Visual assistance system based on cloud analysis

Abstract

The utility model provides a visual auxiliary system based on cloud analysis, which relates to the technical field of auxiliary equipment and comprises a hardware mechanism and a control system, the hardware mechanism comprises a head-mounted eyeshade, a sensor combination, a wireless communication module and feedback hardware, and the control system comprises a cloud analysis server and an application integration and interface module. The sensor combination, the wireless communication module and the feedback hardware are arranged in the head-mounted eyeshade; according to the utility model, wearing is facilitated in the form of the head-mounted eyeshade, visual and spatial information of the surrounding environment of a user is collected in real time through the sensor combination, the information is transmitted to the cloud analysis server for analysis through the wireless communication module, the received information is processed by an artificial intelligence algorithm, and the information is displayed according to the analysis result. The feedback instruction is sent to the head-mounted eyeshade so as to provide multi-mode sensory feedback for the user, help the user to recognize obstacles in front and assist the user in recognizing environment information or performing daily activities, and the head-mounted eyeshade is more convenient to use and sufficient in information amount.

Description

Technical Field

[0001] The utility model relates to the technical field of auxiliary equipment, and in particular to a visual assistance system based on cloud analysis. Background Art

[0002] Visually impaired people are those who are blind in one or both eyes due to diseases of the optic nerve or eyes or accidental injuries. They are divided into congenitally blind people and acquired blind people. Visually impaired people are mainly divided into two categories: total blindness and partial blindness. Total blindness means that the eyeball is atrophied or calcified and loses its response to light. The other is amblyopia, which is less than 60% of normal vision. The activities of blind people will be restricted due to visual impairment.

[0003] With the development of science and technology, providing assistive technology for low vision and blind users has become an important research direction. Traditional assistive devices mostly rely on simple sound or tactile feedback, such as guide dogs, white canes, etc. Although these methods are effective, they are limited in information volume and interactivity. Therefore, the utility model proposes a visual assistance system based on cloud analysis to solve the problems existing in the prior art. Utility Model Content

[0004] In response to the above problems, the present invention proposes a visual assistance system based on cloud analysis. The visual assistance system based on cloud analysis collects environmental information through a head-mounted mask, and after cloud-based artificial intelligence analysis, provides voice or vibration feedback to assist users in daily activities.

[0005] To achieve the purpose of the utility model, the utility model is implemented through the following technical solutions: a visual assistance system based on cloud analysis, including a hardware mechanism and a control system, the hardware mechanism includes a head-mounted eye mask, a sensor combination, a wireless communication module and feedback hardware, and the control system includes a cloud analysis server and an application integration and interface module;

[0006] The sensor combination, wireless communication module and feedback hardware are all built into the head-mounted eye mask, and the sensor combination is used to collect visual and spatial information of the user's surrounding environment in real time. The wireless communication module is connected to a cloud analysis server to transmit the information collected by the sensor combination to the cloud analysis server. The cloud analysis server processes and analyzes the received information and sends feedback instructions to the head-mounted eye mask through the wireless communication module based on the analysis results. The feedback hardware provides multimodal sensory feedback to the user based on the received feedback instructions to assist the user in identifying environmental information or performing daily activities.

[0007] A further improvement is that the head-mounted eye mask is made of skin-friendly material and has an adjustable headband.

[0008] A further improvement lies in that: the sensor combination includes an infrared sensor, an ultrasonic sensor, an optical sensor, and a camera, and the sensor combination is used to comprehensively sense the user's surrounding environment, collect specific types of data, including distance, temperature, light intensity, and images, and combine them into an environmental information packet.

[0009] A further improvement lies in that: the wireless communication module adopts Wi-Fi or 5G, a Bluetooth module, and is used for real-time wireless data transmission between the hardware mechanism and the cloud analysis server.

[0010] A further improvement lies in that: the feedback hardware includes a speaker, a microphone, and a vibration unit, and the feedback hardware is built into the head-mounted blindfold and has a feedback mechanism. The speaker provides voice feedback to the user according to the received feedback instruction, and the voice includes environmental description, object recognition result, and navigation instruction. The vibration unit provides vibration feedback according to the received feedback instruction for warning or guiding, and the vibration intensity and mode are provided with an adjustment function based on the application integration and interface module.

[0011] A further improvement lies in that: the microphone is used to receive the user's voice instruction, and the voice instruction is transmitted to the cloud analysis server through the wireless communication module.

[0012] A further improvement lies in that: the cloud analysis server includes a data processing and analysis module, a deep learning model, and a user data processing module. The deep learning model is based on the data of the Internet environment object database and the human language database, and trains the big data models of image recognition and voice devices for image recognition, voice recognition, and processing; the data processing and analysis module is used to process the received environmental information packet, analyze it by using deep learning algorithms in combination with the deep learning model, plan and analyze the data in the environmental information packet to obtain results, and the analysis content includes object recognition, obstacle detection, and path planning.

[0013] A further improvement lies in that: the user data processing module is used to receive the voice instruction uploaded by the microphone, analyze it in cooperation with the deep learning model to obtain semantics, thereby constructing a human-computer interaction. The user interacts with the control system in real time through voice instructions to query information or put forward requirements, and the cloud analysis server provides corresponding feedback after processing; and the user data processing module has a personalized recording algorithm to process the corresponding user requests with the personalized recording algorithm, including learning the user's preferences and behavior patterns to provide customized auxiliary services.

[0014] A further improvement lies in that: the application integration and interface module includes a user interface and software applications, and the user interface is based on the head-mounted blindfold. The user interface provides system operation functions for the user to configure device parameters, including adjusting the volume, selecting a feedback mode, and setting a network connection.

[0015] A further improvement lies in that: the software application is a mobile phone or computer software supporting the overall system, which is used for users or their families to remotely configure devices, view device status or historical data, and receive emergency notifications.

[0016] The beneficial effects of the present utility model are as follows:

[0017] 1. The present utility model is conveniently worn in the form of a head-mounted eye mask. It can collect visual and spatial information of the user's surrounding environment in real time through a sensor combination, and transmit the information to a cloud analysis server through a wireless communication module for analysis. The received information is processed by an artificial intelligence algorithm, and feedback instructions are sent to the head-mounted eye mask according to the analysis results to provide multi-modal sensory feedback to the user, helping the user identify obstacles ahead, locate the positions of items to be retrieved, assist the user in identifying environmental information or performing daily activities, which is more convenient to use and has sufficient information.

[0018] 2. During the operation of the present utility model, the user can interact with the system through voice commands, put forward specific requirements or inquiries. After being processed by the cloud, the system can respond immediately and provide help and feedback, and process the user's requests in a personalized manner, learn the user's preferences and behavior patterns to provide customized auxiliary services, with stronger interactivity.

[0019] 3. The present utility model has a mobile phone or computer software supporting the overall system. Based on the software, users or their families can remotely configure devices, view device status or historical data, and receive emergency notifications, which is convenient for dealing with emergencies and has diverse functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 is the front view of the hardware structure of the present utility model;

[0021] Figure 2 is the schematic diagram of the control system of the present utility model.

[0022] Wherein: 1. Head-mounted eye mask; 2. Sensor combination; 3. Wireless communication module; 4. Adjustable headband; 5. Speaker; 6. Microphone; 7. Vibration unit. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] In order to deepen the understanding of the present utility model, the following will further elaborate on the present utility model in combination with embodiments. These embodiments are only used to explain the present utility model and do not constitute a limitation on the protection scope of the present utility model. Embodiment

[0024] According to Figure 1 、 2As shown in the figure, this embodiment proposes a vision assistance system based on cloud analysis, which includes a hardware mechanism and a control system. The hardware mechanism includes a head-mounted blindfold 1, a sensor combination 2, a wireless communication module 3, and feedback hardware. The control system includes a cloud analysis server and an application integration and interface module;

[0025] The sensor combination 2, the wireless communication module 3, and the feedback hardware are all built into the head-mounted blindfold 1. The sensor combination 2 is used to collect visual and spatial information of the user's surrounding environment in real time. The wireless communication module 3 is connected to the cloud analysis server and transmits the information collected by the sensor combination 2 to the cloud analysis server. The cloud analysis server processes and analyzes the received information, and according to the analysis result, sends a feedback instruction to the head-mounted blindfold 1 through the wireless communication module 3. The feedback hardware provides multi-modal sensory feedback to the user according to the received feedback instruction to assist the user in identifying environmental information or performing daily activities. Design of the head-mounted blindfold 1: Comfortable and easy to wear, integrated with multiple groups of detectors, such as cameras, infrared sensors, ultrasonic sensors, etc., to collect environmental information in all directions. Cloud artificial intelligence analysis: The collected information is sent to the cloud through a wireless network and analyzed and judged by artificial intelligence algorithms, with fast processing speed and high accuracy. Multi-modal feedback mechanism: According to the cloud analysis result, the system provides voice feedback through the built-in speaker 5 or vibration feedback through the vibration unit 7 to guide the user to perform corresponding actions or recognize the environment. Assist users with amblyopia or blindness to identify the front path and obstacles, improving their safety and confidence in walking independently; assist users in identifying and locating items in the desktop or other close-range environments, such as stationery, daily necessities, etc.; provide environmental description and question-and-answer assistance, such as identifying house numbers, reading menus or signs, etc., to enhance the user's awareness of the surrounding environment; provide navigation assistance through vibration feedback to guide the user to avoid obstacles or point to a specific direction.

[0026] The head-mounted eye mask 1 is made of skin-friendly materials, and the head-mounted eye mask 1 is equipped with an adjustable headband 4. The design takes into account user comfort and includes an adjustable headband, breathable materials, and a skin-friendly lining material. The sensor combination 2 includes an infrared sensor, an ultrasonic sensor, an optical sensor, and a camera, and the sensor combination 2 is used to comprehensively sense the user's surrounding environment and collect specific types of data, including distance, temperature, light intensity, and images, which are combined into an environmental information packet. The wireless communication module 3 uses Wi-Fi or 5G, a Bluetooth module for real-time wireless data transmission between the hardware mechanism and the cloud analysis server. The structure of the head-mounted eye mask 1: It is designed in a lightweight and comfortable eye mask form, with an adjustable headband and skin-friendly materials inside, suitable for long-term wear. Multiple sensors and at least one high-definition camera are integrated at the front end of the eye mask for capturing environmental visual information and other relevant data. The sensor combination 2: It includes an infrared sensor, an ultrasonic sensor, an optical sensor, etc., to achieve a comprehensive perception of the user's surrounding environment. Each sensor collects specific types of data, such as distance, temperature, light intensity, etc., to provide richer environmental information. The wireless communication module 3: It uses Wi-Fi or 5G, Bluetooth technology to achieve real-time data transmission between the head-mounted device and the cloud analysis server. The module design needs to ensure stability and low power consumption.

[0027] The feedback hardware includes a speaker 5, a microphone 6, and a vibration unit 7, and the feedback hardware is built into the head-mounted eye mask 1 and has a feedback mechanism. The speaker 5 provides voice feedback to the user according to the received feedback instructions, and the voice includes environmental descriptions, object recognition results, and navigation instructions. The vibration unit 7 provides vibration feedback according to the received feedback instructions for warning or guiding, and the vibration intensity and mode are provided with an adjustment function based on the application integration and interface module. Voice feedback: According to the cloud analysis results, voice feedback is provided to the user through the built-in speaker 5. The voice content includes but is not limited to environmental descriptions, object recognition results, navigation instructions, etc. Vibration feedback: The device is built with a vibration unit 7 to provide vibration feedback as needed for warning or guiding. The vibration intensity and mode can be adjusted according to different prompt requirements.

[0028] The microphone 6 is used to receive the user's voice instructions, and the voice instructions are transmitted to the cloud analysis server through the wireless communication module 3.

[0029] The cloud analysis server includes a data processing and analysis module, a deep learning model and a user data processing module. The deep learning model is based on the Internet environment object database data and the human language database to train the image recognition and voice device big data model for image recognition, voice recognition and processing, and for functions such as object recognition, obstacle detection and voice recognition; the data processing and analysis module is used to process the received environmental information package, analyze it using a deep learning algorithm combined with a deep learning model, plan and analyze the data in the environmental information package, and obtain the results. The analysis content includes object recognition, obstacle detection, and path planning. Data processing and analysis: The cloud analysis server receives data from the head-mounted device and analyzes it using deep learning and other artificial intelligence algorithms. The analysis content includes but is not limited to object recognition, obstacle detection, path planning, etc. Deep learning model: Train specialized models, such as convolutional neural networks (CNN) for image recognition and recurrent neural networks (RNN) for voice recognition and processing, to improve recognition accuracy and response speed.

[0030] The user data processing module is used to receive the voice commands uploaded by the microphone 6, analyze them with the deep learning model, obtain semantics, and thus construct human-computer interaction. The user interacts with the control system in real time through voice commands, queries information or puts forward requirements, and the cloud analysis server provides corresponding feedback after processing; and the user data processing module has a personalized recording algorithm, which processes corresponding user requests with the personalized recording algorithm, including learning user preferences and behavior patterns to provide customized auxiliary services. The system provides real-time interactive capabilities, and users can query environmental information or request specific auxiliary services through voice commands. During operation, users interact with the system through voice commands, put forward specific requirements or inquiries, and the system can respond immediately and provide help and feedback after processing through the cloud, and process user requests in a personalized manner, learn user preferences and behavior patterns, and provide customized auxiliary services with stronger interactivity. Example

[0031] according to Figure 1 , 2 As shown, this embodiment proposes a visual assistance system based on cloud analysis, including a hardware mechanism and a control system, wherein the hardware mechanism includes a head-mounted eye mask 1, a sensor combination 2, a wireless communication module 3 and feedback hardware, and the control system includes a cloud analysis server and an application integration and interface module;

[0032] The sensor combination 2, the wireless communication module 3, and the feedback hardware are all built into the head-mounted blindfold 1. The sensor combination 2 is used to collect visual and spatial information of the user's surrounding environment in real time. The wireless communication module 3 is connected to the cloud analysis server to transmit the information collected by the sensor combination 2 to the cloud analysis server. The cloud analysis server processes and analyzes the received information, and according to the analysis results, sends feedback instructions to the head-mounted blindfold 1 through the wireless communication module 3. The feedback hardware provides multi-modal sensory feedback to the user according to the received feedback instructions to assist the user in identifying environmental information or performing daily activities. Design of the head-mounted blindfold 1: Comfortable and easy to wear, integrated with multiple groups of detectors, such as cameras, infrared sensors, ultrasonic sensors, etc., to collect environmental information in all directions. Cloud artificial intelligence analysis: The collected information is sent to the cloud through the wireless network and analyzed and judged by artificial intelligence algorithms, with fast processing speed and high accuracy. Multi-modal feedback mechanism: According to the cloud analysis results, the system provides voice feedback through the built-in speaker 5 or vibration feedback through the vibration unit 7 to guide the user to perform corresponding actions or recognize the environment. Assist users with amblyopia or blindness to identify the path and obstacles ahead, improving their safety and confidence in independent walking; assist users in identifying and locating items in the desktop or other nearby environments, such as stationery, daily necessities, etc.; provide environmental descriptions and Q&A assistance, such as identifying house numbers, reading menus or signs, etc., to enhance the user's awareness of the surrounding environment; provide navigation assistance through vibration feedback to guide the user to avoid obstacles or point to a specific direction.

[0033] The application integration and interface module includes a user interface and software applications. The user interface is based on the head-mounted blindfold 1. The user interface provides system operation functions for the user to configure device parameters, including adjusting the volume, selecting a feedback mode, and setting up a network connection. The software application is a mobile phone or computer software supporting the overall system, used for the user or family members to remotely configure the device, view the device status or historical data, and receive emergency notifications. User interface: Provide a simple and intuitive user interface that allows the user to configure device settings, such as adjusting the volume, selecting a feedback mode (voice or vibration), setting up a network connection, etc. Software application: Develop a supporting mobile phone or computer software application that enables the user or family members to remotely configure the device, view the device status or historical data, and receive emergency notifications, facilitating the response to emergency situations and having diverse functions.

[0034] The present utility model is conveniently worn in the form of a head-mounted eye mask 1. The visual and spatial information of the user's surrounding environment is collected in real time through a sensor combination 2, and the information is transmitted to a cloud analysis server through a wireless communication module 3 for analysis. The received information is processed by an artificial intelligence algorithm, and feedback instructions are sent to the head-mounted eye mask 1 according to the analysis results to provide the user with multimodal sensory feedback, helping the user identify obstacles ahead, locate the positions of items to be retrieved, assist the user in identifying environmental information or performing daily activities, making it more convenient to use and with sufficient information. Moreover, during the operation of the present utility model, the user can interact with the system through voice commands, put forward specific requirements or inquiries. After being processed by the cloud, the system can respond immediately and provide assistance and feedback, and process the user's requests in a personalized manner, learning the user's preferences and behavior patterns to provide customized auxiliary services, with stronger interactivity. At the same time, the present utility model is equipped with a mobile phone or computer software for the supporting overall system. Based on the software, the user or family member can remotely configure the device, view the device status or historical data, and receive emergency notifications, facilitating the response to emergencies and with diverse functions.

[0035] The above has shown and described the basic principles, main features and advantages of the present utility model. Those skilled in the art should understand that the present utility model is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present utility model. Without departing from the spirit and scope of the present utility model, the present utility model will have various changes and improvements, and these changes and improvements all fall within the scope of the present utility model claimed. The scope of protection claimed by the present utility model is defined by the appended claims and their equivalents.

Claims

1. A visual assistance system based on cloud analysis, including a hardware mechanism and a control system, characterized in that: The hardware mechanism comprises a head-mounted eye mask (1), a sensor assembly (2), a wireless communication module (3) and feedback hardware, and the control system comprises a cloud analysis server and an application integration and interface module; The sensor assembly (2), wireless communication module (3) and feedback hardware are all built into the head-mounted eye mask (1), and the sensor assembly (2) is used to collect visual and spatial information of the user's surrounding environment in real time. The wireless communication module (3) is connected to a cloud analysis server to transmit the information collected by the sensor assembly (2) to the cloud analysis server. The cloud analysis server processes and analyzes the received information and sends a feedback instruction to the head-mounted eye mask (1) through the wireless communication module (3) based on the analysis result. The feedback hardware provides multi-modal sensory feedback to the user based on the received feedback instruction to assist the user in identifying environmental information or performing daily activities.

2. The visual assistance system based on cloud analysis according to claim 1, characterized in that: The head-mounted eye mask (1) is made of a skin-friendly material, and the head-mounted eye mask (1) is provided with an adjustable headband (4).

3. The visual assistance system based on cloud analysis according to claim 2, characterized in that: The sensor combination (2) includes an infrared sensor, an ultrasonic sensor, an optical sensor and a camera, and the sensor combination (2) is used to perform all-round perception of the user's surrounding environment, collect specific types of data, including distance, temperature, light intensity and images, and combine them into an environmental information package.

4. The visual assistance system based on cloud analysis according to claim 3, characterized in that: The wireless communication module (3) adopts a Wi-Fi or 5G or Bluetooth module and is used for real-time wireless data transmission between the hardware mechanism and the cloud analysis server.

5. The visual assistance system based on cloud analysis according to claim 4, characterized in that: The feedback hardware comprises a speaker (5), a microphone (6) and a vibration unit (7), and the feedback hardware is built into the head-mounted eye mask (1) and has a feedback mechanism. The speaker (5) provides voice feedback to the user according to the received feedback instruction, and the voice includes an environment description, an object recognition result, and a navigation instruction. The vibration unit (7) provides vibration feedback for warning or guidance according to the received feedback instruction, and the vibration intensity and mode are adjusted based on the application integration and interface module.

6. The visual assistance system based on cloud analysis according to claim 5, characterized in that: The microphone (6) is used to receive voice commands from the user, and the voice commands are transmitted to a cloud analysis server via the wireless communication module (3).

7. The visual assistance system based on cloud analysis according to claim 6, characterized in that: The cloud-based analysis server includes a data processing and analysis module, a deep learning model and a user data processing module. The deep learning model is based on the Internet environment object database data and the human language database to train image recognition and voice equipment big data models for image recognition, voice recognition and processing; the data processing and analysis module is used to process the received environmental information packets, analyze them using a deep learning algorithm combined with a deep learning model, plan and analyze the data in the environmental information packets, and obtain results. The analysis content includes object recognition, obstacle detection, and path planning.

8. The visual assistance system based on cloud analysis according to claim 7, characterized in that: The user data processing module is used to receive voice commands uploaded by the microphone (6), analyze them with the help of a deep learning model, obtain semantics, and thereby construct human-computer interaction. The user interacts with the control system in real time through voice commands to query information or put forward requirements, and the cloud analysis server provides corresponding feedback after processing. The user data processing module has a personalized recording algorithm to process corresponding user requests, including learning user preferences and behavior patterns to provide customized auxiliary services.

9. The visual assistance system based on cloud analysis according to claim 1, characterized in that: The application integration and interface module comprises a user interface and a software application, and the user interface is based on a head-mounted eye mask (1). The user interface provides a system operation function for a user to configure device parameters, including adjusting volume, selecting a feedback mode, and setting a network connection.

10. The visual assistance system based on cloud analysis according to claim 9, characterized in that: The software application is a mobile phone or computer software that supports the overall system, which is used by users or family members to remotely configure the device, view device status or historical data, and receive emergency notifications.

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