WO2019158108A1 - 智能冰箱的健康数据监控方法及智能冰箱 - Google Patents

智能冰箱的健康数据监控方法及智能冰箱 Download PDF

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Publication number
WO2019158108A1
WO2019158108A1 PCT/CN2019/075069 CN2019075069W WO2019158108A1 WO 2019158108 A1 WO2019158108 A1 WO 2019158108A1 CN 2019075069 W CN2019075069 W CN 2019075069W WO 2019158108 A1 WO2019158108 A1 WO 2019158108A1
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WIPO (PCT)
Prior art keywords
data
user
health
identity information
indicator
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Ceased
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PCT/CN2019/075069
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English (en)
French (fr)
Inventor
刘新宇
王恩杰
李鲁
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Beijing Jingdong Century Trading Co Ltd
Beijing Jingdong Shangke Information Technology Co Ltd
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Beijing Jingdong Century Trading Co Ltd
Beijing Jingdong Shangke Information Technology Co Ltd
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Publication of WO2019158108A1 publication Critical patent/WO2019158108A1/zh
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Ceased legal-status Critical Current

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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
    • F25D29/00—Arrangement or mounting of control or safety devices
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
    • F25D2500/00—Problems to be solved
    • F25D2500/06—Stock management

Definitions

  • the present disclosure relates to the field of smart home technology, and in particular to a health data monitoring method for a smart refrigerator and a smart refrigerator.
  • the smart refrigerator is used alone, and cannot interact with other intelligent terminals (such as a smart bracelet and a body fat scale, etc.), and can remind the user of the matters needing attention according to the data of the smart terminal.
  • other intelligent terminals such as a smart bracelet and a body fat scale, etc.
  • the smart refrigerator can simply recognize the items that the user inputs on the touch screen and then send the order to the shopping website.
  • the above smart refrigerator has the following drawbacks: on the one hand, it cannot be opened up with other applications or other smart devices, and cannot provide a more comprehensive service for the user (for example, may include automatic appointment of a hospital and registration, etc.); further, due to the inability to cooperate with other Apps or other smart devices are open, so they can't be combined with other apps or other smart devices to provide health monitoring for users.
  • the purpose of the present disclosure is to provide a health data monitoring method for a smart refrigerator and a smart refrigerator, which can overcome, at least to some extent, the smart refrigerator cannot be connected with other smart devices or applications due to limitations and defects of the related art. Users provide questions about health monitoring.
  • a method for monitoring health data of a smart refrigerator includes: receiving user indicator data sent by a user wearable device and/or test data sent by a body fat; identifying user identity information; and identifying the user Identity information, searching for user indicator data and/or test data corresponding to the user identity information; outputting the user indicator data and/or test data.
  • the health data monitoring method further includes: determining, according to the found user indicator data and/or the test data, the corresponding user indicator data and/or test data. Health advice data; output the health advice data.
  • the determining the health suggestion data corresponding to the found user indicator data and/or the test data comprises: searching for the indicator item according to the indicator item in the user indicator data
  • the data comparison table is recommended to obtain the suggestion data corresponding to the indicator item;
  • the suggestion data corresponding to the indicator item is aggregated to obtain the health suggestion data with the found user indicator data and/or the test data.
  • the outputting the user indicator data and/or the test data includes: generating user indicator data and/or test data variation curves within a specific time period of the user; User indicator data and/or test data curve.
  • the health suggestion data includes recipe suggestion data; wherein the health data monitoring method further comprises: searching for a recipe suggestion data and a food material data comparison table according to the recipe suggestion data, thereby determining Corresponding food material data; identifying the existing food materials in the refrigerator according to the image taken by the camera inside the refrigerator; determining the food to be added according to the determined food material data and the identified existing food materials; and displaying the food materials to be added.
  • the health data monitoring method further includes: searching for a transaction site through the Internet according to the food item selected by the user; if searching for the presence of the user-selected food item The trading site automatically issues a request to generate an order.
  • the health data monitoring method after receiving user indicator data sent by the user wearable device and/or test data sent by the body fat scale, the health data monitoring method further includes: transmitting to the user wearable device User indicator data, determining user identity information corresponding to the user indicator data according to a binding relationship between the user wearable device and the user identity information; and/or outputting the user identity information for the test data sent by the body fat scale And prompting the received user identity information as the user identity information corresponding to the test data.
  • identifying the user identity information includes: determining, by the face recognition, the user identity information according to a correspondence between the previously stored face and the user identity information.
  • the health data monitoring method further includes: capturing a user face image; identifying a skin health state from the user face image; and combining the received user with the recognized skin health state Indicator data and/or test data for skin health status, user metric data and/or test data, and a skin improvement recommendation checklist to obtain skin improvement recommendations.
  • the health suggestion data includes medical advice data; wherein the health data monitoring method further includes: receiving a confirmation of the medical advice data by the user; The Internet searches for the hospital site corresponding to the medical advice data; the medical request is automatically sent to the hospital site.
  • the health data monitoring method further includes: scanning a two-dimensional code of a specific food material through an external camera of the refrigerator; searching and searching through the Internet according to the food material corresponding to the two-dimensional code The transaction site corresponding to the food item; if a transaction site where the user-selected food item exists is found, a request for generating an order is automatically issued.
  • the health data monitoring method further includes: periodically scanning the inside of the refrigerator through a camera inside the refrigerator to determine whether there is newly added food; and if there is the newly added food, identifying The newly added food material; recording a time point at which the newly added food material is judged; comparing the time from the recorded time point with the shelf life corresponding to the identified food item; if the time from the recorded time point is greater than The shelf life, the reminder of the expiration of the ingredients is issued.
  • a smart refrigerator comprising: a receiver configured to receive user indicator data transmitted by a user wearable device and/or test data transmitted by a body fat scale; and an identification device configured to identify the user identity
  • the information processor is configured to search for user indicator data and/or test data corresponding to the user identity information according to the identified user identity information; and the output device is configured to output the user indicator data and/or the test data.
  • the processor is further configured to determine a health suggestion corresponding to the found user indicator data and/or test data according to the found user indicator data and/or test data.
  • Data; the output device is further configured to output the health suggestion data.
  • the determining the health suggestion data corresponding to the found user indicator data and/or the test data comprises: searching for the indicator item according to the indicator item in the user indicator data
  • the data comparison table is recommended to obtain the suggestion data corresponding to the indicator item;
  • the suggestion data corresponding to the indicator item is aggregated to obtain the health suggestion data with the found user indicator data and/or the test data.
  • the output device is further configured to generate user indicator data and/or test data variation curve within the specific time period of the user; wherein the smart refrigerator further includes: a display , configured to display the user indicator data and/or the test data curve.
  • the health suggestion data includes recipe suggestion data; the processor is further configured to search the recipe suggestion data and the food material data comparison table according to the recipe suggestion data, thereby determining corresponding food material data
  • the smart refrigerator further includes: a built-in camera disposed inside the smart refrigerator, configured to capture an image of the existing food material in the refrigerator; the processor is further configured to identify an existing one in the refrigerator according to the image of the existing food material
  • the foodstuff determines the foodstuff to be added according to the determined food material data and the identified existing foodstuff; the display is further configured to display the foodstuff to be added.
  • the processor is further configured to: search for a transaction site through the Internet according to the food selected by the user; automatically issue a request to generate an order if a transaction site where the user-selected food item exists is searched .
  • the processor is further configured to determine, with the user indicator data sent by the user wearable device, the user indicator data according to the binding relationship between the user wearable device and the user identity information.
  • the output device is further configured to output, for the test data sent by the body fat scale, a prompt for the user to input the user identity information, and use the received user identity information as the user identity information corresponding to the test data.
  • identifying the user identity information includes: determining, by the face recognition, the user identity information according to a correspondence between the previously stored face and the user identity information.
  • the identification device is further configured to capture a user face image and identify a skin health state from the user face image; the processor is further configured to identify the skin health The status, in conjunction with the received user metric data and/or test data, finds skin health status, user metric data and/or test data, and a skin improvement recommendation checklist to obtain skin improvement recommendations.
  • the health suggestion data includes medical advice data; wherein the processor is further configured to: receive a confirmation of the medical advice data by the user; according to the medical advice data, through the Internet Search for a hospital site corresponding to the medical advice data; automatically send a medical request to the hospital site.
  • the smart refrigerator further includes: an external camera disposed outside the smart refrigerator, configured to scan a two-dimensional code of the specific food material; the processor is further configured according to the second The food material corresponding to the dimension code searches the transaction site corresponding to the food material through the Internet; if the transaction site where the user-selected food material exists, the request for generating the order is automatically issued.
  • the built-in camera is further configured to periodically scan the inside of the refrigerator, and the processor is configured to: determine whether there is newly added food according to the built-in camera scan result; if there is the new Adding the foodstuff, identifying the newly added foodstuff; recording the time point at which the newly added foodstuff is judged; comparing the time from the recorded time point with the shelf life corresponding to the identified foodstuff; if from the recorded The time at which the time point begins is greater than the shelf life, and an item expired reminder is issued.
  • the invention discloses a health data monitoring method for a smart refrigerator, which receives user indicator data and/or test data; then identifies user identity information and searches for user indicator data and/or test data corresponding to user identity information; and finally outputs user indicators.
  • Data and/or test data on the one hand, by receiving user indicator data and/or body fat sent test data sent by the user wearable device, and then outputting the indicator data and/or test data corresponding to the user by the user identity information.
  • the user can perform self-detection of the health status of the body according to the output indicator data and/or the test data, and solves the problem that the smart refrigerator cannot provide health monitoring for the user because the smart refrigerator cannot be connected with other smart devices or applications. It provides a more convenient method for users' health monitoring; on the other hand, by intelligently opening the smart refrigerator and user wearable devices, the smart home is further enhanced, enabling users to use smart refrigerators and wearable devices. It can be more convenient and improved. User experience.
  • FIG. 1 illustrates a flow chart of a health data monitoring method of a smart refrigerator according to an example embodiment of the present disclosure.
  • FIG. 2 illustrates a block diagram of an environment of an application of a health data monitoring method of a smart refrigerator, according to an example embodiment of the present disclosure.
  • FIG. 3 illustrates an example of a structure of a smart bracelet according to an example embodiment of the present disclosure.
  • FIG. 4 illustrates an example of a structure of a body fat scale according to an exemplary embodiment of the present disclosure.
  • FIG. 5 illustrates an example of a structure of a smart refrigerator according to an exemplary embodiment of the present disclosure.
  • FIG. 6 illustrates a structural example view of a smart refrigerator in a state in which a refrigerating compartment door is opened, according to an exemplary embodiment of the present disclosure.
  • FIG. 7 illustrates an example diagram of user indicator data and/or test data variation curves in accordance with an example embodiment of the present disclosure.
  • FIG. 8 illustrates a flow chart of another health data monitoring method of a smart refrigerator according to an example embodiment of the present disclosure.
  • FIG. 9 illustrates a flow chart of another health data monitoring method of a smart refrigerator according to an example embodiment of the present disclosure.
  • FIG. 10 illustrates a flow chart of another health data monitoring method of a smart refrigerator according to an example embodiment of the present disclosure.
  • FIG. 11 illustrates a flow chart of a health data monitoring method of another smart refrigerator according to an example embodiment of the present disclosure.
  • FIG. 12 illustrates a flow chart of another health data monitoring method of a smart refrigerator according to an example embodiment of the present disclosure.
  • FIG. 13 illustrates a flow chart of another health data monitoring method of a smart refrigerator according to an example embodiment of the present disclosure.
  • a health data monitoring method of a smart refrigerator is first provided.
  • the health data monitoring method of the smart refrigerator may include the following steps:
  • Step S110 Receive user indicator data and/or body fat sent test data sent by the user wearable device.
  • Step S120 Identify user identity information.
  • Step S130 Search for user indicator data and/or test data corresponding to the user identity information according to the identified user identity information.
  • Step S140 Output the user indicator data and/or test data.
  • the test data is sent, and then the user identity information is outputted with the indicator data corresponding to the user and/or Or test data, so that the user can perform self-detection of the health status of the body according to the output indicator data and/or test data, and solve the problem that the smart refrigerator cannot be provided with health monitoring for the user because the smart refrigerator cannot be connected with other smart devices or applications in the prior art.
  • the problem provides a more convenient method for users' health monitoring; on the other hand, by intelligently opening the smart refrigerator and the user wearable device, the smart home is further enhanced, so that the user is in the smart refrigerator and wearable. When the device is used, it can be more convenient and enhance the user experience.
  • step S110 user indicator data and/or body fat sent test data transmitted by the user wearable device are received.
  • the user wearable device may include a smart watch, a smart bracelet, a smart sports shoe, and the like, and may also include other wearable smart devices, such as smart glasses, etc., this example does not Make special restrictions.
  • the present example uses a smart wristband as a wearable smart device as an example to explain and explain a portion of the present disclosure relating to a wearable device.
  • the smart refrigerator 201 can receive user indicator data sent by the user wearable device (smart bracelet 202) by wireless communication (wifi) or Bluetooth; wherein the user indicator data can be Including the user's heart rate, the user's sleep state, and the user's motion state, etc.; may also include other data, such as the user's body temperature, etc., this example does not impose any special restrictions; secondly, it can also receive the test data sent by the body fat 203
  • the test data may include the user's weight and the user's body fat, etc.; other data may be included, such as a BMI (Body Mass Index), etc., which is not particularly limited in this example.
  • the user indicator data and the test data may be stored in the smart refrigerator according to the mapping relationship between the user ID and the user's face image.
  • Local disk or cloud server 204 may be stored in the smart refrigerator according to the mapping relationship between the user ID and the user's face image.
  • FIG. 2 a structural example diagram of the above smart wristband can be referred to FIG. 2.
  • 301 is a wristband of a smart bracelet, and the wristband can be directly worn to the wrist of the user through a wristband
  • 302 is a display screen of the smart bracelet, which can be used to display the above user index data.
  • the smart bracelet can be used for recording step count, heart rate monitoring, sleep monitoring, sedentary reminder, and calorie-receiving light function; the smart bracelet can include wireless communication, Bluetooth communication, etc., and can communicate with the terminal device. Then read the corresponding data.
  • a structural example diagram of the above-described body fat can be referred to FIG. 4.
  • 401 is a glass panel called body fat
  • 402 is a display screen; when the user needs to measure the weight, it can stand directly on the glass panel, and then the body weight and body fat can be displayed through the display screen.
  • the body fat may include wireless communication, Bluetooth communication, etc., and the corresponding data may be read by communicating with the terminal device.
  • FIG. 5 a structural example diagram of the smart refrigerator described above may be referred to FIG. 5.
  • 501 is a refrigerating compartment door
  • 502 is a greenhouse door
  • 503 is a freezing compartment door
  • 504 is a display screen
  • 505 is a linear microphone array
  • 506 is a sounding hole
  • 507 is a front camera.
  • FIG. 6 is a view showing an example of the structure of the smart refrigerator in a state where the refrigerating compartment door 501 is opened.
  • 601 is a built-in camera
  • 602 is a refrigerator door camera.
  • the health data monitoring method of the smart refrigerator may further include: determining, according to a binding relationship between the user wearable device and the user identity information, the user indicator data sent by the user wearable device.
  • the binding relationship between the user wearable device and the user identity information (for example, the ID that the user wearable device assigns to the user, etc.) may be determined.
  • the user identity information corresponding to the user indicator data (for example, the ID may be bound to the user indicator data); further, for the test data sent by the body fat, the user may enter the user identity information through the display screen 504 of the refrigerator.
  • the prompt when receiving the identity information (ID) input by the user, bind the test data to the identity information. In this way, it is more convenient for the user to query the test data and the user indicator data, and avoid the problem of data confusion caused by the simultaneous use of multiple users.
  • step S120 user identity information is identified.
  • the identifying the user identity information may include: determining, by the face recognition, the user identity information according to the correspondence between the previously stored face and the user identity information.
  • the face information may be first collected by the front camera 507; after the smart refrigerator collects the face information of the user, according to the correspondence between the stored face and the user identity information And identifying the collected facial information and determining the identity information of the user according to the recognition result; if the identity information of the user does not exist, the user may establish a new user information.
  • step S130 user indicator data and/or test data corresponding to the user identity information are searched for according to the identified user identity information.
  • the user indicator data and/or test data corresponding to the user identity information may be searched in the local disk or the cloud server according to the identified user identity information.
  • step S140 the user indicator data and/or test data are output.
  • outputting the user indicator data and/or the test data may include: generating user indicator data and/or test data variation curves within the specific time period of the user; displaying the user indicator data and/or testing Data curve.
  • the user indicator data and/or the test data curve in the specific time period of the user may be generated; wherein the curve may be as shown in FIG. Changes occur, body fat and body circumference also change; in Figure 7, 701 is the user's body weight curve, 702 is the user's body fat curve, 703 is the user's body circumference curve; second, can pass the display screen 504, the above curve is displayed for the user to view; the output may be output by other means for the user to view, for example, may be sent to the user's terminal device, so that the user can view through the terminal device, etc., this example No special restrictions are imposed.
  • Fig. 8 is a view schematically showing another method of monitoring health data of a smart refrigerator.
  • the health data monitoring method of the smart refrigerator may further include steps S810 to S820.
  • step S810 health suggestion data corresponding to the found user index data and/or test data is determined according to the found user index data and/or test data.
  • the user indicator data and/or the test data may be determined according to the found user indicator data and/or the test data.
  • Corresponding health advice data may include: searching for the indicator item and the recommended data comparison table according to the indicator item in the user indicator data, thereby obtaining the The suggestion data corresponding to the indicator item is aggregated; the suggestion data corresponding to the indicator item is aggregated to obtain health suggestion data with the found user indicator data and/or test data.
  • the indicator item and the recommended data comparison table may be searched according to the indicator item in the user indicator data (for example, the user heart rate, the user sleep state, and the user motion state) (for example, the user heart rate and the recommended data may be included.
  • Table, user sleep state and suggestion comparison table, user motion state and suggestion comparison table, etc. and then obtain recommendation data corresponding to each indicator item according to each comparison table; then, comprehensively process the recommendation data corresponding to each indicator item, Obtaining health suggestion data with the found user indicator data and/or test data; for example, according to each indicator item and the recommended data comparison table, the user's heart rate and sleep state are poor, and the exercise state is relatively lacking, so
  • the result is a reminder to the user, for example, to increase the amount of exercise (how many steps per day) and to go to bed early (do not sleep later than a few times and the total sleep time should not be less than a few hours).
  • step S820 the health suggestion data is output.
  • the health suggestion data of the user may be output.
  • the display may be displayed on the display screen 504 for the user to view; or may be outputted by other means for the user to view, for example, may be sent to the user's terminal device, so that the user can view through the terminal device, etc.
  • the example does not impose any special restrictions on this.
  • FIG. 9 schematically shows a health data monitoring method of another smart refrigerator.
  • the health data monitoring method of the smart refrigerator may include steps S910-S940.
  • step S910 based on the recipe suggestion data, the recipe suggestion data and the foodstuff data comparison table are searched to determine the corresponding foodstuff data.
  • step S920 the ingredients already in the refrigerator are identified based on the images taken by the camera inside the refrigerator.
  • step S930 the food to be added is determined based on the determined food material data and the identified existing food material.
  • step S940 the food to be added is displayed.
  • the recipe suggestion data and the food material data comparison table may be searched according to the recipe suggestion data to determine the corresponding food; for example, the sleep quality is not good, and it may be recommended to eat more green.
  • Vegetables, milder fruits and lighter diets can include spinach, oilseeds, apples, bananas, rice porridge, millet porridge, etc., so the food data needed can include spinach, oilseeds, apples, bananas, and rice and millet.
  • the existing ingredients in the refrigerator are identified, for example, according to the captured image, the existing ingredients may include apples, rice, millet, etc.;
  • the determined food material data and the identified existing food materials determine the food materials to be added.
  • the food materials to be added may include spinach, oil wheat vegetables, bananas, and the like; finally, the food materials to be added are displayed on the display screen 504. in.
  • the user can select the food to be purchased and obtain the desired food through a one-click purchase, which may specifically include: searching the transaction site through the Internet according to the selected material of the user; A transaction site where the user-selected ingredients are found is automatically issued a request to generate an order.
  • searching the transaction site through the Internet according to the selected material of the user A transaction site where the user-selected ingredients are found is automatically issued a request to generate an order.
  • the user can select the corresponding food through the touch display screen 504.
  • the selected ingredients include spinach and banana; then, the smart refrigerator searches through the Internet according to the user's selection result.
  • Corresponding transaction sites such as XX supermarkets, etc.
  • a request to generate an order is automatically issued; the user can make a payment according to the order to purchase the desired ingredients.
  • Fig. 10 schematically shows a data monitoring method of another smart refrigerator.
  • the data monitoring method of the smart refrigerator further includes step S1010 - step S1030.
  • step S1010 a user face image is captured.
  • step S1020 the skin health status is identified from the user's face image.
  • step S1030 skin health status, user indicator data and/or test data, and skin improvement suggestions are searched for the identified skin health status in conjunction with the received user indicator data and/or test data. Compare the table to get skin improvement recommendations.
  • the user's face image can be captured by the front camera 507; then, the user's skin health state is recognized according to the captured face image; finally, according to the recognized skin health state, combined with the received user indicator data/or Test data, find skin health status, user metrics data and/or test data, and a skin improvement recommendation checklist to obtain skin improvement recommendations; for example, to identify that the user's skin is dry and yellowish, then by looking up the suggested comparison table
  • Suggestions for skin improvement can include: drinking plenty of water and sleeping early, eating more fruits and vegetables, and so on.
  • Fig. 11 is a view schematically showing another method of monitoring health data of a smart refrigerator.
  • the health data monitoring method of the smart refrigerator may further include step S1110 - step S1130.
  • step S1110 the user's confirmation of the medical advice data is received.
  • step S1120 a hospital site corresponding to the medical advice data is searched via the Internet based on the medical advice data.
  • step S1130 a medical request is automatically issued to the hospital site.
  • the medical advice data can be displayed on the display screen 504, and the user can confirm the medical advice data by touch; secondly, when the refrigerator receives the user After confirming the medical advice data, according to the medical advice data, searching for the hospital site corresponding to the medical advice data through the Internet, for example, the distance may be selected or the medical treatment recommendation data is more professional, and the ranking is relatively high.
  • the message automatically sends a request for medical treatment to the hospital site. In this way, the time for the user to send a medical request and the appointment registration can be saved, and the user experience is further improved.
  • Fig. 12 schematically shows a health data monitoring method of another smart refrigerator.
  • the health data monitoring method of the smart refrigerator may further include step S1210 - step S1230.
  • step S1210 the two-dimensional code of the specific food material is scanned by an external camera of the refrigerator.
  • step S1220 a transaction site corresponding to the food item is searched via the Internet based on the food material corresponding to the two-dimensional code.
  • step S1230 if a transaction site where the user-selected food item exists is searched, a request to generate an order is automatically issued.
  • the external camera (front camera 507) of the refrigerator can scan the two-dimensional code of the specific food material (which can also be a barcode, which is not particularly limited in this example); secondly, according to the food corresponding to the two-dimensional code (for example, it may be broccoli), search for a transaction site corresponding to the food item through the Internet (for example, may be an XX supermarket); and then, when searching for a plurality of websites corresponding to the food item, display each website to the display screen 504. For the user to make a selection; finally, according to the transaction site selected by the user to automatically issue a request for a grand order, the user can complete the purchase of the ingredient after the payment is successful. In this way, the user can choose a more diversified way of purchasing the ingredients, saving the time for the user to purchase the ingredients through the vegetable market or the supermarket, and the jewellery enhances the user experience.
  • the two-dimensional code of the specific food material which can also be a barcode, which is not particularly limited in this example
  • FIG. 13 schematically shows a health data monitoring method of another smart refrigerator.
  • the health data monitoring method of the smart refrigerator may further include step S1310 - step S1350.
  • step S1310 the inside of the refrigerator is periodically scanned by the camera inside the refrigerator to determine whether or not there is newly added food.
  • step S1320 if there is the newly added foodstuff, the newly added foodstuff is identified.
  • step S1330 the point in time at which the newly added food item is judged is recorded.
  • step S1340 the time from the recorded time point is compared with the shelf life corresponding to the identified food item.
  • step S1350 if the time from the recorded time point is greater than the shelf life, an ingredient expiration reminder is issued.
  • the internal camera of the refrigerator (the built-in camera 601 and the door camera 602) is periodically (for example, may be separated by 1 hour or 3 hours, etc., and this example does not particularly limit this).
  • the food inside the refrigerator is scanned and according to the scan result.
  • Determining whether there is newly added ingredients secondly, when scanning the newly added ingredients, taking a photo of the newly added ingredients and identifying the newly added ingredients according to the photos (for example, the newly added ingredients are tomatoes); , recording the time point at which the newly added ingredients are scanned (for example, may be January 5, 2018); again, the time from the recorded time point is compared with the shelf life corresponding to the identified ingredients; if the time from the recording If the start time of the point is greater than the shelf life, the food material expiration reminder can be issued; for example, on January 10, 2018, the time from the tomato to the refrigerator is 5 days, and the event is greater than the shelf life of the tomato (3 days). A reminder that the tomato has expired; it can also issue a reminder that it will expire soon, which can remind the user to eat as soon as possible. In this way, food poisoning and the like for eating out of expired foods are avoided.
  • a smart refrigerator comprising: a receiver configured to receive user indicator data transmitted by a user wearable device and/or test data transmitted by a body fat scale; and an identification device configured to identify The user identity information is configured to search for user indicator data and/or test data corresponding to the user identity information according to the identified user identity information; and the output device is configured to output the user indicator data and/or the test data.
  • the processor is further configured to determine health suggestion data corresponding to the found user indicator data and/or test data according to the found user indicator data and/or test data;
  • the output device is also configured to output the health suggestion data.
  • the determining the health suggestion data corresponding to the searched user indicator data and/or the test data comprises: searching for the indicator item and the suggestion data comparison table according to the indicator item in the user indicator data And obtaining recommendation data corresponding to the indicator item; and the recommendation data corresponding to the indicator item is aggregated to obtain health suggestion data with the found user indicator data and/or test data.
  • the output device is further configured to generate user indicator data and/or test data variation curve within the specific time period of the user; wherein the smart refrigerator further comprises: a display configured to display The user indicator data and/or the test data curve.
  • the health suggestion data includes recipe suggestion data; the processor is further configured to: according to the recipe suggestion data, look up a recipe suggestion data and a food material data comparison table to determine corresponding food material data; the smart The refrigerator further includes: a built-in camera disposed inside the smart refrigerator, configured to photograph an image of the existing food material in the refrigerator; the processor is further configured to identify the existing food material in the refrigerator according to the image of the existing food material, according to the determination The food data and the identified existing ingredients determine the ingredients to be added; the display is also configured to display the ingredients to be added.
  • the processor is further configured to: search for a transaction site via the Internet according to the food selected by the user; if the transaction site where the user-selected food item exists is found, a request to generate an order is automatically issued.
  • the processor is further configured to determine user identity corresponding to the user indicator data according to the binding relationship between the user wearable device and the user identity information for the user indicator data sent by the user wearable device.
  • the output device is further configured to output, for the test data sent by the body fat scale, a prompt for the user to input the user identity information, and use the received user identity information as the user identity information corresponding to the test data.
  • identifying the user identity information includes: determining, by the face recognition, the user identity information according to the correspondence between the previously stored face and the user identity information.
  • the identification device is further configured to capture a user face image and identify a skin health state from the user face image; the processor is further configured to receive the combined skin health status User metrics data and/or test data for skin health status, user metric data and/or test data, and a skin improvement recommendation checklist to obtain skin improvement recommendations.
  • the health suggestion data includes medical advice data; wherein the processor is further configured to: receive confirmation of the medical advice data by the user; and search and seek medical advice according to the medical advice data The hospital site corresponding to the data; the medical request is automatically sent to the hospital site.
  • the smart refrigerator further includes: an external camera disposed outside the smart refrigerator, configured to scan a two-dimensional code of the specific food material; the processor further configured to correspond to the two-dimensional code
  • the foodstuff is searched through the Internet for a transaction site corresponding to the foodstuff; if a transaction site where the user-selected foodstuff is found is found, a request for generating an order is automatically issued.
  • the built-in camera is further configured to periodically scan the inside of the refrigerator, and the processor is configured to: determine whether there is newly added food material according to the built-in camera scan result; if the newly added food material, Identifying the newly added foodstuff; recording a time point at which the newly added foodstuff is judged; comparing the time from the recorded time point with the shelf life corresponding to the identified foodstuff; if starting from the recorded time point The time is greater than the shelf life, and the food expired reminder is issued.
  • modules or units of equipment for action execution are mentioned in the detailed description above, such division is not mandatory. Indeed, in accordance with embodiments of the present disclosure, the features and functions of two or more modules or units described above may be embodied in one module or unit. Conversely, the features and functions of one of the modules or units described above may be further divided into multiple modules or units.
  • the technical solution according to an embodiment of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network.
  • a non-volatile storage medium which may be a CD-ROM, a USB flash drive, a mobile hard disk, etc.
  • a number of instructions are included to cause a computing device (which may be a personal computer, server, mobile terminal, or network device, etc.) to perform a method in accordance with an embodiment of the present disclosure.

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Abstract

一种智能冰箱的健康数据监控方法和智能冰箱，属于智能家居技术领域。该健康数据监控方法包括：接收用户可穿戴设备发送的用户指标数据和/或体脂称发送的测试数据（S110）；识别用户身份信息（S120）；按照识别的用户身份信息，查找与所述用户身份信息对应的用户指标数据和/或测试数据（S130）；输出所述用户指标数据和/或测试数据（S140）。该方法解决了现有技术中由于智能冰箱（201）无法与其他智能设备或应用打通而无法为用户提供健康监控的问题，为用户的健康监控提供了一个较为便捷的方法。

Description

智能冰箱的健康数据监控方法及智能冰箱 技术领域
本公开涉及智能家居技术领域，具体而言，涉及一种智能冰箱的健康数据监控方法以及智能冰箱。
背景技术
随着社会的快速发展以及人民生活水平不断提高，广大用户对健康的关注也在提高。因此，为了满足用户的需求，市面上涌现出了很多基于运动和健康的可穿戴设备。进一步的，随着物联网和各种传感器应用技术的高速发展，智能冰箱也逐渐在市面上出现，目前的智能冰箱的智能性多数集中在食物图像识别、在线购物、食物管理和大屏幕应用等方面。
现有技术中，智能冰箱是单独使用的，不能与其他智能终端(例如智能手环以及体脂秤等等)产生交互，进而可以根据该智能终端的数据提醒用户需要注意的事项。例如，在食物图像识别中，仅仅是单纯识别出冰箱中有那些食物，并将其显示在屏幕上。进一步的，在在线购物中，智能冰箱仅可以单纯识别用户在触摸屏输入的需要购买的物品，再向购物网站发送订单。
但是，上述智能冰箱存在如下缺陷：一方面，不能与其他应用或其他智能设备打通，无法为用户提供更为综合的服务(例如可以包括自动预约医院并挂号等)；进一步的，由于无法与其他应用或其他智能设备打通，因此无法与其他应用或者其他智能设备进行结合，进而为用户提供健康监控。
因此，需要提供一种新的智能冰箱的健康数据监控方法。
需要说明的是，在上述背景技术部分公开的信息仅用于加强对本公开的背景的理解，因此可以包括不构成对本领域普通技术人员已知的现有技术的信息。
发明内容
本公开的目的在于提供一种智能冰箱的健康数据监控方法及智能冰箱，进而至少在一定程度上克服由于相关技术的限制和缺陷而导致的由于智能冰箱无法与其他智能设备或应用打通而无法为用户提供健康监控的问题。
根据本公开的一个方面，提供一种智能冰箱的健康数据监控方法，包括：接收用 户可穿戴设备发送的用户指标数据和/或体脂称发送的测试数据；识别用户身份信息；按照识别的用户身份信息，查找与所述用户身份信息对应的用户指标数据和/或测试数据；输出所述用户指标数据和/或测试数据。
在本公开的一种示例性实施例中，所述健康数据监控方法还包括：按照查找到的用户指标数据和/或测试数据，确定与该查找到的用户指标数据和/或测试数据对应的健康建议数据；输出所述健康建议数据。
在本公开的一种示例性实施例中，所述确定与该查找到的用户指标数据和/或测试数据对应的健康建议数据包括：根据所述用户指标数据中的指标项，查找指标项与建议数据对照表，从而获得与所述指标项对应的建议数据；将与所述指标项对应的建议数据聚合处理，得到与该查找到的用户指标数据和/或测试数据的健康建议数据。
在本公开的一种示例性实施例中，所述输出所述用户指标数据和/或测试数据包括：生成所述用户的特定时间段内的用户指标数据和/或测试数据变化曲线；显示所述用户指标数据和/或测试数据变化曲线。
在本公开的一种示例性实施例中，所述健康建议数据包括食谱建议数据；其中，所述健康数据监控方法还包括：根据食谱建议数据，查找食谱建议数据与食材数据对照表，从而确定对应的食材数据；根据冰箱内部摄像头拍摄的图像识别冰箱中已有的食材；根据确定的食材数据和识别出的已有的食材，确定需添加的食材；显示需添加的食材。
在本公开的一种示例性实施例中，在显示需添加的食材之后，所述健康数据监控方法还包括：根据用户选择的食材，通过互联网搜索交易站点；如果搜索到存在用户选择的食材的交易站点，自动发出生成订单的请求。
在本公开的一种示例性实施例中，在接收用户可穿戴设备发送的用户指标数据和/或体脂秤发送的测试数据之后，所述健康数据监控方法还包括：对于用户可穿戴设备发送的用户指标数据，根据用户可穿戴设备与用户身份信息的绑定关系，确定与该用户指标数据对应的用户身份信息；和/或对于体脂秤发送的测试数据，输出使用户输入用户身份信息的提示，并将接收的用户身份信息作为与该测试数据对应的用户身份信息。
在本公开的一种示例性实施例中，识别用户身份信息包括：通过人脸识别，根据事先存储的人脸与用户身份信息的对应关系，确定用户身份信息。
在本公开的一种示例性实施例中，所述健康数据监控方法还包括：拍摄用户人脸 图像；从用户人脸图像中识别皮肤健康状态；针对识别出的皮肤健康状态，结合接收的用户指标数据和/或测试数据，查找皮肤健康状态、用户指标数据和/或测试数据、以及皮肤改进建议对照表，从而获得皮肤改进建议。
在本公开的一种示例性实施例中，所述健康建议数据包括就医建议数据；其中，所述健康数据监控方法还包括：接收用户对就医建议数据的确认；根据所述就医建议数据，通过互联网搜索与就医建议数据对应的医院站点；自动向该医院站点发出就医请求。
在本公开的一种示例性实施例中，所述健康数据监控方法还包括：通过冰箱的外置摄像头扫描特定食材的二维码；根据所述二维码对应的食材，通过互联网搜索与所述食材对应的交易站点；如果搜索到存在用户选择的食材的交易站点，自动发出生成订单的请求。
在本公开的一种示例性实施例中，所述健康数据监控方法还包括：通过冰箱内部摄像头，定期扫描冰箱内部，判断是否有新加入的食材；如果有所述新加入的食材，则识别所述新加入的食材；记录判断出有新加入的食材的时间点；将从记录的时间点开始的时间和与该识别的食材对应的保质期进行比较；如果从记录的时间点开始的时间大于所述保质期，发出食材过期提醒。
根据本公开的另一个方面，提供一种智能冰箱，包括：接收器，配置为接收用户可穿戴设备发送的用户指标数据和/或体脂秤发送的测试数据；识别设备，配置为识别用户身份信息；处理器，配置为按照识别的用户身份信息，查找与用户身份信息对应的用户指标数据和/或测试数据；输出设备，配置为输出所述用户指标数据和/或测试数据。
在本公开的一种示例性实施例中，所述处理器还配置为按照查找到的用户指标数据和/或测试数据，确定与该查找到的用户指标数据和/或测试数据对应的健康建议数据；所述输出设备还配置为输出所述健康建议数据。
在本公开的一种示例性实施例中，所述确定与该查找到的用户指标数据和/或测试数据对应的健康建议数据包括：根据所述用户指标数据中的指标项，查找指标项与建议数据对照表，从而获得与所述指标项对应的建议数据；将与所述指标项对应的建议数据聚合处理，得到与该查找到的用户指标数据和/或测试数据的健康建议数据。
在本公开的一种示例性实施例中，所述输出设备还配置为生成所述用户的特定时间段内的用户指标数据和/或测试数据变化曲线；其中，所述智能冰箱还包括：显示器， 配置为显示所述用户指标数据和/或测试数据变化曲线。
在本公开的一种示例性实施例中，所述健康建议数据包括食谱建议数据；所述处理器还配置为根据食谱建议数据，查找食谱建议数据与食材数据对照表，从而确定对应的食材数据；所述智能冰箱还包括：设置在智能冰箱内部的内置摄像头，配置为拍摄冰箱中的已有食材的图像；所述处理器还配置为根据所述已有食材的图像识别冰箱中已有的食材，根据确定的食材数据和识别出的已有的食材，确定需添加的食材；所述显示器还配置为显示需添加的食材。
在本公开的一种示例性实施例中，所述处理器还配置为：根据用户选择的食材，通过互联网搜索交易站点；如果搜索到存在用户选择的食材的交易站点，自动发出生成订单的请求。
在本公开的一种示例性实施例中，所述处理器还配置为对于用户可穿戴设备发送的用户指标数据，根据用户可穿戴设备与用户身份信息的绑定关系，确定与该用户指标数据对应的用户身份信息；所述输出设备还配置为对于体脂秤发送的测试数据，输出使用户输入用户身份信息的提示，并将接收的用户身份信息作为与该测试数据对应的用户身份信息。
在本公开的一种示例性实施例中，识别用户身份信息包括：通过人脸识别，根据事先存储的人脸与用户身份信息的对应关系，确定用户身份信息。
在本公开的一种示例性实施例中，所述识别设备还配置为拍摄用户人脸图像，并从用户人脸图像中识别皮肤健康状态；所述处理器还配置为针对识别出的皮肤健康状态，结合接收的用户指标数据和/或测试数据，查找皮肤健康状态、用户指标数据和/或测试数据、以及皮肤改进建议对照表，从而获得皮肤改进建议。
在本公开的一种示例性实施例中，所述健康建议数据包括就医建议数据；其中，所述处理器还配置为：接收用户对就医建议数据的确认；根据所述就医建议数据，通过互联网搜索与就医建议数据对应的医院站点；自动向该医院站点发出就医请求。
在本公开的一种示例性实施例中，所述智能冰箱还包括：设置在智能冰箱外部的外置摄像头，配置为扫描特定食材的二维码；所述处理器还配置为根据所述二维码对应的食材，通过互联网搜索与所述食材对应的交易站点；如果搜索到存在用户选择的食材的交易站点，自动发出生成订单的请求。
在本公开的一种示例性实施例中，所述内置摄像头还配置为定期扫描冰箱内部，所述处理器配置为：根据内置摄像头扫描结果，判断是否有新加入的食材；如果有所 述新加入的食材，则识别所述新加入的食材；记录判断出有新加入的食材的时间点；将从记录的时间点开始的时间和与该识别的食材对应的保质期进行比较；如果从记录的时间点开始的时间大于所述保质期，发出食材过期提醒。
本公开一种智能冰箱的健康数据监控方法，通过接收用户指标数据和/或测试数据；然后识别用户身份信息并查找与用户身份信息对应的用户指标数据和/或测试数据；最后再输出用户指标数据和/或测试数据；一方面，通过接收用户可穿戴设备发送的用户指标数据和/或体脂称发送的测试数据，然后再用户身份信息输出与该用户对应的指标数据和/或测试数据，使得用户可以根据输出的指标数据和/或测试数据进行身体的健康状况的自我检测，解决了现有技术中由于智能冰箱无法与其他智能设备或应用打通而无法为用户提供健康监控的问题，为用户的健康监控提供了一个较为便捷的方法；另一方面，通过将智能冰箱以及用户可穿戴设备打通，进一步的提升了智能家居的智能化，使得用户在对智能冰箱以及可穿戴设备进行使用时可以更加的便捷化，提升了用户体验。
应当理解的是，以上的一般描述和后文的细节描述仅是示例性和解释性的，并不能限制本公开。
附图说明
此处的附图被并入说明书中并构成本说明书的一部分，示出了符合本公开的实施例，并与说明书一起用于解释本公开的原理。显而易见地，下面描述中的附图仅仅是本公开的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1示出根据本公开一示例实施方式的一种智能冰箱的健康数据监控方法的流程图。
图2示出根据本公开一示例实施方式的一种智能冰箱的健康数据监控方法的应用的环境的框图。
图3示出根据本公开一示例实施方式的一种智能手环的结构示例图。
图4示出根据本公开一示例实施方式的一种体脂称的结构示例图
图5示出根据本公开一示例实施方式的一种智能冰箱的结构示例图
图6示出根据本公开一示例实施方式的一种智能冰箱在冷藏室门开启的状态下的结构示例图。
图7示出根据本公开一示例实施方式的一种用户指标数据和/或测试数据变化曲线示例图。
图8示出根据本公开一示例实施方式的另一种智能冰箱的健康数据监控方法的流程图。
图9示出根据本公开一示例实施方式的另一种智能冰箱的健康数据监控方法的流程图。
图10示出根据本公开一示例实施方式的另一种智能冰箱的健康数据监控方法的流程图。
图11示出根据本公开一示例实施方式的另一种智能冰箱的健康数据监控方法的流程图。
图12示出根据本公开一示例实施方式的另一种智能冰箱的健康数据监控方法的流程图。
图13示出根据本公开一示例实施方式的另一种智能冰箱的健康数据监控方法的流程图。
具体实施方式
现在将参考附图更全面地描述示例实施方式。然而，示例实施方式能够以多种形式实施，且不应被理解为限于在此阐述的范例；相反，提供这些实施方式使得本公开将更加全面和完整，并将示例实施方式的构思全面地传达给本领域的技术人员。所描述的特征、结构或特性可以以任何合适的方式结合在一个或更多实施方式中。在下面的描述中，提供许多具体细节从而给出对本公开的实施方式的充分理解。然而，本领域技术人员将意识到，可以实践本公开的技术方案而省略所述特定细节中的一个或更多，或者可以采用其它的方法、组元、装置、步骤等。在其它情况下，不详细示出或描述公知技术方案以避免喧宾夺主而使得本公开的各方面变得模糊。
此外，附图仅为本公开的示意性图解，并非一定是按比例绘制。图中相同的附图标记表示相同或类似的部分，因而将省略对它们的重复描述。附图中所示的一些方框图是功能实体，不一定必须与物理或逻辑上独立的实体相对应。可以采用软件形式来实现这些功能实体，或在一个或多个硬件模块或集成电路中实现这些功能实体，或在不同网络和/或处理器装置和/或微控制器装置中实现这些功能实体。
本示例实施方式中首先提供了一种智能冰箱的健康数据监控方法。参考图1所示， 该智能冰箱的健康数据监控方法可以包括以下步骤：
步骤S110.接收用户可穿戴设备发送的用户指标数据和/或体脂称发送的测试数据。
步骤S120.识别用户身份信息。
步骤S130.按照识别的用户身份信息，查找与所述用户身份信息对应的用户指标数据和/或测试数据。
步骤S140.输出所述用户指标数据和/或测试数据。
上述智能冰箱的健康数据监控方法中，一方面，通过接收用户可穿戴设备发送的用户指标数据和/或体脂称发送的测试数据，然后再用户身份信息输出与该用户对应的指标数据和/或测试数据，使得用户可以根据输出的指标数据和/或测试数据进行身体的健康状况的自我检测，解决了现有技术中由于智能冰箱无法与其他智能设备或应用打通而无法为用户提供健康监控的问题，为用户的健康监控提供了一个较为便捷的方法；另一方面，通过将智能冰箱以及用户可穿戴设备打通，进一步的提升了智能家居的智能化，使得用户在对智能冰箱以及可穿戴设备进行使用时可以更加的便捷化，提升了用户体验。
下面，将结合附图对本示例实施方式中上述智能冰箱的健康数据监控方法中的各步骤进行详细的解释以及说明。
参考图1所示，在步骤S110中，接收用户可穿戴设备发送的用户指标数据和/或体脂称发送的测试数据。
在本示例实施方式中，上述用户可穿戴设备可以包括智能手表、智能手环以及智能运动鞋等等，也可以包括其他可穿戴的智能设备，例如可以是智能眼镜等等，本示例对此不做特殊限制。进一步的，本示例以智能手环作为可穿戴智能设备为例，对本公开中涉及可穿戴设备的部分进行解释以及说明。
在本示例实施方式中，参考图2所示，首先，智能冰箱201可以通过无线通信(wifi)或者蓝牙接收用户可穿戴设备(智能手环202)发送的用户指标数据；其中，用户指标数据可以包括用户心率、用户睡眠状态以及用户运动状态等等；也可以包括其他数据，例如可以是用户体温等等，本示例对此不做特殊限制；其次，还可以接收体脂称203发送的测试数据；其中，测试数据可以包括用户体重以及用户体脂等等；也可以包括其他数据，例如可以是BMI(Body Mass Index，身体质量指数)等等，本示例对此不做特殊限制。进一步的，当接收到用户可穿戴设备发送的用户指标数据和/或体脂 称发送的测试数据后，可以将用户指标数据以及测试数据按照用户ID以及用户面部图像的映射关系存储至智能冰箱的本地磁盘或者云服务器204中。
在本示例实施方式中，上述智能手环的结构示例图可以参考图2所示。在图3中，301为智能手环的腕带，可以通过腕带直接将智能手环佩戴至用户的手腕等地方；302为智能手环的显示屏，可以用于显示上述用户指标数据。进一步的，智能手环的可以用于记录步数、心率监测、睡眠监测、久坐提醒以及消耗卡路里显示灯功能；智能手环可以包括无线通信以及蓝牙通信等等，可以通过和终端设备进行通信进而读取相应的数据。
在本示例实施方式中，上述体脂称的结构示例图可以参考图4所示。在图4中，401为体脂称的玻璃面板，402为显示屏；当用户需要对体重进行测量时，可以直接站在玻璃面板上，然后体重以及体脂可以通过显示屏进行显示。进一步的，体脂称可以包括无线通信以及蓝牙通信等等，可以通过和终端设备进行通信进而读取相应的数据。
在本示例实施方式中，上述智能冰箱的结构示例图可以参考图5所示。在图5中，501为冷藏室门，502为变温室门，503为冷冻室门，504为显示屏幕，505为线性麦克阵列，506为发声孔，507为前置摄像头。进一步的，图6是智能冰箱在冷藏室门501开启的状态下的结构示例图。在图6中，601为内置摄像头，602为冰箱门体摄像头。
在本示例的另一种实施方式中，上述智能冰箱的健康数据监控方法还可以包括：对于用户可穿戴设备发送的用户指标数据，根据用户可穿戴设备与用户身份信息的绑定关系，确定与该用户指标数据对应的用户身份信息；和/或对于体脂秤发送的测试数据，输出使用户输入用户身份信息的提示，并将接收的用户身份信息作为与该测试数据对应的用户身份信息。详细而言：
首先，当接收到用户可穿戴设备发送的用户指标数据后，可以根据用户可穿戴设备与用户身份信息的绑定关系(例如可以是用户可穿戴设备为用户分配的ID等等)，确定与该用户指标数据对应的用户身份信息(例如可以将ID与用户指标数据进行绑定)；进一步的，对于体脂称发送的测试数据，可以通过冰箱的显示屏幕504显示“使用户输入用户身份信息”的提示，当接收到用户输入的身份信息(ID)后，将测试数据与该身份信息进行绑定。通过该方式，使得用户在查询测试数据以及用户指标数据是更加便捷，避免由于同时有多个用户进行使用时造成的数据混淆的问题。
继续参考图1所示，在步骤S120中，识别用户身份信息。
在本示例实施方式中，识别用户身份信息可以包括：通过人脸识别，根据事先存储的人脸与用户身份信息的对应关系，确定用户身份信息。详细而言：
当某一用户需要查询用户指标数据以及测试数据时，可以首先通过前置摄像头507采集面部信息；当智能冰箱采集到该用户的面部信息后，根据实现存储的人脸与用户身份信息的对应关系，对采集到的面部信息进行识别并根据识别结果确定该用户的身份信息；如果不存在该用户的身份信息，则可以对该用户建立一个新的用户信息。
继续参考图1所示，在步骤S130中，按照识别的用户身份信息，查找与所述用户身份信息对应的用户指标数据和/或测试数据。
在本示例实施方式中，当对用户身份信息进行识别后，可以根据识别到的用户身份信息，在本地磁盘或者云服务器中查找与该用户身份信息对应的用户指标数据和/或测试数据。
继续参考图1所示，在步骤S140中，输出所述用户指标数据和/或测试数据。
在本示例实施方式中，输出用户指标数据和/或测试数据可以包括：生成所述用户的特定时间段内的用户指标数据和/或测试数据变化曲线；显示所述用户指标数据和/或测试数据变化曲线。详细而言：
当查找到上述用户指标数据和/或测试数据后，首先，可以生成该用户的特定时间段内的用户指标数据和/或测试数据变化曲线；其中，曲线可以如图7所示，用户的体重发生变化，体脂以及体围也随之发生变化；图7中，701为用户体重的变化曲线，702为用户体脂的变化曲线，703为用户体围的变化曲线；其次，可以通过显示屏幕504对上述曲线进行显示，以供用户进行查看；也可以通过其他方式进行输出以供用户查看，例如可以是发送至用户的终端设备，以使用户通过终端设备进行查看等等，本示例对此不做特殊限制。
图8示意性示出另一种智能冰箱的健康数据监控方法。参考图8所示，该智能冰箱的健康数据监控方法还可以包括步骤S810-步骤S820。
参考图8所示，在步骤S810中，按照查找到的用户指标数据和/或测试数据，确定与该查找到的用户指标数据和/或测试数据对应的健康建议数据。
在本示例实施方式中，当查找到上述用户指标数据和/或测试数据后，还可以根据查到的用户指标数据和/或测试数据，确定与该查找到的用户指标数据和/或测试数据对应的健康建议数据。其中，确定与该查找到的用户指标数据和/或测试数据对应的健 康建议数据具体的可以包括：根据所述用户指标数据中的指标项，查找指标项与建议数据对照表，从而获得与所述指标项对应的建议数据；将与所述指标项对应的建议数据聚合处理，得到与该查找到的用户指标数据和/或测试数据的健康建议数据。详细而言：
首先，可以根据用户指标数据中的指标项(例如可以是用户心率、用户睡眠状态以及用户运动状态种任一种)，查找该指标项与建议数据对照表(例如可以包括用户心率与建议数据对照表、用户睡眠状态与建议对照表以及用户运动状态与建议对照表等等)，然后根据各对照表获得与各指标项对应的建议数据；然后，将各指标项对应的建议数据进行综合处理，得到与该查找到的用户指标数据和/或测试数据的健康建议数据；例如，根据各指标项与建议数据对照表发现，用户的心率以及睡眠状态较差，运动状态较为缺乏，因此可以根据该结果对用户进行提醒，比如可以加大运动量(每天达到多少步数)以及早睡(每天睡觉不要晚于几点以及总共睡眠时间不能少于几小时)等等。
继续参考图8所示，在步骤S820中，输出所述健康建议数据。
在本示例实施方式中，当得到上述健康建议数据后，可以输出该用户的健康建议数据。例如，可以通过显示屏幕504进行显示，以供用户进行查看；也可以通过其他方式进行输出以供用户查看，例如可以是发送至用户的终端设备，以使用户通过终端设备进行查看等等，本示例对此不做特殊限制。
图9示意性示出另一种智能冰箱的健康数据监控方法。参考图9所示，该智能冰箱的健康数据监控方法可以包括步骤S910-步骤S940。
在步骤S910中，根据食谱建议数据，查找食谱建议数据与食材数据对照表，从而确定对应的食材数据。
在步骤S920中，根据冰箱内部摄像头拍摄的图像识别冰箱中已有的食材。
在步骤S930中，根据确定的食材数据和识别出的已有的食材，确定需添加的食材。
在步骤S940中，显示需添加的食材。
下面，对步骤S910-步骤S940进行解释以及说明。首先，当得到上述包括食谱建议数据的健康建议数据后，可以根据该食谱建议数据，查找食谱建议数据与食材数据对照表，从而确定对应的食材；例如，睡眠质量不好，可以建议多吃绿色蔬菜、较为温和的水果以及较为清淡的饮食，可以包括菠菜、油麦菜、苹果、香蕉以及大米粥、 小米粥等等，因此需要的食材数据可以包括菠菜、油麦菜、苹果、香蕉以及大米、小米等；然后，根据冰箱内部摄像头(内置摄像头601)拍摄的图像识别冰箱中已有的食材，例如，根据拍摄到的图像识别到已有食材可以包括苹果、大米以及小米等等；然后，再根据确定的食材数据和识别出的已有的食材，确定需要添加的食材，例如，需要添加的食材可以包括菠菜、油麦菜以及香蕉等等；最后，再将该需要添加的食材显示至显示屏幕504中。
进一步的，当得到上述需要添加的食材后，用户可以自行选择需要购买的食材并通过一键购买来获取所需的食材，具体的可以包括：根据用户选择的食材，通过互联网搜索交易站点；如果搜索到存在用户选择的食材的交易站点，自动发出生成订单的请求。详细而言：
首先，当需要添加的食材显示至显示屏幕504后，用户可以通过触控显示屏幕504选取对应的食材，例如，选取的食材有菠菜以及香蕉；然后，智能冰箱会根据用户的选择结果通过互联网搜索相应的交易站点，例如XX超市等；最后，当搜索到该站点存在用户选择的食材后，自动发出生成订单的请求；用户可以根据该订单进行支付以购买所需的食材。
图10示意性示出另一种智能冰箱的数据监控方法。参考图10所示，该智能冰箱的数据监控方法还包括步骤S1010-步骤S1030。
参考图10所示，在步骤S1010中，拍摄用户人脸图像。
继续参考图10所示，在步骤S1020中，从用户人脸图像中识别皮肤健康状态。
继续参考图10所示，在步骤S1030中，针对识别出的皮肤健康状态，结合接收的用户指标数据和/或测试数据，查找皮肤健康状态、用户指标数据和/或测试数据、以及皮肤改进建议对照表，从而获得皮肤改进建议。
下面，对上述步骤S1010-步骤S1030进行解释以及说明。首先，可以通过前置摄像头507拍摄用户的人脸图像；然后，根据拍摄的人脸图像识别该用户的皮肤健康状态；最后，根据识别出的皮肤健康状态，再结合接收的用户指标数据/或测试数据，查找皮肤健康状态、用户指标数据和/或测试数据、以及皮肤改进建议对照表，从而获得皮肤改进建议；例如，识别出用户的皮肤较为干燥且偏黄，则通过查找建议对照表获得的皮肤改进建议可以包括：多喝水以及早睡、多吃蔬菜水果等等。
图11示意性示出另一种智能冰箱的健康数据监控方法。参考图11所示，该智能冰箱的健康数据监控方法还可以包括步骤S1110-步骤S1130。
参考图11所示，在步骤S1110中，接收用户对就医建议数据的确认。
继续参考图11所示，在步骤S1120中，根据所述就医建议数据，通过互联网搜索与就医建议数据对应的医院站点。
继续参考图11所示，在步骤S1130中，自动向该医院站点发出就医请求。
下面，对上述步骤S1110-步骤S1130进行解释以及说明。首先，当得到上述包括就医建议数据的健康建议数据后，可以将该就医建议数据显示至显示屏幕504中，用户可以通过触控的方式对该就医建议数据进行确认；其次，当冰箱接收到用户对就医建议数据的确认后，根据该就医建议数据，通过互联网搜索与该就医建议数据对应的医院站点，例如可以选取距离较近的或者对就医建议数据中涉及的病症较为专业的、排名较为靠前的医院站点等等；然后，当搜索到上述医院站点以后，可以将该医院站点显示至显示屏幕504上，用户可以根据该显示结果选取符合自己需求的医院站点，智能冰箱在根据用户的确认消息向该医院站点自动发出就医请求。通过该方式，可以节省用户发送就医请求以及预约挂号的时间，进一步提升了用户体验。
图12示意性示出另一种智能冰箱的健康数据监控方法。参考图12所示，该智能冰箱的健康数据监控方法还可以包括步骤S1210-步骤S1230。
参考图12所示，在步骤S1210中，通过冰箱的外置摄像头扫描特定食材的二维码。
继续参考图12所示，在步骤S1220中，根据所述二维码对应的食材，通过互联网搜索与所述食材对应的交易站点。
继续参考图12所示，在步骤S1230中，如果搜索到存在用户选择的食材的交易站点，自动发出生成订单的请求。
下面，对上述步骤S1210-步骤S1230进行解释以及说明。首先，可以通过冰箱的外置摄像头(前置摄像头507)对特定食材的二维码(也可以是条形码，本示例对此不做特殊限制)进行扫描；其次，根据该二维码对应的食材(例如可以是西蓝花)，通过互联网搜索与该食材对应的交易站点(例如可以是XX超市)；然后，当搜索到该食材对应的多个网站时，将各网站显示至显示屏幕504中以供用户进行选择；最后，根据用户选择的交易站点自动发出盛鼎订单的请求，当用户支付成功后即可以完成对该食材的购买。通过该方式，可以使得用户在购买食材上的选择方式更为多样化，节省了用户需要通过去菜市场或者超市购买食材的时间，锦衣提升了用户体验。
图13示意性示出另一种智能冰箱的健康数据监控方法。参考图13所示，该智能 冰箱的健康数据监控方法还可以包括步骤S1310-步骤S1350。
参考图13所示，在步骤S1310中，通过冰箱内部摄像头，定期扫描冰箱内部，判断是否有新加入的食材。
继续参考图13所示，在步骤S1320中，如果有所述新加入的食材，则识别所述新加入的食材。
继续参考图13所示，在步骤S1330中，记录判断出有新加入的食材的时间点。
继续参考图13所示，在步骤S1340中，将从记录的时间点开始的时间和与该识别的食材对应的保质期进行比较。
继续参考图13所示，在步骤S1350中，如果从记录的时间点开始的时间大于所述保质期，发出食材过期提醒。
下面，将对上述步骤S1310-步骤S1350进行解释以及说明。首先，通过冰箱的内部摄像头(内置摄像头601以及门体摄像头602)定期(例如可以是间隔1小时或者3小时等等，本示例对此不做特殊限制)扫描冰箱内部的食材，并根据扫描结果判断是否有新加入的食材；其次，当扫描到有新加入的食材时，拍摄该新加入的食材的照片并根据照片识别该新加入的食材(例如，该新加入的食材为西红柿)；然后，记录扫描到该新加入的食材的时间点(例如可以是2018年1月5日)；再次，从记录的时间点开始的时间与该识别的食材对应的保质期进行比较；如果从记录的时间点开始的时间大于保质期，则可以发出食材过期提醒；例如，在2018年1月10日时，距离西红柿放入冰箱的时间为5天，该事件大于西红柿的保质期(3天)，则可以发出西红柿过期的提醒；也可以发出即将过期的提醒，可以提醒用户尽快食用等等。通过该方式，避免了用于由于食用过期食品造成的食物中毒等等。
根据本公开的一个实施例，还提供了一种智能冰箱，包括：接收器，配置为接收用户可穿戴设备发送的用户指标数据和/或体脂秤发送的测试数据；识别设备，配置为识别用户身份信息；处理器，配置为按照识别的用户身份信息，查找与用户身份信息对应的用户指标数据和/或测试数据；输出设备，配置为输出所述用户指标数据和/或测试数据。
根据本公开的一个实施例，所述处理器还配置为按照查找到的用户指标数据和/或测试数据，确定与该查找到的用户指标数据和/或测试数据对应的健康建议数据；所述输出设备还配置为输出所述健康建议数据。
根据本公开的一个实施例，所述确定与该查找到的用户指标数据和/或测试数据对 应的健康建议数据包括：根据所述用户指标数据中的指标项，查找指标项与建议数据对照表，从而获得与所述指标项对应的建议数据；将与所述指标项对应的建议数据聚合处理，得到与该查找到的用户指标数据和/或测试数据的健康建议数据。
根据本公开的一个实施例，所述输出设备还配置为生成所述用户的特定时间段内的用户指标数据和/或测试数据变化曲线；其中，所述智能冰箱还包括：显示器，配置为显示所述用户指标数据和/或测试数据变化曲线。
根据本公开的一个实施例，所述健康建议数据包括食谱建议数据；所述处理器还配置为根据食谱建议数据，查找食谱建议数据与食材数据对照表，从而确定对应的食材数据；所述智能冰箱还包括：设置在智能冰箱内部的内置摄像头，配置为拍摄冰箱中的已有食材的图像；所述处理器还配置为根据所述已有食材的图像识别冰箱中已有的食材，根据确定的食材数据和识别出的已有的食材，确定需添加的食材；所述显示器还配置为显示需添加的食材。
根据本公开的一个实施例，所述处理器还配置为：根据用户选择的食材，通过互联网搜索交易站点；如果搜索到存在用户选择的食材的交易站点，自动发出生成订单的请求。
根据本公开的一个实施例，所述处理器还配置为对于用户可穿戴设备发送的用户指标数据，根据用户可穿戴设备与用户身份信息的绑定关系，确定与该用户指标数据对应的用户身份信息；所述输出设备还配置为对于体脂秤发送的测试数据，输出使用户输入用户身份信息的提示，并将接收的用户身份信息作为与该测试数据对应的用户身份信息。
根据本公开的一个实施例，识别用户身份信息包括：通过人脸识别，根据事先存储的人脸与用户身份信息的对应关系，确定用户身份信息。
根据本公开的一个实施例，所述识别设备还配置为拍摄用户人脸图像，并从用户人脸图像中识别皮肤健康状态；所述处理器还配置为针对识别出的皮肤健康状态，结合接收的用户指标数据和/或测试数据，查找皮肤健康状态、用户指标数据和/或测试数据、以及皮肤改进建议对照表，从而获得皮肤改进建议。
根据本公开的一个实施例，所述健康建议数据包括就医建议数据；其中，所述处理器还配置为：接收用户对就医建议数据的确认；根据所述就医建议数据，通过互联网搜索与就医建议数据对应的医院站点；自动向该医院站点发出就医请求。
根据本公开的一个实施例，所述智能冰箱还包括：设置在智能冰箱外部的外置摄 像头，配置为扫描特定食材的二维码；所述处理器还配置为根据所述二维码对应的食材，通过互联网搜索与所述食材对应的交易站点；如果搜索到存在用户选择的食材的交易站点，自动发出生成订单的请求。
根据本公开的一个实施例，所述内置摄像头还配置为定期扫描冰箱内部，所述处理器配置为：根据内置摄像头扫描结果，判断是否有新加入的食材；如果有所述新加入的食材，则识别所述新加入的食材；记录判断出有新加入的食材的时间点；将从记录的时间点开始的时间和与该识别的食材对应的保质期进行比较；如果从记录的时间点开始的时间大于所述保质期，发出食材过期提醒。
应当注意，尽管在上文详细描述中提及了用于动作执行的设备的若干模块或者单元，但是这种划分并非强制性的。实际上，根据本公开的实施方式，上文描述的两个或更多模块或者单元的特征和功能可以在一个模块或者单元中具体化。反之，上文描述的一个模块或者单元的特征和功能可以进一步划分为由多个模块或者单元来具体化。
此外，尽管在附图中以特定顺序描述了本公开中方法的各个步骤，但是，这并非要求或者暗示必须按照该特定顺序来执行这些步骤，或是必须执行全部所示的步骤才能实现期望的结果。附加的或备选的，可以省略某些步骤，将多个步骤合并为一个步骤执行，以及/或者将一个步骤分解为多个步骤执行等。
通过以上的实施方式的描述，本领域的技术人员易于理解，这里描述的示例实施方式可以通过软件实现，也可以通过软件结合必要的硬件的方式来实现。因此，根据本公开实施方式的技术方案可以以软件产品的形式体现出来，该软件产品可以存储在一个非易失性存储介质(可以是CD-ROM，U盘，移动硬盘等)中或网络上，包括若干指令以使得一台计算设备(可以是个人计算机、服务器、移动终端、或者网络设备等)执行根据本公开实施方式的方法。
此外，上述附图仅是根据本公开示例性实施例的方法所包括的处理的示意性说明，而不是限制目的。易于理解，上述附图所示的处理并不表明或限制这些处理的时间顺序。另外，也易于理解，这些处理可以是例如在多个模块中同步或异步执行的。
本领域技术人员在考虑说明书及实践这里公开的发明后，将容易想到本公开的其他实施例。本申请旨在涵盖本公开的任何变型、用途或者适应性变化，这些变型、用途或者适应性变化遵循本公开的一般性原理并包括本公开未公开的本技术领域中的公知常识或惯用技术手段。说明书和实施例仅被视为示例性的，本公开的真正范围和 精神由权利要求指出。

Claims (24)

  1. 一种智能冰箱的健康数据监控方法，其特征在于，包括：
    接收用户可穿戴设备发送的用户指标数据和/或体脂称发送的测试数据；
    识别用户身份信息；
    按照识别的用户身份信息，查找与所述用户身份信息对应的用户指标数据和/或测试数据；
    输出所述用户指标数据和/或测试数据。
  2. 根据权利要求1所述的健康数据监控方法，其特征在于，所述健康数据监控方法还包括：
    按照查找到的用户指标数据和/或测试数据，确定与该查找到的用户指标数据和/或测试数据对应的健康建议数据；
    输出所述健康建议数据。
  3. 根据权利要求2所述的健康数据监控方法，其特征在于，所述确定与该查找到的用户指标数据和/或测试数据对应的健康建议数据包括：
    根据所述用户指标数据中的指标项，查找指标项与建议数据对照表，从而获得与所述指标项对应的建议数据；
    将与所述指标项对应的建议数据聚合处理，得到与该查找到的用户指标数据和/或测试数据的健康建议数据。
  4. 根据权利要求1所述的健康数据监控方法，其特征在于，所述输出所述用户指标数据和/或测试数据包括：
    生成所述用户的特定时间段内的用户指标数据和/或测试数据变化曲线；
    显示所述用户指标数据和/或测试数据变化曲线。
  5. 根据权利要求2所述的健康数据监控方法，其特征在于，所述健康建议数据包括食谱建议数据；
    其中，所述健康数据监控方法还包括：
    根据食谱建议数据，查找食谱建议数据与食材数据对照表，从而确定对应的食材数据；
    根据冰箱内部摄像头拍摄的图像识别冰箱中已有的食材；
    根据确定的食材数据和识别出的已有的食材，确定需添加的食材；
    显示需添加的食材。
  6. 根据权利要求5所述的健康数据监控方法，其特征在于，在显示需添加的食材之后，所述健康数据监控方法还包括：
    根据用户选择的食材，通过互联网搜索交易站点；
    如果搜索到存在用户选择的食材的交易站点，自动发出生成订单的请求。
  7. 根据权利要求1所述的健康数据监控方法，其特征在于，在接收用户可穿戴设备发送的用户指标数据和/或体脂秤发送的测试数据之后，所述健康数据监控方法还包括：
    对于用户可穿戴设备发送的用户指标数据，根据用户可穿戴设备与用户身份信息的绑定关系，确定与该用户指标数据对应的用户身份信息；和/或
    对于体脂秤发送的测试数据，输出使用户输入用户身份信息的提示，并将接收的用户身份信息作为与该测试数据对应的用户身份信息。
  8. 根据权利要求1所述的健康数据监控方法，其特征在于，识别用户身份信息包括：
    通过人脸识别，根据事先存储的人脸与用户身份信息的对应关系，确定用户身份信息。
  9. 根据权利要求1所述的健康数据监控方法，其特征在于，所述健康数据监控方法还包括：
    拍摄用户人脸图像；
    从用户人脸图像中识别皮肤健康状态；
    针对识别出的皮肤健康状态，结合接收的用户指标数据和/或测试数据，查找皮肤健康状态、用户指标数据和/或测试数据、以及皮肤改进建议对照表，从而获得皮肤改进建议。
  10. 根据权利要求2所述的健康数据监控方法，其特征在于，所述健康建议数据包括就医建议数据；
    其中，所述健康数据监控方法还包括：
    接收用户对就医建议数据的确认；
    根据所述就医建议数据，通过互联网搜索与就医建议数据对应的医院站点；
    自动向该医院站点发出就医请求。
  11. 根据权利要求1所述的健康数据监控方法，其特征在于，所述健康数据监控 方法还包括：
    通过冰箱的外置摄像头扫描特定食材的二维码；
    根据所述二维码对应的食材，通过互联网搜索与所述食材对应的交易站点；
    如果搜索到存在用户选择的食材的交易站点，自动发出生成订单的请求。
  12. 根据权利要求1所述的健康数据监控方法，其特征在于，所述健康数据监控方法还包括：
    通过冰箱内部摄像头，定期扫描冰箱内部，判断是否有新加入的食材；
    如果有所述新加入的食材，则识别所述新加入的食材；
    记录判断出有新加入的食材的时间点；
    将从记录的时间点开始的时间和与该识别的食材对应的保质期进行比较；
    如果从记录的时间点开始的时间大于所述保质期，发出食材过期提醒。
  13. 一种智能冰箱，其特征在于，包括：
    接收器，配置为接收用户可穿戴设备发送的用户指标数据和/或体脂秤发送的测试数据；
    识别设备，配置为识别用户身份信息；
    处理器，配置为按照识别的用户身份信息，查找与用户身份信息对应的用户指标数据和/或测试数据；
    输出设备，配置为输出所述用户指标数据和/或测试数据。
  14. 根据权利要求13所述的智能冰箱，其特征在于，所述处理器还配置为按照查找到的用户指标数据和/或测试数据，确定与该查找到的用户指标数据和/或测试数据对应的健康建议数据；
    所述输出设备还配置为输出所述健康建议数据。
  15. 根据权利要求14所述的智能冰箱，其特征在于，所述确定与该查找到的用户指标数据和/或测试数据对应的健康建议数据包括：
    根据所述用户指标数据中的指标项，查找指标项与建议数据对照表，从而获得与所述指标项对应的建议数据；
    将与所述指标项对应的建议数据聚合处理，得到与该查找到的用户指标数据和/或测试数据的健康建议数据。
  16. 根据权利要求15所述的智能冰箱，其特征在于，所述输出设备还配置为生成所述用户的特定时间段内的用户指标数据和/或测试数据变化曲线；
    其中，所述智能冰箱还包括：
    显示器，配置为显示所述用户指标数据和/或测试数据变化曲线。
  17. 根据权利要求16所述的智能冰箱，其特征在于，所述健康建议数据包括食谱建议数据；
    所述处理器还配置为根据食谱建议数据，查找食谱建议数据与食材数据对照表，从而确定对应的食材数据；
    所述智能冰箱还包括：
    设置在智能冰箱内部的内置摄像头，配置为拍摄冰箱中的已有食材的图像；
    所述处理器还配置为根据所述已有食材的图像识别冰箱中已有的食材，根据确定的食材数据和识别出的已有的食材，确定需添加的食材；
    所述显示器还配置为显示需添加的食材。
  18. 根据权利要求17所述的智能冰箱，其特征在于，所述处理器还配置为：根据用户选择的食材，通过互联网搜索交易站点；
    如果搜索到存在用户选择的食材的交易站点，自动发出生成订单的请求。
  19. 根据权利要求13所述的智能冰箱，其特征在于，所述处理器还配置为对于用户可穿戴设备发送的用户指标数据，根据用户可穿戴设备与用户身份信息的绑定关系，确定与该用户指标数据对应的用户身份信息；
    所述输出设备还配置为对于体脂秤发送的测试数据，输出使用户输入用户身份信息的提示，并将接收的用户身份信息作为与该测试数据对应的用户身份信息。
  20. 根据权利要求13所述的智能冰箱，其特征在于，识别用户身份信息包括：
    通过人脸识别，根据事先存储的人脸与用户身份信息的对应关系，确定用户身份信息。
  21. 根据权利要求13所述的智能冰箱，其特征在于，所述识别设备还配置为拍摄用户人脸图像，并从用户人脸图像中识别皮肤健康状态；
    所述处理器还配置为针对识别出的皮肤健康状态，结合接收的用户指标数据和/或测试数据，查找皮肤健康状态、用户指标数据和/或测试数据、以及皮肤改进建议对照表，从而获得皮肤改进建议。
  22. 根据权利要求14所述的智能冰箱，其特征在于，所述健康建议数据包括就医建议数据；
    其中，所述处理器还配置为：接收用户对就医建议数据的确认；
    根据所述就医建议数据，通过互联网搜索与就医建议数据对应的医院站点；
    自动向该医院站点发出就医请求。
  23. 根据权利要求13所述的智能冰箱，其特征在于，所述智能冰箱还包括：
    设置在智能冰箱外部的外置摄像头，配置为扫描特定食材的二维码；
    所述处理器还配置为根据所述二维码对应的食材，通过互联网搜索与所述食材对应的交易站点；
    如果搜索到存在用户选择的食材的交易站点，自动发出生成订单的请求。
  24. 根据权利要求17所述的智能冰箱，其特征在于，所述内置摄像头还配置为定期扫描冰箱内部，所述处理器配置为：
    根据内置摄像头扫描结果，判断是否有新加入的食材；
    如果有所述新加入的食材，则识别所述新加入的食材；
    记录判断出有新加入的食材的时间点；
    将从记录的时间点开始的时间和与该识别的食材对应的保质期进行比较；
    如果从记录的时间点开始的时间大于所述保质期，发出食材过期提醒。
PCT/CN2019/075069 2018-02-14 2019-02-14 智能冰箱的健康数据监控方法及智能冰箱 Ceased WO2019158108A1 (zh)

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