Dangerous scene warning method and terminal equipment

Abstract

The present application provides a dangerous scene warning method and terminal device, which relates to the field of terminal technology, and can classify user groups, match different dangerous scenes, and provide warning assistance in different warning methods when the user is in a dangerous scene. The method includes: obtaining user information, matching user group categories according to user information; matching one or more dangerous scenes according to user group categories; obtaining environmental information, and judging whether the user is in one or more dangerous scenes according to the environmental information; if the user is in one or more dangerous scenes, matching the warning method to start the warning.

Description

Technical Field

[0001] The present application relates to the field of terminal technology, and in particular to a dangerous scene early warning method and terminal equipment. Background Art

[0002] With the development of science and technology, the application of wearable devices has become increasingly popular in recent years. At present, most wearable devices such as bracelets provide health monitoring functions, or some smart glasses provide dangerous scene recognition and alarm functions. When danger occurs, the smart device detects the danger and alerts the outside world for help. However, since the danger has already occurred and it takes a certain amount of time to wait for rescue, the user cannot escape from danger in time, resulting in certain personal and property losses. Summary of the invention

[0003] The present application provides a dangerous scene warning method and terminal device, which can configure different dangerous scenes for different user groups and configure different warning methods for different dangerous scenes, so as to help users avoid danger and can help users escape from danger in time.

[0004] In order to achieve the above objectives, this application adopts the following technical solutions:

[0005] In a first aspect, the present application provides a dangerous scene warning method, which may include: obtaining user information, matching user group categories according to the user information, and matching one or more dangerous scenes according to the user group categories. Obtaining environmental information, and judging whether the user is in one or more dangerous scenes according to the environmental information. If the user is in one or more dangerous scenes, matching the warning method to start the warning.

[0006] Exemplarily, the user information obtained may include the user's facial data, and then based on the user's facial data such as wrinkles, it can be determined that the current user is a minor, that is, the user group category of the current user is a minor, and the pre-configured dangerous scenes configured for minors are queried, and based on the collected environmental information, it is determined whether the user's current environment is a dangerous scene for minors. If it is a dangerous scene for minors, early warning assistance is provided to the user according to the pre-configured early warning method.

[0007] In this way, different dangerous scenarios and warning methods are pre-configured for different user group categories. The collected information is used to determine the user group category to which the user belongs, and then to determine whether the current user is in the corresponding dangerous scenario. If in a dangerous scenario, the corresponding warning method is used to provide warning assistance to the user, remind the user to pay attention to the danger, and help the user escape from danger.

[0008] In a possible implementation, matching user group categories according to user information includes: determining user characteristic information according to the user information; the user characteristic information includes any one or more of the following: age, health condition, gender, occupation; matching user group categories according to the user characteristic information.

[0009] For example, the collected user information may include user facial information, such as skin laxity, wrinkles, hairstyle, etc. User information may also include user physical data, such as heart rate, blood pressure, etc. User characteristic information of the current user, such as age, etc., may be determined based on the user information, so that the corresponding user group category may be matched based on the user age. If the current user is determined to be a minor based on the user age, the user belongs to the minor group.

[0010] In a possible implementation, the user group categories include any one or more of the following: minors, adults, elderly people, sick people, people in special occupations, and special protected groups.

[0011] For example, some special occupations, such as high-risk occupations, will face some scenarios that ordinary user groups cannot access, and these scenarios may be dangerous to users. Therefore, the user groups of special occupations are divided into categories, and then corresponding dangerous scenarios can be configured for the special occupation groups according to the characteristics of the personnel in this category to prevent the occurrence of danger or help users escape from danger as soon as possible. For example, some special protection groups, such as the disabled group, some dangers that are easier to avoid or escape for ordinary user groups may be very dangerous compared to the disabled group. Therefore, special protection groups are divided into categories to comprehensively ensure user safety.

[0012] In a possible implementation, matching the user group category according to the user characteristic information includes: matching the user group category according to the user's age and / or health condition and / or gender and / or occupation.

[0013] In a possible implementation, one or more dangerous scenarios are matched according to the user group category, including: if the user is a minor, the dangerous scenarios include any one or more of the following: drowning, electric shock, crossroads, contact with strangers, and dangerous items. If the user is an adult, the dangerous scenarios include any one or more of the following: dangerous operation driving, driving in a dangerous environment, and driving on dangerous roads. If the user is an elderly person, the dangerous scenarios include any one or more of the following: drug use, diet, disease attack, and fraud. If the user is a sick person, the dangerous scenarios include any one or more of the following: dangerous scenarios for asthma patients and dangerous scenarios for heart patients; dangerous scenarios for asthma patients include any one or more of the following: poor air quality, pollen, dust, and dense crowds; dangerous scenarios for heart patients include any one or more of the following: high-altitude playgrounds, strenuous exercise, mountain climbing, and altitude sickness. If the user is a special professional, the dangerous scenarios include any one or more of the following: animals going crazy, outdoor work, and abnormal protective equipment. If the user is a special protected group, the dangerous scenarios include any one or more of the following: traveling alone at night, being followed by a stranger, a pregnant woman squatting for a long time, and high traffic density.

[0014] In this way, according to the user group category, the dangerous scene corresponding to the group category is matched to achieve maximum user safety.

[0015] In a possible implementation, one or more dangerous scenarios are matched according to user group categories, including: matching natural disaster dangerous scenarios and dangerous animal and plant dangerous scenarios for all users. Natural disaster dangerous scenarios include any one or more of the following: fire, earthquake, mudslide, sandstorm, tsunami. Dangerous animal and plant dangerous scenarios include any one or more of the following: highly dangerous animals, poisonous plants.

[0016] In this way, some dangerous scenes are configured as basic dangerous scenes for all users. These basic dangerous scenes will pose a certain threat to all users, and the degree of danger is relatively high. Therefore, in order to ensure the safety of users and prevent them from being in danger, the above basic dangerous scenes are configured for each user, such as natural disaster dangerous scenes and dangerous animal and plant dangerous scenes.

[0017] In a possible implementation, matching one or more dangerous scenarios according to user group categories includes: matching early warning modes according to user group categories. Early warning modes include a first early warning mode and at least one second early warning mode. The first early warning mode corresponds to all users, and the second early warning mode corresponds to user group categories. Matching one or more dangerous scenarios according to early warning modes. Dangerous scenarios include: a first dangerous scenario corresponding to the first early warning mode and a second dangerous scenario corresponding to the second early warning mode.

[0018] In this way, different warning modes are configured to correspond to different dangerous scenarios, and then warning modes are matched to different user groups, that is, corresponding to different dangerous scenarios. Dangerous scenarios are divided to provide users with more systematic danger warnings.

[0019] In a possible implementation, the warning method includes any one or more of the following: warning reminder, self-rescue knowledge broadcast, escape guidance, broadcast for help, and alarm rescue.

[0020] Exemplarily, dangerous scenes include potential dangerous scenes, that is, there is potential danger in the current scene, such as the potential possibility of a traffic accident when the user passes through an intersection. At this time, an early warning reminder can be issued. When the user is in a dangerous scene such as a fire, the user can be provided with escape guidance and alarm rescue, so as to help the user escape from danger in time.

[0021] From this, it can be seen that different warning methods can be pre-configured for different dangerous scenarios. Then, when it is determined that the user is in a dangerous scenario, the best warning assistance is provided to the user according to the pre-configured warning method for the current dangerous scenario, so as to avoid danger to the user or enable the user to escape from danger as soon as possible.

[0022] In one possible implementation, if the user is in one or more dangerous scenarios, a warning is initiated by matching the warning method, including: initiating a warning according to matching the warning method with one or more dangerous scenarios; or, dividing the danger level into levels according to the potential danger of one or more dangerous scenarios to the user, and initiating a warning according to the danger level matching the warning method; or, initiating a warning according to matching the warning method with the danger level determined by the user; or, initiating a warning according to the warning method that matches the one or more dangerous scenarios determined by the user.

[0023] In this way, the danger level and warning method corresponding to the dangerous scene can be flexibly configured according to the dangerous scene or the actual needs of the user, so that the user can avoid or escape from the danger as soon as possible. In addition, higher danger levels can be assigned to dangerous scenes with greater potential dangers, and more warning methods can be configured. For example, in the case of fire, early warning reminders, self-rescue knowledge playback, escape guidance, broadcasting for help, and alarm rescue can be configured to help users achieve self-rescue and escape from the current dangerous scene as soon as possible.

[0024] In one possible implementation, after obtaining user information and matching user group categories according to the user information, the method includes: prompting the user to select and determine one or more dangerous scenarios; or, automatically matching one or more dangerous scenarios according to the user group category; or, after automatically matching one or more dangerous scenarios according to the user group category, prompting the user to select and determine one or more dangerous scenarios; or, prompting the user to create one or more dangerous scenarios; or, after automatically matching one or more first dangerous scenarios according to the user group category, prompting the user to create one or more second dangerous scenarios, which dangerous scenarios include a first dangerous scenario and a second dangerous scenario.

[0025] In this way, different dangerous scene configurations can be provided to users more flexibly. Moreover, users can freely select or create dangerous scenes according to their own circumstances. If the user's ability is sufficient to deal with certain dangerous scenes, the user can choose to close these dangerous scenes without warning. If the user believes that other dangerous scenes will cause danger to the user, the corresponding dangerous scenes can be created. Flexible configuration methods can further improve the user experience.

[0026] In a possible implementation, the user information includes any one or more of the following: user facial information, user vital sign data, and information input by the user.

[0027] In a possible implementation, the environmental information includes image information and / or audio information of the environment in which the user is located and / or information detected by an environmental sensor. The information detected by the environmental sensor includes any one or more of the following: air humidity, ambient temperature, ambient light, ambient odor, ambient sound, and atmospheric pressure.

[0028] In this way, the smart device can choose to combine multiple environmental information to determine the user's current environment, achieve more accurate early warning judgment, and reduce misjudgment. For example, it can be combined with the current image information to determine that the user is driving a vehicle, the current ambient light is dim, and combined with the current ambient light information to determine that the current user is driving at night. In this way, it can be determined whether the current user is in a dangerous scene based on the pre-configured dangerous scene.

[0029] In a second aspect, the present application provides a terminal device, which may include: one or more processors, a memory, and one or more computer programs. One or more computer programs are stored in the memory, and one or more computer programs include instructions. When the instructions are executed by the terminal device, the terminal device executes: obtaining user information, matching user group categories according to the user information; matching one or more dangerous scenes according to the user group category. Obtaining environmental information, judging whether the user is in one or more dangerous scenes according to the environmental information; if the user is in one or more dangerous scenes, matching the warning method to start the warning.

[0030] In a possible implementation, when the instruction is executed by the terminal device, the terminal device executes: determining user characteristic information according to user information, and matching user group categories according to the user information. The user characteristic information includes any one or more of the following: age, health condition, gender, and occupation.

[0031] Exemplarily, user group categories include any one or more of the following: minors, adults, elderly people, sick people, people in special occupations, and special protected groups.

[0032] In a possible implementation, when the instruction is executed by the terminal device, the terminal device is caused to perform: matching user group categories according to user age and / or health status and / or gender and / or occupation.

[0033] In one possible implementation, when the instruction is executed by the terminal device, the terminal device executes: matching one or more dangerous scenarios according to the user group category, including: if the user is a minor, the dangerous scenarios include any one or more of the following: drowning, electric shock, intersection, contact with strangers, dangerous objects. If the user is an adult, the dangerous scenarios include any one or more of the following: dangerous driving, driving in a dangerous environment, driving on a dangerous road. If the user is an elderly person, the dangerous scenarios include any one or more of the following: drug use, diet, disease attack, fraud. If the user is a sick person, the dangerous scenarios include any one or more of the following: dangerous scenarios for asthma patients, dangerous scenarios for heart patients; dangerous scenarios for asthma patients include any one or more of the following: poor air quality, pollen, dust, and dense crowds; dangerous scenarios for heart patients include any one or more of the following: high-altitude playgrounds, strenuous exercise, mountain climbing, and altitude sickness. If the user is a person in a special profession, the dangerous scenarios include any one or more of the following: mad animals, outdoor work, and abnormal protective equipment; if the user is a special protected group, the dangerous scenarios include any one or more of the following: traveling alone at night, being followed by a stranger, a pregnant woman squatting for a long time, and high traffic density.

[0034] In a possible implementation, when the instruction is executed by the terminal device, the terminal device executes: matching natural disaster danger scenes and dangerous animal and plant danger scenes for all users. Among them, natural disaster danger scenes include any one or more of the following: fire, earthquake, mudslide, sandstorm, tsunami. Dangerous animal and plant danger scenes include any one or more of the following: highly dangerous animals, poisonous plants.

[0035] In a possible implementation, when the instruction is executed by the terminal device, the terminal device executes: matching the warning mode according to the user group category. The warning mode includes a first warning mode and at least one second warning mode. The first warning mode corresponds to all users, and the second warning mode corresponds to the user group category. Matching one or more danger scenarios according to the warning mode. The danger scenarios include: a first danger scenario corresponding to the first warning mode and a second danger scenario corresponding to the second warning mode.

[0036] In a possible implementation, the warning method includes any one or more of the following: warning reminder, self-rescue knowledge broadcast, escape guidance, broadcast for help, and alarm rescue.

[0037] In one possible implementation, when the instruction is executed by the terminal device, the terminal device executes: initiating an early warning according to matching the early warning method with one or more dangerous scenarios; or, dividing the danger level according to the potential danger of one or more dangerous scenarios to the user, and initiating an early warning according to matching the early warning method with the danger level; or, initiating an early warning according to matching the early warning method with the danger level determined by the user; or, initiating an early warning according to the early warning method that matches the one or more dangerous scenarios determined by the user.

[0038] In one possible implementation, when the instruction is executed by the terminal device, the terminal device executes: prompting the user to select and determine one or more dangerous scenarios; or, automatically matching one or more dangerous scenarios according to user group categories; or, after automatically matching one or more dangerous scenarios according to user group categories, prompting the user to select and determine one or more dangerous scenarios; or, prompting the user to create one or more dangerous scenarios; or, after automatically matching one or more first dangerous scenarios according to user group categories, prompting the user to create one or more second dangerous scenarios, where the dangerous scenarios include the first dangerous scenarios and the second dangerous scenarios.

[0039] In a possible implementation, the user information includes any one or more of the following: user facial information, user vital sign data, and information input by the user.

[0040] In a possible implementation, the environmental information includes image information and / or audio information of the environment in which the user is located and / or information detected by an environmental sensor. The information detected by the environmental sensor includes any one or more of the following: air humidity, ambient temperature, ambient light, ambient odor, ambient sound, and atmospheric pressure.

[0041] In a third aspect, the present application provides a terminal device having the function of implementing the dangerous scene warning method described in the first aspect and any possible implementation thereof. The function can be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions.

[0042] In a fourth aspect, the present application provides a computer storage medium comprising computer instructions. When the computer instructions are executed on a terminal device, the terminal device executes the dangerous scene warning method as described in the first aspect and any possible implementation method thereof.

[0043] In a fifth aspect, the present application provides a computer program product. When the computer program product is run on a terminal device, the terminal device executes the dangerous scene warning method as described in the above-mentioned first aspect and any possible implementation method thereof.

[0044] In a sixth aspect, a circuit system is provided, the circuit system including a processing circuit, the processing circuit being configured to execute the dangerous scene warning method as described in the first aspect and any possible implementation thereof.

[0045] In the seventh aspect, an embodiment of the present application provides a chip system, comprising at least one processor and at least one interface circuit, wherein the at least one interface circuit is used to perform transceiver functions and send instructions to at least one processor, and when the at least one processor executes the instructions, the at least one processor executes the dangerous scene warning method as described in the first aspect above and any possible implementation method thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A schematic diagram of the structure of a communication system provided in an embodiment of the present application;

[0047] Figure 2 A schematic diagram of the structure of a wearable device provided in an embodiment of the present application;

[0048] Figure 3 A schematic diagram of the structure of a terminal device provided in an embodiment of the present application;

[0049] Figure 4 A schematic diagram of a flow chart of a dangerous scene warning method provided in an embodiment of the present application;

[0050] Figure 5 Schematic diagram of application scenarios of the dangerous scene warning method provided in the embodiment of the present application Figure 1 ;

[0051] Figure 6 Schematic diagram of application scenarios of the dangerous scene warning method provided in the embodiment of the present application Figure 2 ;

[0052] Figure 7 Schematic diagram of application scenarios of the dangerous scene warning method provided in the embodiment of the present application Figure 3 ;

[0053] Figure 8 Schematic diagram of application scenarios of the dangerous scene warning method provided in the embodiment of the present application Figure 4 ;

[0054] Fig. 9 Schematic diagram of application scenarios of the dangerous scene warning method provided in the embodiment of the present application Figure 5 ;

[0055] Fig.10 Schematic diagram of application scenarios of the dangerous scene warning method provided in the embodiment of the present application Figure 6 ;

[0056] Fig.11 Schematic diagram of application scenarios of the dangerous scene warning method provided in the embodiment of the present application Figure 7 ;

[0057] Fig.12 Schematic diagram of application scenarios of the dangerous scene warning method provided in the embodiment of the present application Figure 8 ;

[0058] Fig.13 Schematic diagram of application scenarios of the dangerous scene warning method provided in the embodiment of the present application Figure 9 ;

[0059] Fig.14 Schematic diagram of application scenarios of the dangerous scene warning method provided in the embodiment of the present application Figure 10 ;

[0060] Fig.15 Schematic diagram of application scenarios of the dangerous scene warning method provided in the embodiment of the present application Figure 10 one;

[0061] Fig.16 A schematic diagram of the structure of a terminal device provided in an embodiment of the present application;

[0062] Fig.17 A schematic diagram of the structure of the chip system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0063] The dangerous scene warning method and wearable device provided in the embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0064] The terms "including" and "having" and any variations thereof mentioned in the description of this application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0065] It should be noted that, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0066] In the description of this application, unless otherwise specified, the meaning of "plurality" refers to two or more. "And / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0067] The solution of the embodiment of the present application can be applied to a single smart device, and can also be applied to a system composed of multiple smart devices. Among them, the smart device can be a wearable device such as smart glasses, smart bracelets, wireless headphones, etc., and can also be a mobile phone, a tablet computer, a laptop computer, a personal digital assistant (PDA), etc., and can also be an artificial intelligence (AI) terminal such as an intelligent robot. For example: the system can be a system composed of multiple wearable devices, and can also be a system composed of a wearable device and a terminal such as a mobile phone and / or an artificial intelligence terminal. In a system composed of multiple smart devices, some or all of the smart devices are used to collect information, and some smart devices are used to determine whether the user is in a dangerous scene based on the collected information.

[0068] For example, Figure 1It shows a communication system 100 composed of a wearable device and a terminal device. In the communication system 100, one or more wearable devices 101 and one or more terminal devices 102 may be included. The wearable device 101 may respectively establish a short-range wireless communication connection with the one or more terminal devices 102 to realize the communication function between the wearable device 101 and the terminal device 102. For example, the wearable device 101 may establish a communication connection such as a Bluetooth connection, a Wi-Fi (wireless fidelity) connection, a ZigBee (ZigBee protocol) connection or an NFC (near field communication) connection with the terminal device 102. Of course, the wearable device 101 may also establish a communication connection with the terminal device 102 through a cellular network interconnection or a switching device (for example, a USB data cable or a Dock device), and the embodiments of the present application do not impose any restrictions on this.

[0069] Take the wearable device 101 as smart glasses as an example. Figure 2 As shown, the smart glasses include:

[0070] The application processor (AP) 201, also called the main processor, runs the operating system (OS) and related application software.

[0071] In some implementations of the embodiments of the present application, the AP can perform danger assessment, decision-making, emergency response, and self-rescue guidance.

[0072] The short-range processor 202, i.e., the short-range baseband communication processing unit, runs short-range communication protocol software, such as the interconnection and networking of smart devices based on Bluetooth and WiFi protocols, for example, the communication interconnection and networking between smart devices.

[0073] The camera is used to capture still images or videos. The object is projected onto the photosensitive element through the lens to generate an optical image. The photosensitive element can be a charge coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the light signal into an electrical signal, which is then passed to the ISP to be converted into a digital image signal.

[0074] The graphics processing unit (GPU) 203 is used to perform feature analysis and calculation on the image data and record the scene image, which may include 2D (dimension) and / or 3D processing, such as superimposing position positioning information.

[0075] The image signal processor (ISP) 204 is used to perform image processing (eg, feature extraction, comparison analysis) on the captured image to generate image feature data, and may include a processor core that performs necessary software processing or pure hardware implementation.

[0076] The above-mentioned image can be an image captured by the camera of the smart glasses, or it can be an image captured by other devices and received by the smart glasses. The embodiment of the present application does not make any specific limitation on this.

[0077] In some implementations of the embodiments of the present application, GPU 203 and ISP 204 process the collected images and compress / decompress the images. Based on the images, AP 201 determines the current scene of the user and whether the current scene is a dangerous scene.

[0078] The display subsystem 205 performs display processing on the image to be displayed generated by the GPU 203. The display subsystem includes a display and an external interface. The display subsystem 205 uses the display to display, or the display subsystem 205 uses the external interface to send the image to be displayed to other smart devices so that other smart devices can display it.

[0079] The display may be a virtual display or a lens of smart glasses. When the display is a virtual display, the image to be displayed may be displayed on the virtual display in the air, without being projected on a physical screen.

[0080] In some implementations of the embodiments of the present application, the displayed image may be self-rescue knowledge or self-rescue guidance images corresponding to dangerous scenes, etc. When the display is displayed using a smart glasses display, since the virtual display or the lenses of the smart glasses can move with the user's field of view, it is more convenient to watch, and it is convenient for the user to watch the self-rescue knowledge or self-rescue guidance images.

[0081] The storage support 206 includes an external memory interface and an internal memory, and is used to implement the storage interface function to connect to the external memory and perform necessary internal storage and caching of the received data.

[0082] The neural-network processing unit (NPU) 207 is an artificial intelligence processor (AI processor), which is usually a device for processing convolutional neural networks (CNN). It can be dedicated to artificial intelligence operations, such as using CNN models to perform a large amount of information recognition and screening processing, and can also specifically implement the training function of a part of the CNN model.

[0083] In some implementations of the embodiments of the present application, NPU207 implements modeling, analysis, and identification of dangerous scenes. For example, a scene that the user often passes by is a dangerous scene, such as an intersection. At this time, the corresponding dangerous scene of the intersection can be modeled and trained according to the scene, so that the wearable device 101 can more accurately judge the dangerous scene of the intersection and prevent the occurrence of danger. The specific modeling training method can be referred to the prior art, and the embodiments of the present application will not be specifically described.

[0084] The security element (SE) 208 is responsible for processing privacy information and has independent memory and processor inside to ensure system security.

[0085] The radio frequency front end (RFFE) 209 mainly includes the radio frequency switch, duplexer, filter, power amplifier (PA), etc. required for wireless communication. It is connected to the radio frequency integrated circuit (RFIC), which is used as a communication hardware acceleration, i.e., a communication processor.

[0086] Wireless transceiver (WTR) mainly includes mixer, transformer and variable gain amplifier.

[0087] System on chip (SoC), also known as system on chip, is a general term for systems running on a chip with a dedicated integrated circuit. Figure 2 Shown is a complete system with all contents embedded in software / hardware.

[0088] The above-mentioned RFFE 209 and WTR work together with various components within the SoC to perform various types of cellular wireless communications, including 2G / 3G / 4G / 5G communications.

[0089] The short-range communication chip 210 includes, for example, WiFi, Bluetooth, NFC, radio, global positioning system (GPS), etc.

[0090] The codec chip 211, connected to an external headset / speaker / microphone, belongs to the voice subsystem, processes voice signals, converts the original voice signals from nature into digital voice signals and performs pulse code modulation (PCM), and outputs voice / audio signals (64kbps or higher) for further processing by the SoC.

[0091] The sensor subsystem 212 mainly includes a processor for processing sensor data, specifically for collecting, classifying, identifying and processing sensor data. The sensor may include any one or more of the following: pressure sensor, gyroscope sensor, air pressure sensor, magnetic sensor, acceleration sensor, distance sensor, proximity light sensor, fingerprint sensor, temperature sensor, touch sensor, ambient light sensor, bone conduction sensor, 3D face recognition. The embodiment of the present application does not impose any limitation on this.

[0092] The power management IC (PMIC) 213, also called the power management unit (PMU), belongs to the clock / voltage domain subsystem and belongs to the power management (PM) core. It is used to generate the voltage and clock required for other chips to work, including batteries, crystal oscillators, etc., to achieve power management.

[0093] It is understandable that the structure shown in the embodiment of the present application does not constitute a specific limitation on the wearable device 101. Figure 2 More or fewer components may be shown, two or more components may be combined, or there may be a different configuration of components. Figure 2 The various components shown in the drawings may be implemented in hardware, software, or a combination of hardware and software, including one or more signal processing or application specific integrated circuits.

[0094] like Figure 3As shown, the terminal device 102 in the above communication system 100 can be specifically a mobile phone. The terminal device 102 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a radio frequency module 150, a communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a button 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc. Among them, the sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, etc.

[0095] It is understood that the structure illustrated in the embodiment of the present application does not constitute a specific limitation on the terminal device 102. In other embodiments of the present application, the terminal device 102 may include more or fewer components than shown in the figure, or combine some components, or split some components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0096] The processor 110 may include one or more processing units, for example, the processor 110 may include an application processor (AP), a modem processor, a graphics processor (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.

[0097] The controller may be the nerve center and command center of the terminal device 102. The controller may generate an operation control signal according to the instruction operation code and the timing signal to complete the control of fetching and executing instructions.

[0098] The processor 110 may also be provided with a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. The memory may store instructions or data that the processor 110 has just used or cyclically used. If the processor 110 needs to use the instruction or data again, it may be directly called from the memory. This avoids repeated access, reduces the waiting time of the processor 110, and thus improves the efficiency of the system.

[0099] In some embodiments, the processor 110 may include one or more interfaces. The interface may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc.

[0100] The I2C interface is a bidirectional synchronous serial bus, including a serial data line (SDA) and a serial clock line (SCL). In some embodiments, the processor 110 may include multiple groups of I2C buses. The processor 110 may be coupled to the touch sensor 180K, the charger, the flash, the camera 193, etc. through different I2C bus interfaces. For example: the processor 110 may be coupled to the touch sensor 180K through the I2C interface, so that the processor 110 communicates with the touch sensor 180K through the I2C bus interface, thereby realizing the touch function of the terminal device 102.

[0101] The I2S interface can be used for audio communication. In some embodiments, the processor 110 can include multiple I2S buses. The processor 110 can be coupled to the audio module 170 via the I2S bus to achieve communication between the processor 110 and the audio module 170. In some embodiments, the audio module 170 can transmit an audio signal to the communication module 160 via the I2S interface to achieve the function of answering a call through a Bluetooth headset.

[0102] The PCM interface can also be used for audio communication, sampling, quantizing and encoding analog signals. In some embodiments, the audio module 170 and the communication module 160 can be coupled via a PCM bus interface. In some embodiments, the audio module 170 can also transmit audio signals to the communication module 160 via the PCM interface to implement the function of answering calls via a Bluetooth headset. Both the I2S interface and the PCM interface can be used for audio communication.

[0103] The UART interface is a universal serial data bus for asynchronous communication. The bus can be a bidirectional communication bus. It converts the data to be transmitted between serial communication and parallel communication. In some embodiments, the UART interface is generally used to connect the processor 110 and the communication module 160. For example, the processor 110 communicates with the Bluetooth module in the communication module 160 through the UART interface to implement the Bluetooth function. In some embodiments, the audio module 170 can transmit an audio signal to the communication module 160 through the UART interface to implement the function of playing music through a Bluetooth headset.

[0104] The MIPI interface can be used to connect the processor 110 with peripheral devices such as the display screen 194 and the camera 193. The MIPI interface includes a camera serial interface (CSI), a display serial interface (DSI), etc. In some embodiments, the processor 110 and the camera 193 communicate via the CSI interface to implement the shooting function of the terminal device 102. The processor 110 and the display screen 194 communicate via the DSI interface to implement the display function of the terminal device 102.

[0105] The GPIO interface can be configured by software. The GPIO interface can be configured as a control signal or as a data signal. In some embodiments, the GPIO interface can be used to connect the processor 110 with the camera 193, the display 194, the communication module 160, the audio module 170, the sensor module 180, etc. The GPIO interface can also be configured as an I2C interface, an I2S interface, a UART interface, a MIPI interface, etc.

[0106] The USB interface 130 is an interface that complies with the USB standard specification, and specifically can be a Mini USB interface, a Micro USB interface, a USB Type C interface, etc. The USB interface 130 can be used to connect a charger to charge the terminal device 102, and can also be used to transmit data between the terminal device 102 and peripheral devices. It can also be used to connect headphones to play audio through the headphones. The interface can also be used to connect other electronic devices, such as AR devices, etc.

[0107] It is understandable that the interface connection relationship between the modules illustrated in the embodiment of the present application is only a schematic illustration and does not constitute a structural limitation on the terminal device 102. In other embodiments of the present application, the terminal device 102 may also adopt different interface connection methods in the above embodiments, or a combination of multiple interface connection methods.

[0108] The charging management module 140 is used to receive charging input from a charger. The charger may be a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 140 may receive charging input from a wired charger through the USB interface 130. In some wireless charging embodiments, the charging management module 140 may receive wireless charging input through a wireless charging coil of the terminal device 102. While the charging management module 140 is charging the battery 142, it may also power the electronic device through the power management module 141.

[0109] The power management module 141 is used to connect the battery 142, the charging management module 140 and the processor 110. The power management module 141 receives input from the battery 142 and / or the charging management module 140, and supplies power to the processor 110, the internal memory 121, the external memory, the display screen 194, the camera 193, and the communication module 160. The power management module 141 can also be used to monitor parameters such as battery capacity, battery cycle number, battery health status (leakage, impedance), etc. In some other embodiments, the power management module 141 can also be set in the processor 110. In other embodiments, the power management module 141 and the charging management module 140 can also be set in the same device.

[0110] The wireless communication function of the terminal device 102 can be implemented through antenna 1, antenna 2, RF module 150, communication module 160, modem processor and baseband processor.

[0111] Antenna 1 and antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in terminal device 102 can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve the utilization of antennas. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In some other embodiments, the antenna can be used in combination with a tuning switch.

[0112] The RF module 150 can provide solutions for wireless communications including 2G / 3G / 4G / 5G, etc., applied to the terminal device 102. The RF module 150 may include at least one filter, a switch, a power amplifier, a low noise amplifier (LNA), etc. The RF module 150 can receive electromagnetic waves from the antenna 1, and filter, amplify, and process the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation. The RF module 150 can also amplify the signal modulated by the modulation and demodulation processor, and convert it into electromagnetic waves for radiation through the antenna 1. In some embodiments, at least some of the functional modules of the RF module 150 can be set in the processor 110. In some embodiments, at least some of the functional modules of the RF module 150 can be set in the same device as at least some of the modules of the processor 110.

[0113] The modem processor may include a modulator and a demodulator. Among them, the modulator is used to modulate the low-frequency baseband signal to be sent into a medium-high frequency signal. The demodulator is used to demodulate the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low-frequency baseband signal to the baseband processor for processing. After the low-frequency baseband signal is processed by the baseband processor, it is passed to the application processor. The application processor outputs a sound signal through an audio device (not limited to a speaker 170A, a receiver 170B, etc.), or displays an image or video through a display screen 194. In some embodiments, the modem processor may be an independent device. In other embodiments, the modem processor may be independent of the processor 110 and be set in the same device as the RF module 150 or other functional modules.

[0114] The communication module 160 can provide wireless communication solutions including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared (IR), etc., which are applied to the terminal device 102. The communication module 160 can be one or more devices integrating at least one communication processing module. The communication module 160 receives electromagnetic waves via the antenna 2, modulates the frequency of the electromagnetic wave signal and performs filtering, and sends the processed signal to the processor 110. The communication module 160 can also receive the signal to be sent from the processor 110, modulate the frequency of it, amplify it, and convert it into electromagnetic waves for radiation through the antenna 2.

[0115] In some embodiments, the antenna 1 of the terminal device 102 is coupled to the radio frequency module 150, and the antenna 2 is coupled to the communication module 160, so that the terminal device 102 can communicate with the network and other devices through wireless communication technology. The wireless communication technology may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), wideband code division multiple access (WCDMA), time-division code division multiple access (TD-SCDMA), long term evolution (LTE), BT, GNSS, WLAN, NFC, FM, and / or IR technology. The GNSS may include a global positioning system (GPS), a global navigation satellite system (GLONASS), a Beidou navigation satellite system (BDS), a quasi-zenith satellite system (QZSS) and / or a satellite based augmentation system (SBAS).

[0116] The terminal device 102 implements the display function through a GPU, a display screen 194, and an application processor. The GPU is a microprocessor for image processing, which connects the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 110 may include one or more GPUs, which execute program instructions to generate or change display information.

[0117] The display screen 194 is used to display images, videos, etc. The display screen 194 includes a display panel. The display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode or an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), Miniled, MicroLed, Micro-oLed, a quantum dot light-emitting diode (QLED), etc. In some embodiments, the terminal device 102 may include 1 or N display screens 194, where N is a positive integer greater than 1.

[0118] The terminal device 102 can realize the shooting function through ISP, camera 193, video codec, GPU, display screen 194 and application processor.

[0119] ISP is used to process the data fed back by camera 193. For example, when taking a photo, the shutter is opened, and the light is transmitted to the camera photosensitive element through the lens. The light signal is converted into an electrical signal, and the camera photosensitive element transmits the electrical signal to ISP for processing and converts it into an image visible to the naked eye. ISP can also perform algorithm optimization on the noise, brightness, and skin color of the image. ISP can also optimize the exposure, color temperature and other parameters of the shooting scene. In some embodiments, ISP can be set in camera 193.

[0120] The camera 193 is used to capture still images or videos. The object generates an optical image through the lens and projects it onto the photosensitive element. The photosensitive element can be a charge coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the optical signal into an electrical signal, and then passes the electrical signal to the ISP to be converted into a digital image signal. The ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into an image signal in a standard RGB, YUV or other format. In some embodiments, the terminal device 102 may include 1 or N cameras 193, where N is a positive integer greater than 1.

[0121] The digital signal processor is used to process digital signals, and can process not only digital image signals but also other digital signals. For example, when the terminal device 102 selects a frequency point, the digital signal processor is used to perform Fourier transform on the frequency point energy.

[0122] Video codecs are used to compress or decompress digital videos. The terminal device 102 may support one or more video codecs. Thus, the terminal device 102 may play or record videos in a variety of coding formats, such as Moving Picture Experts Group (MPEG) 1, MPEG2, MPEG3, MPEG4, etc.

[0123] NPU is a neural network (NN) computing processor. By drawing on the structure of biological neural networks, such as the transmission mode between neurons in the human brain, it can quickly process input information and can also continuously self-learn. Through NPU, applications such as intelligent cognition of the terminal device 102 can be realized, such as image recognition, face recognition, voice recognition, text understanding, etc.

[0124] The external memory interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the terminal device 102. The external memory card communicates with the processor 110 through the external memory interface 120 to implement a data storage function. For example, files such as music and videos are stored in the external memory card.

[0125] The internal memory 121 can be used to store computer executable program codes, which include instructions. The processor 110 executes various functional applications and data processing of the terminal device 102 by running the instructions stored in the internal memory 121. The internal memory 121 may include a program storage area and a data storage area. Among them, the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc. The data storage area may store data created during the use of the terminal device 102 (such as audio data, a phone book, etc.), etc. In addition, the internal memory 121 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, a universal flash storage (UFS), etc.

[0126] The terminal device 102 can implement audio functions such as music playing and recording through the audio module 170, the speaker 170A, the receiver 170B, the microphone 170C, the headphone interface 170D, and the application processor.

[0127] The audio module 170 is used to convert digital audio information into analog audio signal output, and is also used to convert analog audio input into digital audio signals. The audio module 170 can also be used to encode and decode audio signals. In some embodiments, the audio module 170 can be arranged in the processor 110, or some functional modules of the audio module 170 can be arranged in the processor 110.

[0128] The speaker 170A, also called a "speaker", is used to convert an audio electrical signal into a sound signal. The terminal device 102 can listen to music or listen to a hands-free call through the speaker 170A.

[0129] The receiver 170B, also called a "handset", is used to convert audio electrical signals into sound signals. When the terminal device 102 receives a call or voice message, the voice can be received by placing the receiver 170B close to the ear.

[0130] Microphone 170C, also called "microphone" or "microphone", is used to convert sound signals into electrical signals. When making a call or sending a voice message, the user can speak by putting their mouth close to the microphone 170C to input the sound signal into the microphone 170C. The terminal device 102 can be provided with at least one microphone 170C. In other embodiments, the terminal device 102 can be provided with two microphones 170C, which can not only collect sound signals but also realize noise reduction function. In other embodiments, the terminal device 102 can also be provided with three, four or more microphones 170C to collect sound signals, reduce noise, identify the sound source, realize directional recording function, etc.

[0131] The earphone interface 170D is used to connect a wired earphone and can be a USB interface 130 or a 3.5 mm open mobile terminal platform (OMTP) standard interface or a cellular telecommunications industry association of the USA (CTIA) standard interface.

[0132] The pressure sensor 180A is used to sense the pressure signal and can convert the pressure signal into an electrical signal. In some embodiments, the pressure sensor 180A can be set on the display screen 194. There are many types of pressure sensors 180A, such as resistive pressure sensors, inductive pressure sensors, capacitive pressure sensors, etc. A capacitive pressure sensor can be a parallel plate including at least two conductive materials. When a force acts on the pressure sensor 180A, the capacitance between the electrodes changes. The terminal device 102 determines the intensity of the pressure based on the change in capacitance. When a touch operation acts on the display screen 194, the terminal device 102 detects the intensity of the touch operation based on the pressure sensor 180A. The terminal device 102 can also calculate the position of the touch based on the detection signal of the pressure sensor 180A.

[0133] The gyroscope sensor 180B can be used to determine the motion posture of the terminal device 102. In some embodiments, the angular velocity of the terminal device 102 around three axes (i.e., x, y, and z axes) can be determined by the gyroscope sensor 180B. The gyroscope sensor 180B can be used for anti-shake shooting. For example, when the shutter is pressed, the gyroscope sensor 180B detects the angle of the terminal device 102 shaking, calculates the distance that the lens module needs to compensate based on the angle, and allows the lens to offset the shaking of the terminal device 102 through reverse movement to achieve anti-shake. The gyroscope sensor 180B can also be used for navigation and somatosensory game scenes.

[0134] The air pressure sensor 180C is used to measure air pressure. In some embodiments, the terminal device 102 calculates the altitude through the air pressure value measured by the air pressure sensor 180C to assist positioning and navigation.

[0135] The magnetic sensor 180D includes a Hall sensor. The terminal device 102 can use the magnetic sensor 180D to detect the opening and closing of the flip leather case. In some embodiments, when the terminal device 102 is a flip phone, the terminal device 102 can detect the opening and closing of the flip cover according to the magnetic sensor 180D. Then, according to the detected opening and closing state of the leather case or the opening and closing state of the flip cover, the flip cover automatic unlocking and other features are set.

[0136] The acceleration sensor 180E can detect the magnitude of the acceleration of the terminal device 102 in various directions (generally three axes). When the terminal device 102 is stationary, the magnitude and direction of gravity can be detected. It can also be used to identify the posture of the electronic device and is applied to applications such as horizontal and vertical screen switching and pedometers.

[0137] The distance sensor 180F is used to measure the distance. The terminal device 102 can measure the distance by infrared or laser. In some embodiments, when shooting a scene, the terminal device 102 can use the distance sensor 180F to measure the distance to achieve fast focusing.

[0138] The proximity light sensor 180G may include, for example, a light emitting diode (LED) and a light detector, such as a photodiode. The light emitting diode may be an infrared light emitting diode. The terminal device 102 emits infrared light outward through the light emitting diode. The terminal device 102 uses a photodiode to detect infrared reflected light from nearby objects. When sufficient reflected light is detected, it can be determined that there is an object near the terminal device 102. When insufficient reflected light is detected, the terminal device 102 can determine that there is no object near the terminal device 102. The terminal device 102 can use the proximity light sensor 180G to detect that the user holds the terminal device 102 close to the ear to talk, so as to automatically turn off the screen to save power. The proximity light sensor 180G can also be used in leather case mode and pocket mode to automatically unlock and lock the screen.

[0139] The ambient light sensor 180L is used to sense the ambient light brightness. The terminal device 102 can adaptively adjust the brightness of the display screen 194 according to the perceived ambient light brightness. The ambient light sensor 180L can also be used to automatically adjust the white balance when taking pictures. The ambient light sensor 180L can also cooperate with the proximity light sensor 180G to detect whether the terminal device 102 is in a pocket to prevent accidental touch.

[0140] The fingerprint sensor 180H is used to collect fingerprints. The terminal device 102 can use the collected fingerprint characteristics to achieve fingerprint unlocking, access application locks, fingerprint photography, fingerprint answering calls, etc.

[0141] The temperature sensor 180J is used to detect temperature. In some embodiments, the terminal device 102 uses the temperature detected by the temperature sensor 180J to execute a temperature processing strategy. For example, when the temperature reported by the temperature sensor 180J exceeds a threshold, the terminal device 102 reduces the performance of the processor located near the temperature sensor 180J to reduce power consumption and implement thermal protection. In other embodiments, when the temperature is lower than another threshold, the terminal device 102 heats the battery 142 to avoid abnormal shutdown of the terminal device 102 due to low temperature. In some other embodiments, when the temperature is lower than another threshold, the terminal device 102 performs a boost on the output voltage of the battery 142 to avoid abnormal shutdown caused by low temperature.

[0142] The touch sensor 180K is also called a "touch panel". The touch sensor 180K can be set on the display screen 194, and the touch sensor 180K and the display screen 194 form a touch screen, also called a "touch screen". The touch sensor 180K is used to detect touch operations acting on or near it. The touch sensor can pass the detected touch operation to the application processor to determine the type of touch event. Visual output related to the touch operation can be provided through the display screen 194. In other embodiments, the touch sensor 180K can also be set on the surface of the terminal device 102, which is different from the position of the display screen 194.

[0143] The bone conduction sensor 180M can obtain a vibration signal. In some embodiments, the bone conduction sensor 180M can obtain a vibration signal of a vibrating bone block of the vocal part of the human body. The bone conduction sensor 180M can also contact the human pulse to receive a blood pressure beat signal. In some embodiments, the bone conduction sensor 180M can also be set in an earphone and combined into a bone conduction earphone. The audio module 170 can parse out a voice signal based on the vibration signal of the vibrating bone block of the vocal part obtained by the bone conduction sensor 180M to realize a voice function. The application processor can parse the heart rate information based on the blood pressure beat signal obtained by the bone conduction sensor 180M to realize a heart rate detection function.

[0144] The key 190 includes a power key, a volume key, etc. The key 190 may be a mechanical key or a touch key. The terminal device 102 may receive key input and generate key signal input related to user settings and function control of the terminal device 102.

[0145] Motor 191 can generate vibration prompts. Motor 191 can be used for incoming call vibration prompts, and can also be used for touch vibration feedback. For example, touch operations acting on different applications (such as taking pictures, audio playback, etc.) can correspond to different vibration feedback effects. For touch operations acting on different areas of the display screen 194, motor 191 can also correspond to different vibration feedback effects. Different application scenarios (for example: time reminders, receiving messages, alarm clocks, games, etc.) can also correspond to different vibration feedback effects. The touch vibration feedback effect can also support customization.

[0146] Indicator 192 may be an indicator light, which may be used to indicate charging status, power changes, messages, missed calls, notifications, etc.

[0147] The SIM card interface 195 is used to connect a SIM card. The SIM card can be connected to and separated from the terminal device 102 by inserting it into the SIM card interface 195 or pulling it out from the SIM card interface 195. The terminal device 102 can support 1 or N SIM card interfaces, where N is a positive integer greater than 1. The SIM card interface 195 can support Nano SIM cards, Micro SIM cards, SIM cards, and the like. Multiple cards can be inserted into the same SIM card interface 195 at the same time. The types of the multiple cards can be the same or different. The SIM card interface 195 can also be compatible with different types of SIM cards. The SIM card interface 195 can also be compatible with external memory cards. The terminal device 102 interacts with the network through the SIM card to implement functions such as calls and data communications. In some embodiments, the terminal device 102 uses an eSIM, i.e., an embedded SIM card. The eSIM card can be embedded in the terminal device 102 and cannot be separated from the terminal device 102.

[0148] The following will specifically introduce the dangerous scene warning method provided by the embodiment of the present application in conjunction with the accompanying drawings. In the following embodiments, smart glasses are used as the wearable device 101, and the paired smart device of the smart glasses is a mobile phone.

[0149] In addition, in the embodiment of the present application, when the smart glasses are not connected to other smart devices, the user group category and the user's scene can be judged based on the data collected by the smart glasses themselves. When the smart glasses are connected to other smart devices, the smart glasses can be integrated with other smart devices to form a network, that is, the data collected by other smart devices can be combined with the data collected by themselves, and then the user group category and whether they are in a dangerous scene can be judged more accurately. In other words, smart glasses can undertake all or part of the data processing work of other smart devices, and the embodiment of the present application does not limit the division of labor between smart glasses and other smart devices.

[0150] At present, some smart devices have the function of detecting the user's physical data and environmental information and issuing danger alarms. Smart devices use the above functions to track the user's health status and determine whether the user is in a dangerous situation. If the user is in danger, the alarm will be issued. For example, the sensor function of the smart device can be used to monitor the user's environmental information, and the alarm will be issued immediately when the user is detected to be in danger.

[0151] However, when danger occurs, simply taking advantage of the alarm function and waiting for rescue cannot avoid the danger. After the alarm is raised, the user cannot escape danger immediately, which will cause the user to continue to be harmed. In addition, the user danger judgment standard is single and does not apply to all user groups. For example, for children, crossing the road without an adult is a dangerous scene, but at this time, the physiological information collected by the smart device is normal, and the smart device will not alarm. For adults, crossing the road in compliance with traffic rules can not be regarded as a dangerous scene.

[0152] Therefore, an embodiment of the present application provides a dangerous scene warning method, in which the user group category is matched according to the user information in the smart glasses, and a plurality of dangerous scenes are pre-set according to each user group category. After the user uses the smart glasses, the smart glasses determine the user group category to which the user belongs and whether the user is in the dangerous scene corresponding to the user group category based on the user information collected by one or more smart devices used by the user. When the user is in a dangerous scene, self-rescue guidance is provided to the user, and it is determined whether to call the police based on the dangerous scene. For example, when a child is crossing the road, voice or other means can be used to guide the child to cross the road without calling the police. When a child is at a fire scene, the smart glasses provide self-rescue guidance and call the police at the same time to defuse the danger. Through more accurate judgment of dangerous scenes and self-rescue guidance, users can escape from danger as soon as possible.

[0153] In a possible implementation, dangerous scenarios applicable to different user groups can be created based on user characteristic information. The user characteristic information includes any one or more of the following: user age, user health status, user gender, and user occupation.

[0154] Optionally, each user group category may correspond to an early warning mode, and when the smart device determines the early warning mode, it may automatically match the dangerous scenario in the early warning mode.

[0155] Referring to Table 1, illustratively, user groups are classified according to user age and / or health status and / or gender and / or occupation, each user group category corresponds to an early warning mode, and one or more danger scenarios are created accordingly.

[0156] Table 1

[0157]

[0158]

[0159] In Table 1 above, Mode 1 is a general mode, corresponding to basic danger scenarios, and is applicable to all users, that is, Mode 1 is a general mode, and this mode will be configured for each user. For example, when a user faces some natural disasters, it is not clear which method is the best way to save themselves. Or, even if some users have learned how to save themselves when facing some natural disasters, when the user is in a natural disaster scene, due to factors such as tension, they cannot take effective self-rescue methods in time, and still need certain self-rescue guidance to reduce the damage to the user. Therefore, the natural disaster danger scene can be set as the danger scene corresponding to Mode 1.

[0160] Since users of different age groups face different dangerous scenarios, user groups are classified according to their age, and the warning modes are divided into Mode 2 to Mode 4. Each age group can correspond to dangerous scenarios of different age groups, such as the dangerous scenarios for minors, dangerous scenarios for adults, and dangerous scenarios for the elderly in Table 1 above.

[0161] When a user suffers from a disease, some specific scenarios may be dangerous to the user. For example, an environment with poor air quality, such as an environment with a lot of pollen or dust, may be dangerous to asthma patients. Therefore, the user groups of sick people are divided into categories corresponding to disease risk scenarios, and mode 5 in the warning mode is set to disease warning mode. In this mode, different risk scenarios can be set according to different diseases.

[0162] When users are engaged in special occupations, such as those working in high-risk industries, they will be exposed to special dangerous scenes that ordinary people cannot be exposed to. Therefore, dangerous scenes for special occupations are set to avoid danger or help users escape danger as soon as possible. For example, animal trainers come into contact with a large number of animals in their daily work. There may be emergencies that stimulate animals to go crazy and cause danger to users. Therefore, user groups of special occupations are divided into categories corresponding to special occupational dangerous scenes, and mode 6 in the warning mode is set to special occupational warning mode. In this mode, different dangerous scenes can be set according to different special occupations.

[0163] Some special protection groups, such as women, pregnant women, and the disabled, may be dangerous in some special scenarios. Therefore, user group categories of special protection groups are divided, corresponding to the dangerous scenarios of special protection groups, and mode 7 in the early warning mode is set to the special protection group early warning mode. In this mode, different dangerous scenarios can be set according to different special protection groups.

[0164] Mode 8 is a custom mode, corresponding to custom danger scenarios, and is applicable to all users, that is, mode 8 will be configured for each user. If the user believes that there are other scenarios that may cause danger to the user in addition to all the current danger scenarios, the user can create different danger scenarios in mode 8 according to his or her own needs, thereby meeting the user's personalized needs.

[0165] The above-mentioned dangerous scenes include scenes that may potentially cause harm to users, such as dangerous animals and plants or crossroads. When the smart glasses determine that the user is in the potential dangerous scene, they will remind the user to pay attention to the danger and guide the user so that the user can resolve the danger. For example, guide the user not to touch or eat dangerous animals and plants, pay attention to passing vehicles at crossroads, etc. Dangerous scenes also include dangerous scenes that the user is already in, such as fire, heart attack, etc. When the smart glasses determine that the user is already in a dangerous scene, they will explain and demonstrate rescue and escape for the dangerous scene that has already occurred, and activate the self-rescue system to implement self-rescue guidance or seek help from the outside in appropriate scenes. For example, in the event of a fire, the smart glasses will guide the user to save themselves, plan escape routes and call the police for help; when a heart attack occurs, they will promptly implement self-rescue guidance and seek help from the outside to seize the "golden 3 minutes" rescue opportunity.

[0166] It should be noted that the above-mentioned user group classification method is only an exemplary description of the embodiment of the present application, and there may be other classification methods. For example, minors and their corresponding warning modes and dangerous scenes can be divided more finely, such as further dividing mode 2 into mode 2-1 and mode 2-2. Among them, mode 2-1 corresponds to "children under 10 years old", and the corresponding dangerous scene is the same as the dangerous scene corresponding to mode 2 in Table 1; mode 2-2 corresponds to "minors aged 10-18 years old". Since users in this age group already have certain danger identification and self-rescue capabilities, the dangerous scene after removing "crossroads" and "contact with strangers" in the dangerous scene corresponding to mode 2 in Table 1 can be used as the dangerous scene corresponding to mode 2-2. The embodiment of the present application does not make specific restrictions on this. In addition, the dangerous scene corresponding to each user group category and warning mode should not be limited to the dangerous scenes listed in Table 1. It can be understood that each user group category and warning mode should correspond to more dangerous scenes according to actual conditions.

[0167] Optionally, users can use smart devices such as mobile phones, computers, PADs, etc. that are connected to smart glasses and have editing functions to set warnings for smart glasses. Warning settings refer to related settings for warning functions in smart glasses, such as warning modes, dangerous scenarios, warning methods, etc. This application embodiment takes smart glasses connected to mobile phones and uses mobile phones to set warnings as an example. Smart glasses can be connected to mobile phones using Bluetooth, Wi-Fi, or USB interfaces. See Figure 5 As shown in (a), after the user selects the warning setting in the mobile phone screen display interface 501, the user can enter the warning setting page. When the switch 502 corresponding to the warning mode is turned on, the dangerous scene settings and basic settings will be displayed, and the basic settings such as dangerous scenes, self-rescue guidance mode, and sound can be further set. The user can choose to turn off the warning mode by turning off the switch 502. The warning mode can also be turned off by a quicker method such as voice. For example, when the smart glasses collect the user's voice words such as "turn off the warning mode" or "warning mode off", the smart glasses turn off the warning mode. When the warning mode is turned off, the warning setting interface is as follows: Figure 5 As shown in (b) in the figure, dangerous scenes and basic settings are hidden. For example, when a user visits a zoo, the animals in a certain venue may be preset by the smart glasses as more aggressive animals. Then, when the user watches, the smart glasses may frequently issue danger warnings. Therefore, at this time, the user can choose to turn off the warning function of the smart glasses so that the visit can be normal.

[0168] Optionally, users can set up dangerous scenarios in smart glasses. Figure 6 As shown in (a) of FIG. 1 , after the user turns on the early warning mode through the switch 502, he clicks on the dangerous scene setting to enter the following Figure 6 The dangerous scene setting interface shown in (b) in the figure will display all dangerous scenes, such as basic dangerous scenes, dangerous scenes for minors, dangerous scenes for adults, dangerous scenes for the elderly, dangerous scenes for diseases, etc. The smart glasses will judge the user group category and warning mode based on the user information and automatically turn on or off the corresponding dangerous scenes. The specific method is described below. Figure 6 As shown in (b), the current user is an elderly person, so the basic danger scene and the elderly danger scene are enabled by default. Of course, the user can also use the switch 502 to turn on or off the corresponding danger scene. For example, the user can click the switch 502 corresponding to the disease danger scene to set the corresponding disease danger scene. After that, the user can further set a specific scene, for example, click the basic danger scene to enter the following Figure 6 In the interface (c) shown in the basic danger scene setting interface, all specific scenes in the basic danger scene are turned on by default. The user can operate switch 502 to turn off danger scenes in the basic danger scene that do not often occur in the user's area, such as earthquakes, mudslides, and tsunamis.

[0169] Optional, see Figure 7 As shown in (a) in the figure, users can set some basic functions in the early warning mode. For example, after clicking the basic settings on the early warning setting interface, the user can enter the following Figure 7 In the interface shown in (b), you can set the self-help boot mode, sound, display, do not disturb mode, auxiliary functions, etc. For example, click on the self-help boot mode to enter the following Figure 7 In the interface shown in (c), different self-rescue guidance modes can be selected. For people of different age groups, the methods of self-rescue guidance are different. For example, for minors, it is necessary to use easy-to-understand voice or animation for guidance to prevent users from using wrong self-rescue methods due to not understanding the self-rescue guidance, which may cause losses. Or the smart glasses use projection demonstrations to directly guide users to learn operations and quickly save themselves. For the elderly, self-rescue guidance requires a slower speaking speed to give users more time to react and operate. Usually, smart glasses will automatically match the self-rescue guidance mode according to the early warning mode. For example, if mode 4 is applicable to the elderly, it will directly match the self-rescue guidance mode of the elderly mode. At this time, if the user feels that the current self-rescue guidance mode is inappropriate, he or she can change it by changing the self-rescue guidance mode in the following way: Figure 7 In the interface shown in (c) of FIG. 1 , operate switch 502 to select different self-help guidance modes. Figure 7Other basic settings for warnings can be made in the interface shown in (b) of FIG. For example, the Do Not Disturb mode can be set to set a corresponding time period without warning alarms. For another example, the auxiliary function settings can be used to set alarm contacts, LED flashing, etc. This embodiment of the application does not specifically limit this.

[0170] like Figure 4 As shown, a dangerous scene warning method provided by an embodiment of the present application is as follows:

[0171] S401, the smart glasses are turned on, user information is obtained, and user group categories are matched according to the user information.

[0172] In a possible implementation, after the smart glasses are turned on, they will automatically collect user information, which includes information collected by their own sensors and information collected by other user devices, and determine user characteristic information based on the user information. For example, the smart glasses can scan the user's face and collect user facial data, such as skin laxity, wrinkles, hairstyle, etc., and then determine user characteristic information such as user age and gender. For another example, the user's physical sign data detected by wearable devices such as smart bracelets are received to determine user characteristic information such as user age and whether the user has a disease. The user's physical sign data may be heart rate, respiration, blood pressure, etc. For example, when the user's heart rate data collected multiple times or periodically is abnormal, it can be determined that the user has heart disease. For another example, in some smart terminals, the user has entered the owner information, and the owner information may include age, medical history, etc. The smart glasses can directly determine the user characteristic information by directly receiving the owner information. For another example, through human-computer interaction, the user is guided to enter his own characteristic information, and the smart glasses obtain the user characteristic information. Among them, the human-computer interaction method includes voice guidance, such as voice asking for user information such as age, parsing the voice after the user answers to extract user information, and then matching the user group category; or image guidance, such as presenting a form containing user information collection, filling in and confirming by the user, and matching the user group category according to the user information filled in by the user. The embodiment of the application does not specifically limit the method of obtaining user information through human-computer interaction.

[0173] Optionally, the user can also enter user information such as age to more accurately match the user group category. Alternatively, the user can select some diseases that are not easy to judge based on the detected user data. Such as asthma, heart disease, etc. For example, after the smart device collects user data, the voice prompts the user to use a smart device such as a mobile phone, computer, PAD, etc. that is connected to the smart glasses and has editing functions to set basic information. After the voice prompts the user to set basic information, such as Figure 8As shown in (a) of FIG. 1 , the display interface of the mobile phone connected to the smart glasses displays a basic information setting interface, in which the user can enter basic information such as name and age. At this time, the smart device may not be able to determine whether the user has a disease based on the collected user information, so the switch 502 corresponding to whether the user has a disease is in the off state. At this time, if the user has a disease, the function can be turned on by operating the switch 502 to enter the following state: Figure 8 In the basic information setting interface shown in (b), the disease function is turned on in the interface, and different symptoms are displayed accordingly under this function. The user can turn on the corresponding symptoms by operating the switch 502 according to his own situation. If the user suffers from asthma, Figure 8 As shown in (b), the asthma function is turned on by operating the switch 502. By setting the basic information of the user, the smart device can further match the user group category, so that more dangerous scenes suitable for the user can be matched later.

[0174] Therefore, by combining the above-mentioned user information, the user characteristic information is judged, and then the user group category is matched, and then the corresponding dangerous scene can be matched. Among them, the user group category includes at least one or more of the following: minors, adults, elderly people, sick people, special occupational personnel, and special protection groups. For example, according to the user information, it is judged that user A is a minor with asthma. Then, referring to Table 1, the user group category of user A is minors and sick people. After that, the smart glasses can match the corresponding basic dangerous scenes, minors dangerous scenes, and disease dangerous scenes according to the user group category of user A.

[0175] S402. The smart glasses match dangerous scenarios according to user group categories.

[0176] As described above, referring to Table 1, the smart glasses are matched to one or more corresponding dangerous scenarios according to the user group category.

[0177] In a possible implementation, after the smart device determines the user group category based on the user information, it can automatically match one or more corresponding dangerous scenes directly based on the user group category, and perform subsequent dangerous scene detection and warning for the user based on the matched dangerous scenes.

[0178] In a possible implementation, after the smart device determines the user group category based on the user information, it can automatically match one or more corresponding dangerous scenarios directly based on the user group category. Afterwards, the user can be prompted by voice to make relevant warning settings or the user can make relevant warning settings by himself. Figure 5-Figure 7 The user's selection shown determines the final one or more dangerous scenarios and early warning guidance mode and other information.

[0179] Optionally, some diseases that are not easy to judge based on the detected user information can be selected by the user. Such as asthma, heart disease, etc. For example, after the smart device determines the user group category based on the user information, the voice prompts the user to set the relevant disease risk scene. At this time, see Fig. 9 As shown in (a) of FIG. 1 , the smart device connected to the smart glasses directly enters the dangerous scene setting interface, and then the user can directly turn on the disease warning mode by operating the switch 502 on the interface. After turning it on, the user can click on the disease danger scene to enter the dangerous scene. Fig. 9 In the interface shown in (b), in the disease risk scenario setting interface, the corresponding disease is selected by operating the switch 502, and the corresponding risk scenario can be selected by clicking the corresponding disease. Fig. 9 As shown in (b) of FIG. 5 , if the user suffers from asthma, the user can choose to turn on the asthma danger scene by operating the switch 502 according to his or her own situation. Afterwards, the user can further set the asthma danger scene, for example, after clicking on asthma, the user can enter the following Fig. 9 In the interface (c) of FIG. 1 , in the asthma dangerous scene setting interface, all specific scenes in the asthma dangerous scene are turned on by default, and the asthma dangerous scene may include poor air quality, pollen, dust, dense crowds, etc. The user can operate switch 502 to turn off the dangerous scenes in the asthma dangerous scene, such as pollen and dust, which are not often seen in the user's area. In the above manner, more dangerous scenes that meet the user's situation can be matched more accurately to prevent the occurrence of danger, and timely self-help can be achieved after the danger occurs.

[0180] In a possible implementation, after the smart device matches one or more first danger scenarios according to the user group category, it prompts the user to create a customized second danger scenario according to his or her own needs, so that the danger scenario corresponding to the user finally includes the first danger scenario and the second danger scenario. Fig.10 The interface shown in the figure is used to customize the second dangerous scenario setting. Fig.10 As shown in (a) of FIG. 1 , in the dangerous scene setting interface, the user can directly turn on the customized dangerous scene through the switch 502, and enter the customized dangerous scene by clicking on the customized dangerous scene. Fig.10 Alternatively, after the smart device matches a certain dangerous scene for the user according to the user group category, the user can then customize the dangerous scene settings in the dangerous scene setting interface. Fig.10 As shown in (b) of FIG. 1 , the smart device matches a dangerous scene for minors for the user. In the corresponding setting interface, the user can turn on the custom dangerous scene by switching on switch 502 and enter the custom dangerous scene by clicking on the custom dangerous scene. Fig.10The customized dangerous scene setting interface shown in (c) is shown in FIG. Fig.10 As shown in (c) in the figure, users can create custom dangerous scenes by clicking the "New" button. Assuming that user A is a minor and lives on the 19th floor, he is a high-rise resident. When user A approaches the window, there is a risk of falling from a high altitude. In this way, scene 1 is created as the "stay away from the window" dangerous scene. Keywords can be created for the scene to facilitate the smart device to determine the dangerous scene. For example, the keywords can be set to "window", "distance 1 meter", etc., that is, when the distance between user A and the windowsill is less than 1 meter, the smart glasses will start the danger warning. The addition of the keyword can be user text or voice input, and can also be a keyword automatically matched by the smart device. After that, the user can also add dangerous scene pictures or images to enable the smart device to more accurately identify the created custom dangerous scene. And the added dangerous scene pictures or images can be used to train the smart device so that the subsequent smart device can accurately identify similar dangerous scenes. The specific training method is described in the modeling section below. After the setting is completed, the user saves the created dangerous scene by clicking the "Save" button.

[0181] Optionally, after obtaining the newly created dangerous scene, the smart glasses can add it to the server and share it. Similarly, when other users also want to create similar dangerous scenes, after entering the scene name, the smart device can automatically match keywords and images from the server and synchronize them to local use. For example, if you enter similar scene names such as "stay away from windows" and "windows", the corresponding keywords and images can be automatically matched. Alternatively, a preset threshold can be set. When the number of users who create a certain dangerous scene exceeds the preset threshold, the dangerous scene is added to the dangerous scenes corresponding to the corresponding user group category, simplifying the user creation process and improving the user experience. For example, add the dangerous scene of staying away from the window to the dangerous scene for minors.

[0182] In another possible implementation, the smart glasses match the warning mode according to the user group category, and the warning mode includes a first warning mode and at least one second warning mode. Among them, the first warning mode corresponds to all users, and the second warning mode corresponds to the user group category. Match one or more dangerous scenes according to the warning mode, and the dangerous scenes include: a first dangerous scene corresponding to the first warning mode and a second dangerous scene corresponding to the second warning mode. That is, referring to Table 1, the first warning mode is mode 1, and the second warning mode is mode 2-mode 7. The first dangerous scene is a basic dangerous scene, and the second dangerous scene is a dangerous scene for minors, a dangerous scene for adults, a dangerous scene for the elderly, a dangerous scene for diseases, a dangerous scene for special occupations, and a dangerous scene for special protection groups. At this time, after the smart glasses match the warning mode, they can directly match one or more corresponding dangerous scenes according to the warning mode.

[0183] In another possible implementation, after the smart glasses are turned on, a direct voice prompt can be given to the user to use a smart device connected to the smart glasses and having an editing function, such as a mobile phone, computer, PAD, etc. Figures 5 to 10 That is, it is not necessary to perform the above step S401, and the final one or more dangerous scenes are directly determined according to the dangerous scenes selected and / or created by the user, and the user can directly select the warning guidance mode and other information.

[0184] S403, the smart glasses obtain environmental information and determine whether the user is in a dangerous scene. If the user is in a dangerous scene, execute step S404, if the user is not in a dangerous scene, execute step S405.

[0185] Optionally, the smart glasses can determine whether the user is in a dangerous scene based on the user information collected by the smart glasses. The smart glasses can also determine whether the user is in a dangerous scene by combining the user information collected by other smart devices (such as mobile phones). Alternatively, the smart glasses send the collected user information to other smart devices, and the other smart devices judge whether the user is currently in a dangerous scene and then feed back to the smart glasses. This embodiment of the application does not specifically limit this.

[0186] In a possible implementation, the environmental image information of the scene where the current user is located can be collected and analyzed by smart glasses. Exemplarily, the shape features of the target object appearing in the environmental image information are analyzed to determine whether the user is in a dangerous scene. For example, when the smart glasses collect an image containing poisonous plant fruits, it is determined that the user is in a dangerous scene of dangerous animals and plants in the basic dangerous scene, and then step S404 is executed to prevent the user from accidentally touching or eating. For another example, when the smart glasses determine that the user group category is the elderly, the smart glasses determine that the user is preparing to take medicine by analyzing the collected environmental image information, and determine whether the current medicine is a pre-configured symptomatic medicine based on the image information of the medicine. If it is determined to be a non-symptomatic medicine, it is determined that the user is in a dangerous scene of drug use in a dangerous scene for the elderly.

[0187] Optionally, smart glasses can combine the user's vital sign data collected by smart devices (such as smart bracelets) to judge the user's current physical condition to determine whether the user is in a dangerous situation. For example, smart glasses can collect user pupil data. When the user's pupil contracts rapidly, it indicates that the user may be frightened or have a sudden illness; when the user's pupil data is not collected within a preset time period, it indicates that the user may have fainted. At this time, combined with the collection of user heart rate and other data by the smart bracelet, it is more accurate to judge whether the user has a sudden illness.

[0188] Optionally, the smart glasses can combine the ambient audio information collected by the smart device to determine whether the user is in a dangerous scene. Exemplarily, when the user is a child, that is, a minor in the corresponding user group category. First, the smart glasses will store the facial data of acquaintances, and then determine that the user is in contact with people through the collected sound data and image data. And through face recognition, it is confirmed that the facial data of the object currently in contact with the user is not the stored data, and then it is determined that the current user is in contact with a stranger. Therefore, a danger warning is issued to ensure the safety of the user. Exemplarily, some sensitive words can be pre-configured. For example, when the user is an elderly person in the user group category, the data collected by the smart glasses shows that the user is on the phone, and through voiceprint recognition, it is determined that the user is talking to a stranger. When some words such as "transfer" and "amount" are collected, it indicates that the user is in a fraud risk scene in an elderly dangerous scene.

[0189] Optionally, the smart glasses can combine the information detected by the environmental sensors of the smart devices to determine whether the user is in a dangerous scene. The information detected by the environmental sensors includes any one or more of the following: air humidity, ambient temperature, ambient light, ambient odor, ambient sound, and atmospheric pressure. For example, the environmental sensor detects that the air humidity is gradually increasing at this time, and the smart glasses collect environmental image information to determine that the user is playing outdoors at the foot of the mountain. Combined with the above environmental information, the smart glasses can infer the possibility of rainfall, as well as the possibility of landslides or mud-rock flows. And then determine whether the user is currently in a dangerous scene.

[0190] Optionally, smart glasses can combine the location or speed data collected by smart devices to determine whether the user is in a dangerous situation. For example, smart glasses can combine with the mobile phone positioning device to determine the user's current location, such as whether it is located at a dangerous section of the road such as an intersection. Or, if the smart glasses determine that the user is driving a vehicle, combined with the location information, to determine whether the user is driving in a dangerous section of the road. For another example, when the smart glasses determine that the user is driving a vehicle, they can combine with the speed sensor of the mobile phone to determine whether the user is speeding, etc.

[0191] In one possible implementation, a danger level can be configured for dangerous scenarios. For example, in dangerous scenarios for adults, speeding is a level 3 dangerous scenario, high-speed driving on dangerous roads is a level 2 dangerous scenario, and high-speed driving on dangerous roads in rainy and snowy weather is a level 1 dangerous scenario. The danger level is divided according to the potential danger of one or more dangerous scenarios to the user, and different warning methods are adopted for different levels of dangerous scenarios. Then, based on the data collected by the smart glasses and the collected environmental data, it is determined which level of dangerous scenario the user is in, so that different warning methods can be adopted.

[0192] In a possible implementation, smart glasses can model and train dangerous scenes based on dangerous scenes that users often find themselves in. For example, user A is a minor. Assuming that user A passes through a crowded intersection on his way to and from school every day, user A's smart glasses will collect images of the intersection, and through artificial intelligence learning, statistically analyze the traffic light duration, road width, traffic flow and vehicle speed of the intersection, and establish a model based on the average passing speed of user A, giving the safe and dangerous range of user A passing through the intersection, and inputting it into the dangerous scene training model corresponding to the intersection in user A's smart glasses, which is used to train the dangerous scene of the intersection in the dangerous scene of minors for user A, and then output the trained dangerous scene of the intersection, so that user A's smart glasses can make a more accurate judgment and confirmation of the scene. For example, when user A is about to enter the intersection, combined with the current real-time green light duration and the remaining passing distance (such as when the remaining time of the green light is less than 10 seconds, the road width is greater than 20 meters, and the nearest car distance is less than 50 meters), it is finally identified whether the current passage is in a dangerous scene, and reminds user A to pass carefully or stop passing. Furthermore, since the environment in which user A is located may change, for example, when crossing an intersection, the traffic light may be broken or there may be a power outage, it is necessary to make a prediction based on the data previously trained on the dangerous scenario modeling to increase the recognition accuracy and safety rate.

[0193] For another example, user B is also a minor. Assuming that user B passes by a small river on the way to and from school every day, user B's smart glasses will collect images of the river, and through artificial intelligence learning, statistically analyze the speed of the water flow, the height of the water surface, the weather conditions, etc., as well as the average speed or time data of user B passing through the small river, and input them into the dangerous scene training model corresponding to drowning in user B's smart glasses, which is used to train the drowning danger scene in the dangerous scene for user B's minors, and then output the trained drowning danger scene, which can enable user B's smart glasses to make more accurate judgments and confirmations on the scene. For example, on a rainy day, if the river water is higher than user B's knees, user B is considered to be in a dangerous scene, and is reminded to retreat or seek help from the surrounding area.

[0194] It can be seen that for different users in the same user group category, the dangerous scenes they often encounter may also be different. Therefore, it is necessary to conduct modeling training for specific dangerous scenes for users, and continuously improve and update the dangerous scene data, so that smart glasses can more accurately issue danger warnings and help users avoid danger or save themselves in time. Among them, the specific modeling training algorithm can be referred to the prior art, and the embodiments of this application will not be specifically elaborated.

[0195] S404: If the user is in a dangerous situation, the smart glasses match the warning method and start the warning.

[0196] In one possible implementation, the warning method includes any one or more of the following: warning reminders, self-rescue knowledge playback, escape guidance, broadcasting for help, and alarm rescue. Among them, the warning reminder may include a voice reminder, such as a voice playback of "Please note, you are currently in a certain dangerous scene" or a single-syllable warning, such as a "beep! beep! beep!" sound, etc., and may also be a flashing light or a vibration, etc. The self-rescue knowledge playback is a voice playback of pre-configured self-rescue knowledge for different dangerous scenes. For example, fire self-rescue knowledge corresponding to a fire scene, etc. You can also use the virtual display or lenses of smart glasses to play text or animation self-rescue knowledge, such as Fig.11 As shown in FIG. 1 , the virtual display of smart glasses is used to play the animated self-rescue knowledge in fire, so that users can learn how to save themselves in fire, such as taking a low posture or crawling to escape. It is also possible to use a mobile phone or other smart device with display function connected to the smart glasses to play text or animated self-rescue knowledge, such as Fig.12 As shown in the figure, a mobile phone connected to smart glasses plays an animation of self-rescue knowledge in fire. Escape guidance can be an escape route guidance determined by smart glasses in combination with the global positioning system (GPS) in smart devices such as mobile phones, or an escape route provided to users in combination with indoor escape evacuation maps, so as to help users escape from dangerous scenes as soon as possible. Fig.13 The figure shows a schematic diagram of using a virtual display of smart glasses to display an indoor escape route. Fig.14 The figure shows a schematic diagram of using a mobile phone connected to smart glasses to display an indoor escape route. The user can escape from danger as soon as possible according to the escape route. Broadcasting for help means that the smart glasses broadcast a distress message to inform passers-by that the user is in a dangerous scene and needs help. For example, when the smart glasses determine that the user is in a dangerous scene with a stranger in a minor's scene, when it is determined based on the current environmental information that the stranger has a forced contact action, the user can ask for help from passers-by through broadcasting to get rid of the dangerous stranger and prevent harm. Alarm rescue means calling the police for help from the relevant departments or calling a pre-set contact number. For example, when the smart glasses determine that the user is in a fire danger scene in a natural disaster scene, they can automatically call the fire alarm to get rescue in time.

[0197] Optionally, different warning methods are matched for one or more dangerous scenes in which the user is in order to resolve the crisis to the maximum extent. For example, the smart glasses determine that the user matches the dangerous scene of the intersection in the dangerous scene, where the intersection section is a high-incidence section of traffic accidents. The smart glasses determine that no traffic accident has occurred at this time, then safety prevention propaganda such as self-rescue knowledge can be carried out to the user, so that the user can learn relevant knowledge to cope with the subsequent possible dangerous situations. For example, when the user encounters a traffic accident, the smart glasses can play self-rescue knowledge and escape guidance, and broadcast help to seek help from passers-by. At appropriate times, it is also necessary to call the police for rescue so as to get timely treatment. For another example, the smart glasses determine that the current air quality is poor, and the user is in a dangerous scene of an asthma patient in a dangerous scene of the disease. The smart glasses will issue a warning reminder to remind the user that the current scene is potentially dangerous to the user, and ask the user to stay away from the current scene as soon as possible. For another example, the smart glasses determine that the user is currently suffering from a heart attack through the collected data, and the smart glasses will immediately broadcast help and call the police for rescue, so as to achieve the "golden 3 minutes" self-rescue of myocardial infarction.

[0198] Optionally, when the user is in a dangerous scene with different danger levels, different warning methods can be matched. As shown in Table 2 below, the correspondence between the pre-configured danger level and the warning method can be stored in the smart glasses. Exemplarily, the danger level can be divided into 5 levels according to the potential danger of the dangerous scene to the user, and each danger level corresponds to one or more warning methods. For example, the danger level of the natural disaster danger scene is high, and the danger level of the natural disaster danger scene can be set to a higher level, such as level 1. When the user is in a dangerous scene with a higher level, a variety of warning methods are combined to ensure the safety of the user. For example, when the user is in a fire danger scene, the smart glasses will warn, guide escape, broadcast for help and alarm rescue, so that the user can get rescue and leave the fire scene as soon as possible. When the user is in a dangerous scene with less danger, a lower danger level can be set for it, such as level 5. At this time, only a warning reminder is needed to prevent the user from being injured. In this way, the dangerous scene is divided into danger levels according to the danger of the scene, and each danger level corresponds to one or more warning methods, so that the appropriate warning method can be quickly matched.

[0199] Table 2

[0200]

[0201] Optionally, the user can customize the danger level and warning method for the danger scene. The smart device can automatically match the danger level according to the current danger scene, and after the user modifies or confirms it, it matches the warning method according to the danger level determined by the user; or the smart device can display the danger level and warning method setting interface corresponding to each danger scene, on which the danger level and warning method of the current danger scene can be customized. For example, the user wants to set the danger level and warning method for the drowning danger scene. First, see Fig.15 As shown in (a) of FIG. 1 , the user opens and clicks on the dangerous scene for minors in the dangerous scene setting to enter the following Fig.15 In the dangerous scene setting interface for minors, open and click on the drowning danger scene, and then go to the following Fig.15 The smart device will automatically display the corresponding potential danger scenes (such as not drowning) and the danger scenes that have occurred (such as drowning) in the drowning danger scene setting interface. You can customize the danger level and warning method for each danger scene, such as Fig.15 As shown in (c) in the figure, for the card corresponding to the non-drowning danger scene, the smart device can automatically match the danger level, or the user can input or select the danger level as level 3. At this time, the smart device will automatically match the corresponding warning method. Refer to Table 2 above. When the danger level is level 3, the corresponding warning method is: warning reminder, self-rescue knowledge playback and escape guidance. The user can modify the warning method, input or select a new warning method, or delete some warning methods that the user considers unnecessary according to their own needs, such as Fig.15 As shown in (c) in the figure, for the warning mode of the non-drowning danger scene, the user chooses to delete the warning mode of escape guidance, but retains the warning mode of warning reminder and self-rescue knowledge playback. After the user completes the setting of each card in the danger scene, he can click the save button to save the current setting. After the smart glasses obtain the warning mode determined by the end user, they use the warning mode to warn the user.

[0202] In addition, if Fig.15 As shown in (c) in the figure, users can choose to close or delete different dangerous scenes included in certain dangerous scene categories. For example, based on the scene description and their own situation, if the user believes that the scope of scenes included in the non-drowning dangerous scene is too large and cannot protect themselves more completely, they can delete the non-drowning dangerous scene under the drowning dangerous scene and create a new dangerous scene card. Fig.15As shown in (d) in the figure, the non-drowning danger scene is divided into a potential drowning danger scene and an impending drowning danger scene, and the non-drowning danger scene is deleted. Through the new button, the potential drowning danger scene and the impending drowning danger scene are respectively established, the scene description is input or automatically matched, and the corresponding danger level and warning method are set. The scene description can be voice, text, picture, image, etc. Exemplarily, the potential drowning danger scene can be a user walking by the river, with a distance of 1 meter to 3 meters from the river; the impending drowning danger scene can be a user less than 1 meter away from the river and has entered the water. In order to prevent the user from needing to use a certain dangerous scene such as a non-drowning danger scene later, the user can choose not to delete the dangerous scene, but to close the dangerous scene so that it can be opened again when needed later. Alternatively, the user can also choose to create a dangerous scene first through the custom dangerous scene creation method in the above step S402, and then customize the corresponding danger level and warning method.

[0203] It should be noted that after the smart glasses start warning, the smart glasses can broadcast the corresponding content by voice. When the smart glasses are connected to a mobile phone, the mobile phone can also broadcast the voice. Or, when the smart glasses are connected to a Bluetooth headset, the Bluetooth headset can broadcast the voice, which is not specifically limited in the embodiments of the present application.

[0204] In addition, when the user leaves a dangerous scene or completes self-rescue in the current dangerous scene, the smart glasses return to step S403 and continue to match the scene where the user is located to determine whether the user is in a dangerous scene.

[0205] S405: If the user is not in a dangerous situation, return to step S403.

[0206] Specifically, the smart glasses collect user environment information in real time, including the user's environment image information and / or environment audio information and / or information detected by the environment sensor, etc., and match in real time whether the scene the user is currently in is a dangerous scene. If in a dangerous scene, select the warning mode and start the warning; if not in a dangerous scene, continue to collect user environment information and match the dangerous scene.

[0207] It can be seen that the dangerous scene warning method provided by the present application can divide different user groups into different user group categories and set different dangerous scenes accordingly, set corresponding self-rescue guidance measures for different dangerous scenes, and identify whether the user is in a dangerous scene through smart glasses, and then guide the user to save himself. Compared with the prior art, smart devices only provide detection functions or alarm functions, and cannot provide necessary crisis resolution and self-rescue services. In the embodiment of the present application, smart glasses can be used as an entry point, combined with other smart devices, to give play to the advantages of artificial intelligence, divide the work and cooperate, analyze and identify preset, sudden, and potential dangers, and issue warnings. Analyze and identify the scene in which the user is located, and then issue warnings and self-rescue guidance, maximize crisis resolution and escape, and improve user personal safety.

[0208] like Fig.16 As shown, the embodiment of the present application discloses a terminal device, including: one or more processors 1601; memory 1602; and one or more computer programs 1603. The above-mentioned devices can be connected through one or more communication buses 1604. Among them, the above-mentioned one or more computer programs 1603 are stored in the above-mentioned memory 1602 and are configured to be executed by the one or more processors 1601, and the one or more computer programs 1603 include instructions, and the above-mentioned instructions can be used to execute the various steps in the above-mentioned dangerous scene warning method embodiment.

[0209] Exemplarily, the processor 1601 may be Figure 2 The application processor 201 shown in the figure, the memory 1602 can be specifically Figure 2 Storage support 206 is shown.

[0210] The terminal device also includes a communication module 1605; a sensor 1606; the communication module 1606 can be specifically Figure 2 The short-distance processor 20 shown in the figure, the sensor 1606 can be specifically Figure 2 The sensor subsystem 212 is not limited in any way in the present embodiment. The sensor 1606 can be used to execute the steps involved in the above-mentioned dangerous scene early warning method such as detecting user feature data and environmental information.

[0211] Processor 1601 may be a processor or a controller, for example, a central processing unit (CPU), a GPU, a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor may also be a combination that implements a computing function, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0212] The communication module 1605 may be a transceiver, a transceiver circuit, an input / output device, or a communication interface, etc. For example, the communication module 1605 may specifically be a Bluetooth device, a Wi-Fi device, a peripheral interface, and the like.

[0213] The memory 1602 may include a high-speed random access memory, or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), or any other medium that can be used to carry or store desired program codes in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 1602 may exist independently and be connected to the processor via a communication bus 1604. The memory may also be integrated with the processor.

[0214] The present application also provides a chip system, such as Fig.17As shown, the chip system includes at least one processor 1701 and at least one interface circuit 1702. The processor 1701 and the interface circuit 1702 can be interconnected via lines. For example, the interface circuit 1702 can be used to receive signals from other devices (such as the memory of the terminal device 102). For another example, the interface circuit 1702 can be used to send signals to other devices (such as the processor 1701). Exemplarily, the interface circuit 1702 can read the instructions stored in the memory and send the instructions to the processor 1701. When the instructions are executed by the processor 1701, the terminal device can execute the various steps performed by the wearable device 101 in the above embodiment. Of course, the chip system can also include other discrete devices, which are not specifically limited in the embodiments of the present application.

[0215] An embodiment of the present application also provides a computer storage medium, in which computer instructions are stored. When the computer instructions are executed on a terminal device, the terminal device executes the above-mentioned related method steps to implement the dangerous scene warning method in the above-mentioned embodiment.

[0216] The embodiment of the present application also provides a computer program product. When the computer program product is run on a computer, the computer is caused to execute the above-mentioned related steps to implement the dangerous scene warning method in the above-mentioned embodiment.

[0217] In addition, an embodiment of the present application also provides a device, which may specifically be a component or a module, and the device may include a connected processor and a memory; wherein the memory is used to store computer-executable instructions, and when the device is running, the processor may execute the computer-executable instructions stored in the memory so that the device executes the dangerous scene warning method in the above-mentioned method embodiments.

[0218] Among them, the terminal device, computer storage medium, computer program product or chip provided in the embodiments of the present application are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0219] Through the description of the above implementation methods, technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0220] In the several embodiments provided in the present application, it should be understood that the disclosed method can be implemented in other ways. For example, the terminal device embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of modules or units, which can be electrical, mechanical or other forms.

[0221] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0222] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0223] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: flash memory, mobile hard disk, read-only memory, random access memory, disk or optical disk and other media that can store program instructions.

[0224] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A dangerous scene early warning method, characterized in that: The method comprises: Acquire user information, wherein the user information includes any one or more of the following: user facial information, user vital sign data, and information input by the user; Matching user group categories according to the user information, wherein the user group categories include any one or more of the following: minors, adults, elderly people, sick people, special occupational personnel, and special protection groups; Matching a dangerous scene set according to the user group category, wherein: If the user is a minor, the dangerous scenario includes any one or more of the following: drowning, electric shock, crossroads, contact with strangers, dangerous objects; If the user is an adult, the dangerous scenario includes any one or more of the following: dangerous driving, dangerous environment driving, dangerous road driving; If the user is an elderly person, the dangerous scenarios include any one or more of the following: drug use, diet, illness onset, fraud; If the user is a sick person, the dangerous scenes include any one or more of the following: dangerous scenes for asthma patients, dangerous scenes for heart patients; the dangerous scenes for asthma patients include any one or more of the following: poor air quality, pollen, dust, and crowded people; the dangerous scenes for heart patients include any one or more of the following: high-altitude playgrounds, strenuous exercise, mountain climbing, and altitude sickness; If the user is a person of special occupation, the dangerous scene includes any one or more of the following: mad animals, outdoor work, abnormal protective equipment; If the user is a special protection group, the dangerous scenarios include any one or more of the following: traveling alone at night, being followed by a stranger, a pregnant woman squatting for a longer time than a preset time, or a traffic density greater than a preset traffic density; The dangerous scene set includes one or more dangerous scenes matched by the user group category; Select one or more dangerous scenes from the dangerous scene set; Acquiring environmental information, and determining whether the user is in one or more dangerous scenarios according to the environmental information; If the user is in one or more dangerous scenarios, a warning is initiated by matching the warning mode.

2. The dangerous scene early warning method according to claim 1, characterized in that: The matching of user group categories according to the user information includes: Determine user characteristic information according to the user information; the user characteristic information includes any one or more of the following: age, health condition, gender, occupation; The user group category is matched according to the user characteristic information.

3. The dangerous scene early warning method according to claim 2, characterized in that: Matching the user group category according to the user characteristic information includes: The user group category is matched according to the user's age and / or health condition and / or gender and / or occupation.

4. The dangerous scene early warning method according to claim 1, characterized in that: Matching one or more dangerous scenarios according to the user group category includes: Match natural disaster danger scenes and dangerous animal and plant danger scenes for all users; the natural disaster danger scenes include any one or more of the following: fire, earthquake, mudslide, sandstorm, tsunami; the dangerous animal and plant danger scenes include any one or more of the following: aggressive animals, poisonous plants.

5. The dangerous scene early warning method according to claim 1, characterized in that: The matching of one or more dangerous scenarios according to the user group category includes: Matching an early warning mode according to the user group category; the early warning mode includes a first early warning mode and at least one second early warning mode; wherein the first early warning mode corresponds to all users, and the second early warning mode corresponds to the user group category; One or more danger scenarios are matched according to the early warning mode; the danger scenarios include: a first danger scenario corresponding to the first early warning mode and a second danger scenario corresponding to the second early warning mode.

6. The dangerous scene warning method according to any one of claims 1 to 3, characterized in that: The warning methods include any one or more of the following: warning reminder, self-rescue knowledge broadcast, escape guidance, broadcast for help, and alarm rescue.

7. The dangerous scene early warning method according to claim 6, characterized in that: If the user is in one or more dangerous scenarios, matching the warning mode to initiate the warning includes: Initiate an early warning based on matching the early warning method with the one or more dangerous scenarios; or, divide the danger levels according to the potential dangers of the one or more dangerous scenarios to the user, and initiate an early warning based on matching the early warning method with the danger levels; or, initiate an early warning based on matching the early warning method with the danger levels determined by the user; or, initiate an early warning based on the early warning method that matches the one or more dangerous scenarios determined by the user.

8. The dangerous scene early warning method according to claim 7, characterized in that: After obtaining the user information and matching the user group category according to the user information, the method includes: Prompt the user to select and determine the one or more dangerous scenarios; or, automatically match one or more dangerous scenarios according to the user group category; or, after automatically matching one or more dangerous scenarios according to the user group category, prompt the user to select and determine the one or more dangerous scenarios; or, prompt the user to create the one or more dangerous scenarios; or, after automatically matching one or more first dangerous scenarios according to the user group category, prompt the user to create one or more second dangerous scenarios, wherein the dangerous scenarios include the first dangerous scenarios and the second dangerous scenarios.

9. The dangerous scene early warning method according to claim 8, characterized in that: The environmental information includes the user's environmental image information and / or environmental audio information and / or information detected by environmental sensors; the information detected by the environmental sensors includes any one or more of the following: air humidity, ambient temperature, ambient light, ambient odor, ambient sound, and atmospheric pressure.

10. A terminal device, characterized in that: include: one or more processors; Memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory, and the one or more computer programs include instructions; when the instructions are executed by the terminal device, the terminal device executes: Acquire user information, wherein the user information includes any one or more of the following: user facial information, user vital sign data, and information input by the user; match user group categories according to the user information, wherein the user group categories include any one or more of the following: minors, adults, elderly people, sick people, special occupational personnel, and special protection groups; match a set of dangerous scenarios according to the user group categories, wherein if the user is a minor, the dangerous scenarios include any one or more of the following: drowning, electric shock, crossroads, contact with strangers, and dangerous objects; If the user is an adult, the dangerous scenario includes any one or more of the following: dangerous driving, dangerous environment driving, dangerous road driving; If the user is an elderly person, the dangerous scenarios include any one or more of the following: drug use, diet, illness onset, fraud; If the user is a sick person, the dangerous scenes include any one or more of the following: dangerous scenes for asthma patients, dangerous scenes for heart patients; the dangerous scenes for asthma patients include any one or more of the following: poor air quality, pollen, dust, and crowded people; the dangerous scenes for heart patients include any one or more of the following: high-altitude playgrounds, strenuous exercise, mountain climbing, and altitude sickness; If the user is a person of special occupation, the dangerous scene includes any one or more of the following: mad animals, outdoor work, abnormal protective equipment; If the user is a special protection group, the dangerous scenarios include any one or more of the following: traveling alone at night, being followed by a stranger, a pregnant woman squatting for a longer time than a preset time, or a traffic density greater than a preset traffic density; The dangerous scene set includes one or more dangerous scenes matched by the user group category; Obtain a dangerous scene setting, wherein the dangerous scene setting is to select one or more dangerous scenes from the dangerous scene set; obtain environmental information, and determine whether the user is in the one or more dangerous scenes based on the environmental information; if the user is in the one or more dangerous scenes, match the early warning method to initiate an early warning.

11. The terminal device according to claim 10, characterized in that: When the instruction is executed by the terminal device, the terminal device executes: Determine user characteristic information according to the user information; the user characteristic information includes any one or more of the following: age, health condition, gender, occupation; match the user group category according to the user characteristic information.

12. The terminal device according to any one of claims 10 or 11, characterized in that: When the instruction is executed by the terminal device, the terminal device executes: The user group category is matched according to the user's age and / or health condition and / or gender and / or occupation.

13. The terminal device according to claim 10, characterized in that: When the instruction is executed by the terminal device, the terminal device executes: Match natural disaster danger scenes and dangerous animal and plant danger scenes for all users; the natural disaster danger scenes include any one or more of the following: fire, earthquake, mudslide, sandstorm, tsunami; the dangerous animal and plant danger scenes include any one or more of the following: dangerous animals, poisonous plants.

14. The terminal device according to claim 10, characterized in that: When the instruction is executed by the terminal device, the terminal device executes: Matching an early warning mode according to the user group category; the early warning mode includes a first early warning mode and at least one second early warning mode; wherein the first early warning mode corresponds to all users, and the second early warning mode corresponds to the user group category; One or more danger scenarios are matched according to the early warning mode; the danger scenarios include: a first danger scenario corresponding to the first early warning mode and a second danger scenario corresponding to the second early warning mode.

15. The terminal device according to any one of claims 10 or 11, characterized in that: The warning methods include any one or more of the following: warning reminder, self-rescue knowledge broadcast, escape guidance, broadcast for help, and alarm rescue.

16. The terminal device according to claim 15, characterized in that: When the instruction is executed by the terminal device, the terminal device executes: Initiate an early warning according to the one or more dangerous scenarios matching the early warning method; or, classify the danger levels according to the potential dangers of the one or more dangerous scenarios to the user, and initiate an early warning according to the danger levels matching the early warning method; Or, starting the warning according to the danger level determined by the user and matching the warning mode; Or, the warning is initiated according to the warning method matched with the one or more dangerous scenarios determined by the user.

17. The terminal device according to claim 16, characterized in that: When the instruction is executed by the terminal device, the terminal device executes: Prompt the user to select and determine the one or more dangerous scenarios; or, automatically match one or more dangerous scenarios according to the user group category; or, after automatically matching one or more dangerous scenarios according to the user group category, prompt the user to select and determine the one or more dangerous scenarios; or, prompt the user to create the one or more dangerous scenarios; or, after automatically matching one or more first dangerous scenarios according to the user group category, prompt the user to create one or more second dangerous scenarios, wherein the dangerous scenarios include the first dangerous scenarios and the second dangerous scenarios.

18. The terminal device according to any one of claims 10 or 11, characterized in that: The environmental information includes the user's environmental image information and / or environmental audio information and / or information detected by environmental sensors; the information detected by the environmental sensors includes any one or more of the following: air humidity, ambient temperature, ambient light, ambient odor, ambient sound, and atmospheric pressure.

19. A computer storage medium, characterized in that: It includes computer instructions, which, when executed on a terminal device, enable the terminal device to execute the dangerous scene warning method as described in any one of claims 1-9.

20. A computer program product, characterized in that When the computer program product runs on a computer, the computer is enabled to execute the dangerous scene warning method as described in any one of claims 1 to 9.

21. A chip system, characterized in that: It includes at least one processor and at least one interface circuit, wherein the at least one interface circuit is used to perform transceiver functions and send instructions to the at least one processor. When the at least one processor executes the instructions, the at least one processor executes the dangerous scene warning method as described in any one of claims 1-9.

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