNG. The system preprocesses these photos, including but not limited to scaling and format standardization, and automatically extracts EXIF ​​metadata (including shooting time and date, image resolution and size, GPS coordinates, etc.) to ensure smooth subsequent processing.

[0007] S2. Identify and extract key information from digital images, and fuse the object recognition results with the text information in the digital images for recognition.

[0008] Digital image recognition and key information extraction: Analyze each digital image, extract key elements such as objects, scenes, and text, and convert them into a list of keywords in text form.

[0009] S3. Construct a spatiotemporal matrix based on EXIF ​​metadata timestamps and fused recognition results to form a spatiotemporal matrix data structure. This structure helps reconstruct the user's daily or weekly life trajectory, facilitating subsequent storytelling. Based on the timestamp information of each digital image, all digital image data are automatically arranged in chronological order to construct a spatiotemporal matrix, helping to reconstruct the elderly person's daily or weekly life trajectory, thus facilitating subsequent storytelling.

[0010] S4. Based on the spatiotemporal matrix data structure, user habits, and constraints, generate the prompt word "Prompt".

[0011] Construct a prompt word: Combining the spatiotemporal matrix data structure formed in step S3, the user's selected language style (such as a warm and nostalgic style, a concise and factual style, or a humorous and lighthearted style), role setting, output format, and other information, construct a detailed prompt word.

[0012] S5. Generate diary entries based on the prompt word "Prompt" to assess the elderly person's daily activity level, eating habits, and social interactions.

[0013] Diary content generation: Generate a natural and fluent diary entry that conforms to specific style requirements based on the prompt word "Prompt"; by analyzing the keywords in the diary content, assess the elderly's daily activity level, eating habits, and social interaction.

[0014] S6. Create a diary based on digital images and diary content for users to download, view, or share with family, friends, and medical staff.

[0015] Diary Display and Export: The generated diary content is combined with the original images to create a structured PDF document, forming a diary that is displayed to users in a mixed text and image format for download and viewing or sharing with family, friends, and medical staff.

[0016] According to the above-mentioned method for generating AI diaries for daily life records and health assistance for the elderly, preferably, in step S1, the preprocessing of digital images includes: S11. Digital Image Format Check and Conversion: Convert digital image format to JPG format and color space to sRGB.

[0017] S12. Resolution standardization of digital images: The resolution of digital images is scaled to 1920×1080 using a bicubic interpolation algorithm (aspect ratio preservation algorithm).

[0018] S13. Digital Image Parsing: The ExifTool v12.6 kernel is used to parse the EXIF ​​metadata of digital images. The EXIF ​​metadata includes the digital image's timestamp (DateTimeOriginal), image resolution and size, spatial information (GPSLatitude), etc., to ensure the smooth progress of subsequent processing.

[0019] S14. Generate standardized data structures.

[0020] According to the above-mentioned method for generating life records and health-assisted AI diaries for the elderly, preferably, in step S2, the digital image recognition and extraction steps include: performing intelligent analysis and semantic understanding on each digital image: extracting key elements such as objects, scenes, and text, and converting them into a list of keywords in text form; and recognizing and extracting structured information from the multi-level content of the digital image.

[0021] S21. Perform overall scene understanding and object recognition on digital images, automatically identify the main object labels and scene classification information contained in the digital images, generate object recognition results, and output a set of representative image keywords for subsequent prompt word construction and diary generation.

[0022] S22. Perform optical character recognition on digital images to further mine textual information in digital images, such as road signs, logos, handwritten notes, product labels, and other textual content; accurately detect and extract printed and some handwritten text content in digital images, and return the content recognition results in the form of structured data, including information such as text content and recognition confidence.

[0023] S23. The object recognition result and the content recognition result generated by the recognition are fused together to obtain the fused recognition result.

[0024] According to the above-mentioned method for generating life records and health-assisted AI diaries for the elderly, preferably, in step S3, the step of constructing the spatiotemporal matrix is ​​as follows: a unified timeline is generated based on the timestamp (DateTimeOriginal) in the EXIF ​​metadata; based on the obtained fusion recognition results, feature vectors are constructed for each image in the fusion recognition results to form a unified keyword list and semantic description text, and finally a spatiotemporal matrix data structure in JSON format is formed to realize the transformation from discrete images to continuous event streams, providing a structured spatiotemporal framework for subsequent diary generation and health analysis.

[0025] According to the above-mentioned method for generating AI diaries for life records and health assistance for the elderly, preferably, in step S4, the user habits include information such as the user's selected language style, role setting, and output format constraints; the user's selected language style includes warmth, simplicity, and humor; the output format constraints include first person, paragraph length, and word style; the role setting is an elderly life memory guardian, used to convert life data into diary form; and the spatiotemporal matrix data structure is the core element.

[0026] The generation of the prompt word involves transforming the spatiotemporal matrix data structure into an input instruction that the natural language model can understand. This instruction guides the large language model to generate personalized diary content that aligns with the cognitive habits, emotional needs, and health assistance goals of the elderly. The spatiotemporal matrix data structure and user habits are then assembled into a clearly structured, semantically rich, and stylistically controllable prompt word text, which serves as the input for the next stage of the diary generation module.

[0027] According to the above-mentioned method for generating life records and health assistance AI diaries for the elderly, preferably, in step S5, the diary content generation step is as follows: based on the prompt word Prompt, a large language model is called to generate a real, natural and fluent diary content that meets specific style requirements.

[0028] According to the above-mentioned method for generating AI diaries for life records and health assistance for the elderly, preferably, in step S6, the diary generation steps are as follows: the generated diary content, original digital images, and other additional information are packaged into a structured PDF document, and images and text are automatically associated based on a spatiotemporal matrix. A mixed text and image layout is adopted, with corresponding original digital images accompanying each diary entry to enhance the reading experience of the diary content; the diary is displayed to the user in a mixed text and image layout for the user to download and view or share with family, friends, and medical staff; the document includes a cover page, a table of contents, and diary content.

[0029] The second aspect of this invention provides an AI-powered diary generation system for elderly people, encompassing an image preprocessing module, an image recognition module, a timeline organization module, and a diary generation module. The image preprocessing module receives and preprocesses digital images uploaded by users. The image recognition module invokes a deep learning image recognition model to identify key objects, scenes, people, and text within the digital images. The timeline organization module constructs a spatiotemporal matrix from the image data extracted by the deep learning image recognition model based on the shooting time information. The prompt word generation module combines obtained image description keywords, the integrated timeline, and specific style parameters to construct prompt words for generating diary content. The diary generation module uses the generated prompt words as input, invokes a large language model to generate natural language descriptions, combines the digital images and additional information, and forms a diary based on the spatiotemporal matrix, thus executing the AI-powered diary generation method for elderly people described in the first aspect of this invention.

[0030] A third aspect of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any step of the method for generating an AI diary for life recording and health assistance for the elderly as described in the first aspect.

[0031] The fourth aspect of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a computer processor, implements any step of the method for generating a life record and health assistance AI diary for the elderly as described in the first aspect.

[0032] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention uses a deep learning image recognition model to automatically identify key content in user-uploaded digital images, combines timeline information and personalized style parameters to construct prompt words, utilizes the reasoning ability of a large language model to generate structured text diaries, and further evaluates the elderly’s daily activities, eating habits and social interactions through data analysis based on the diary content. This helps the elderly better record and review their lives, improve their quality of life, and at the same time facilitates doctors or caregivers to understand the elderly’s condition, realizing the visualization and intelligent management of health data.

[0033] 2. This invention is applicable to scenarios that help the elderly record life events, aid memory, and manage health. It can automatically integrate daily life image information of the elderly and combine it with timeline and personalized style parameters to generate an AI diary with readability, emotionality, and structure. This method supports multimodal information fusion and automatic generation of picture and text diaries, which can effectively improve the elderly's memory aid ability and quality of life, while providing scientific decision-making basis for doctors and nurses.

[0034] 3. This invention has a high degree of automation and a low barrier to entry. It does not require the elderly to manually input text; they only need to upload photos to generate structured diary content, which can help the elderly better record and review their lives. This invention also has health assistance functions. Through semantic analysis of the diary content, it can help doctors or caregivers judge the elderly’s psychological, cognitive, and lifestyle health status. All the content generated by this invention can be exported as standard documents or database files, which are convenient for long-term storage and statistical analysis. Attached Figure Description

[0035] Figure 1 This is a flowchart illustrating Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the digital image preprocessing process in step S1 of Embodiment 1 of the present invention; Figure 3 This is a flowchart illustrating step S2 in Embodiment 1 of the present invention; Figure 4 This is a flowchart illustrating step S4 in Embodiment 1 of the present invention; Figure 5 This is a flowchart illustrating step S6 in Embodiment 1 of the present invention; Figure 6 This is a schematic diagram of the architecture of Embodiment 2 of the present invention; Detailed Implementation

[0036] The present invention will be further described in detail below through specific embodiments, but this does not limit the scope of the present invention.

[0037] Example 1 A method for generating AI-powered diaries for elderly people to record their daily lives and assist with health, the process of which is as follows: Figure 1 As shown, it includes the following steps; S1. Users upload multiple JPEG and PNG digital images containing everyday life data, with a maximum of 30 images uploaded at a time. After the upload is complete, the following automated preprocessing process is executed to extract the EXIF ​​metadata of the digital images and generate a standardized data structure.

[0038] like Figure 2 As shown, digital image preprocessing includes: S11. Check and convert the format of the original input digital image: convert the digital image format to JPG format and the color space to sRGB.

[0039] S12. Resolution standardization of digital images: The resolution of digital images is scaled to 1920×1080 using a bicubic interpolation algorithm (aspect ratio preservation algorithm) to achieve resolution standardization.

[0040] S13. Digital Image Parsing: The ExifTool v12.6 kernel is used to parse the EXIF ​​metadata of digital images. The EXIF ​​metadata includes the digital image's timestamp (DateTimeOriginal), image resolution and size, spatial information (GPSLatitude), etc., to ensure the smooth progress of subsequent processing.

[0041] S14. Generate a standardized data structure for output.

[0042] S2. Identify and extract key information from digital images, and fuse the object recognition results with the text information in the digital images for recognition.

[0043] The steps for digital image recognition and extraction include: For preprocessed digital images and other relevant information, using image recognition APIs, such as Tencent Cloud Image Recognition Service, to perform intelligent analysis and semantic understanding on each digital image: The Tencent Cloud Image Recognition API is called to analyze each image, extracting key elements such as objects, scenes, and text, and converting them into a keyword list in text form; the Tencent Cloud Image Recognition API, through the Tencent Cloud RecognizeImage v3.2 interface and the Tencent Cloud GeneralBasicOCR interface, achieves multi-level recognition and structured information extraction of digital image content, such as... Figure 3 As shown.

[0044] S21. Utilize the Tencent Cloud RecognizeImage v3.2 interface to perform overall scene understanding and object recognition on digital images. Automatically identify the main object labels and scene classification information contained in the digital images, generate object recognition results, and output a set of representative image keywords for subsequent prompt word construction and diary generation.

[0045] S22. Call the Tencent Cloud GeneralBasicOCR (Optical Character Recognition, OCR) interface to perform optical character recognition on digital images to further extract text information from digital images, such as road signs, logos, handwritten notes, product labels, and other text content. Tencent Cloud GeneralBasicOCR can accurately detect and extract printed and some handwritten text content in digital images and return the content recognition results in the form of structured data. The content recognition results include information such as text content and recognition confidence.

[0046] S23. The object recognition results generated by Tencent Cloud Image Recognition API and the content recognition results generated by Tencent Cloud OCR are fused together to obtain the fused recognition result.

[0047] S3. Construct a spatiotemporal matrix based on the timestamps of EXIF ​​metadata and the fusion recognition results to form a spatiotemporal matrix data structure, which helps to reconstruct the user's life trajectory for a day or a week, so as to facilitate subsequent story narration.

[0048] The steps for constructing the spatiotemporal matrix are as follows: a unified timeline is generated using the timestamp (DateTimeOriginal) in the EXIF ​​metadata as the base timestamp; based on the obtained fusion recognition results, feature vectors are constructed for each image in the fusion recognition results to form a unified list of keywords and semantic description text, and finally a spatiotemporal matrix data structure in JSON format is formed to realize the transformation from discrete images to continuous event streams, providing a structured spatiotemporal framework for subsequent diary generation and health analysis.

[0049] S4. Based on the spatiotemporal matrix data structure, user habits, and constraints, generate the prompt word "Prompt".

[0050] After completing image recognition, OCR extraction, and spatiotemporal information integration, the next step is to generate prompts. The core task of generating prompts is to transform structured data into input instructions that the natural language model can understand, so as to guide the large language model to generate personalized diary content that conforms to the cognitive habits, emotional needs, and health assistance goals of the elderly.

[0051] like Figure 4 As shown, the process for generating the prompt is as follows: the role is set as a guardian of elderly life memories, skilled at converting life data into diary format; the core material is a spatiotemporal matrix data structure; language style parameters are set (such as warmth, conciseness, humor, etc.); output format constraints are set (such as first person, paragraph length, word style, etc.); the prompt is assembled into a clearly structured, semantically rich, and style-controllable prompt text, which serves as the input for the next stage of the diary generation module.

[0052] S5. Generate diary entries based on the prompt word "Prompt" to assess the elderly person's daily activity level, eating habits, and social interactions.

[0053] After the prompt word is generated, the ChatGLM-4 large language model developed by Zhipu AI is called to generate a realistic, natural and fluent diary entry that meets specific style requirements based on the prompt word. Medical staff can use the diary entry to assess the elderly person's daily activity level, eating habits and social interaction.

[0054] S6. Create a diary based on digital images and diary content for users to download, view, or share with family, friends, and medical staff.

[0055] The steps to generate a diary are as follows: Figure 5 As shown, the generated diary content, original digital images, and other supplementary information are packaged into a structured PDF document. The document includes a cover page, a table of contents, and the diary content. Then, based on a spatiotemporal matrix, images and text are automatically associated, and a mixed text and image layout is adopted. Each diary entry is accompanied by a corresponding original digital image to enhance the reading experience. The diary is presented to the user in a mixed text and image layout for the user to download and view or share with family, friends, and medical staff.

[0056] Example 2 An AI-powered diary generation system for elderly people, which includes life recording and health assistance, such as Figure 6 As shown, the system includes an image preprocessing module, an image recognition module, a timeline organization module, and a diary generation module. The image preprocessing module receives multiple digital images uploaded by the user and preprocesses them. The image recognition module calls a deep learning image recognition model to identify key objects, scenes, people, text, and other information in the digital images. The timeline organization module constructs a spatiotemporal matrix from the image data extracted by the deep learning image recognition model based on the shooting time information. The prompt word generation module combines the obtained image description keywords, the integrated timeline, and specific style parameters to construct prompt words for generating diary content. The diary generation module uses the generated prompt words as input, calls the ChatGLM-4 language model to generate natural language descriptions, combines the digital images and additional information, and forms a diary based on the spatiotemporal matrix, thus executing the AI ​​diary generation method for life recording and health assistance for the elderly as described in the first aspect of this invention.

[0057] Example 3 An electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any step of the method for generating an AI diary for life recording and health assistance for the elderly as described in Embodiment 1.

[0058] Furthermore, the method for generating an AI-powered diary for elderly individuals, as described in Embodiment 1, can be implemented as a computer software program. For example, this embodiment includes a computer program product comprising a computer program hosted on a computer-readable medium, the computer program containing program code for performing the method. In such an embodiment, the computer program can be downloaded and installed from a network, and / or installed from a removable medium. When the computer program is executed by a processor, it performs the functions defined in the method of this application.

[0059] Example 4 A computer-readable storage medium storing a computer program, which, when executed by a processor, implements any step of the method for generating an AI-powered diary for life recording and health assistance for the elderly as described in Embodiment 1.

[0060] The computer-readable medium described in this application may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0061] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Python and C++, as well as conventional procedural programming languages ​​or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0062] In this embodiment, the computer-readable storage medium can be accelerated using hardware such as a GPU. The parallel computing advantage of the GPU is used to accelerate any step in the method for generating an AI diary for life recording and health assistance for the elderly, as described in Embodiment 1.

[0063] In summary, this invention effectively overcomes the shortcomings of the prior art and has high industrial applicability. The above embodiments are intended to illustrate the substantive content of this invention, but are not intended to limit the scope of protection of this invention. Those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this invention without departing from the essence and scope of protection of this invention.

[0064] The above embodiments are specific implementations of the present invention, but the implementation of the present invention is not limited to the above embodiments. Any other combination, change, modification, substitution, or simplification that does not exceed the design concept of the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for generating an AI-powered diary for daily life recording and health assistance for the elderly, characterized in that, Includes the following steps: S1. Preprocess the acquired digital image, extract the EXIF ​​metadata of the digital image, and generate a standardized data structure; S2. Identify and extract key information from digital images, and fuse the object recognition results with the text information in the digital images for recognition. S3. Construct a spatiotemporal matrix based on the timestamps of EXIF ​​metadata and the fusion recognition results to form a spatiotemporal matrix data structure; S4. Based on the spatiotemporal matrix data structure, user habits, and constraints, generate the prompt word "Prompt". S5. Generate diary entries based on the prompt word Prompt to assess the elderly person's daily activity level, eating habits, and social interactions. S6. Create a diary based on digital images and diary content for users to download, view, or share with family, friends, and medical staff.

2. The method for generating AI diaries for daily life records and health assistance for the elderly according to claim 1, characterized in that, In step S1, the preprocessing of the digital image includes: S11. Digital Image Format Check and Conversion: Convert digital image format to JPG format and color space to sRGB; S12. Resolution standardization of digital images: The resolution of digital images is scaled to 1920×1080 using a bicubic interpolation algorithm. S13. Digital Image Parsing: The ExifTool v12.6 kernel is used to parse the EXIF ​​metadata of digital images. The EXIF ​​metadata includes the timestamp of the digital image, image resolution and size, and spatial information to ensure the smooth progress of subsequent processing. S14. Generate standardized data structures.

3. The method for generating AI diaries for daily life records and health assistance for the elderly according to claim 1, characterized in that, In step S2, the digital image recognition and extraction steps include: performing intelligent analysis and semantic understanding on each digital image: extracting key elements and converting them into a list of keywords in text form; and recognizing and extracting structured information from the multi-level content of the digital image.

4. The method for generating AI diaries for daily life records and health assistance for the elderly according to claim 3, characterized in that, The digital image recognition and extraction steps include: S21. Perform overall scene understanding and object recognition on digital images, automatically identify the main object labels and scene classification information contained in the digital images, generate object recognition results, and output a set of representative image keywords for subsequent prompt word construction and diary generation. S22. Perform optical character recognition on digital images to further mine text information in digital images; accurately detect and extract printed and some handwritten text content in digital images, and return the content recognition results in the form of structured data, including text content and recognition confidence information; S23. The object recognition result and the content recognition result generated by the recognition are fused together to obtain the fused recognition result.

5. The method for generating AI diaries for daily life records and health assistance for the elderly according to claim 1, characterized in that, In step S3, the steps for constructing the spatiotemporal matrix are as follows: a unified timeline is generated based on the timestamps in the EXIF ​​metadata; based on the obtained fusion recognition results, feature vectors are constructed for each image in the fusion recognition results to form a unified list of keywords and semantic description text, and finally a spatiotemporal matrix data structure in JSON format is formed to realize the transformation from discrete images to continuous event streams, providing a structured spatiotemporal framework for subsequent diary generation and health analysis.

6. The method for generating AI diaries for daily life records and health assistance for the elderly according to claim 1, characterized in that, In step S4, the generation of the prompt word is to transform the spatiotemporal matrix data structure into an input instruction that the natural language model can understand, which is used to guide the large language model to generate personalized diary content that conforms to the cognitive habits, emotional needs and health assistance goals of the elderly. The spatiotemporal matrix data structure and user habits are assembled into a clear, semantically rich, and style-controllable prompt text, which serves as the input for the next stage of the diary generation module.

7. The method for generating AI diaries for daily life records and health assistance for the elderly according to claim 1, characterized in that, In step S6, the diary generation process is as follows: the generated diary content, original digital images, and other supplementary information are packaged into a structured PDF document. Based on the spatiotemporal matrix, images and text are automatically associated, and a mixed text and image layout is adopted. Each diary entry is accompanied by a corresponding original digital image to enhance the reading experience. The diary is displayed to the user in a mixed text and image layout for the user to download and view or share with family, friends, and medical staff. The document includes a cover page, a table of contents, and the diary content.

8. A system for generating AI-powered diaries for elderly people, characterized in that: It includes an image preprocessing module, an image recognition module, a timeline organization module, and a diary generation module; The image preprocessing module is used to receive digital images uploaded by users and preprocess the digital images; The image recognition module is used to call a deep learning image recognition model to identify key objects, scenes, people, and text information in digital images; The timeline organization module is used to construct a spatiotemporal matrix from the image data extracted by the deep learning image recognition model based on the shooting time information; The prompt word generation module is used to combine the obtained image description keywords, the integrated timeline, and specific style parameters to construct prompt words for generating diary content; The diary generation module is used to take the generated prompt words as input, call the large language model to generate natural language descriptions, combine digital images and additional information, and form a diary based on the spatiotemporal matrix, thereby executing the AI ​​diary generation method for life record and health assistance for the elderly as described in any one of claims 1-7.

9. An electronic device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements any step in the method for generating AI diaries for life records and health assistance for the elderly as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a computer processor, implements any step in the method for generating an AI diary for life records and health assistance for the elderly as described in any one of claims 1-7.

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