WO2017190518A1 - 智能冰箱及其控制方法和控制系统 - Google Patents
智能冰箱及其控制方法和控制系统 Download PDFInfo
- Publication number
- WO2017190518A1 WO2017190518A1 PCT/CN2016/113927 CN2016113927W WO2017190518A1 WO 2017190518 A1 WO2017190518 A1 WO 2017190518A1 CN 2016113927 W CN2016113927 W CN 2016113927W WO 2017190518 A1 WO2017190518 A1 WO 2017190518A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- refrigerator
- item
- identified
- information
- image information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Images
Classifications
-
- 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
- F25D29/005—Mounting of control devices
-
- 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
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
- G06F16/5838—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using colour
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/951—Indexing; Web crawling techniques
-
- 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
- F25D2400/00—General features of, or devices for refrigerators, cold rooms, ice-boxes, or for cooling or freezing apparatus not covered by any other subclass
- F25D2400/36—Visual displays
- F25D2400/361—Interactive visual displays
-
- 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 invention relates to the field of household appliances, in particular to a smart refrigerator and a control method and control system thereof.
- the Internet of Things is another wave of global informationization following computer, Internet and mobile communication. It is a new stage of global information development. With the rise of the concept of Internet of Things, the products of the home appliance industry are accelerating and intelligent, and a series of smart refrigerators are launched.
- the existing smart refrigerator usually adopts a camera to collect pictures of the articles therein, classifies the articles according to the article identifiers corresponding to the image of the articles, and then controls the temperature of the refrigerator to keep the articles fresh.
- the database is usually established by the following methods:
- the tester takes several photos, defines and marks a large number of ingredients, and then uploads the obtained data to the database, and further implants the database into the refrigerator of the client, in order to ensure the accuracy of the later identification,
- the information of the items that need to be stored in the database is very large. Therefore, a large amount of manpower and material resources are needed to build the database. Further, after the refrigerator is shipped, the database remains unchanged. Thus, with the advancement of technology, more and more When more exotic items appear, the accuracy of the camera to identify the item will be greatly reduced.
- an embodiment of the present invention provides a control method for a smart refrigerator, including: receiving image information of an item to be identified sent by a refrigerator through a network;
- the identification information is sent to the refrigerator through the network to be displayed through the display interface of the refrigerator.
- the method further includes:
- the confirmation information is that the matching result of the image information of the item to be identified and the identification information output to the refrigerator is correct;
- the confirmation information is that the matching result of the image information of the item to be identified and the identification information output to the refrigerator is incorrect;
- the method further includes: matching the image information and the identification information of the item to be identified one by one, and synchronizing Send to the refrigerator to display through the display interface of the refrigerator.
- the method further includes: performing reverse auditing on the image information of the to-be-identified item displayed on the display interface of the refrigerator and the corresponding identification information by using the network database, and updating the network if database.
- the present invention also provides a control system for a smart refrigerator, comprising:
- a data acquisition module configured to receive, by using a network, image information of an item to be identified sent by the refrigerator
- a query processing module configured to query a network database by using image information of the received item to be identified, and obtain identification information matched thereto;
- an output module configured to send the identification information to the refrigerator through the network to be displayed through a display interface of the refrigerator.
- the query processing module is further configured to: if the confirmation information is received, the confirmation information is that the matching result of the image information of the item to be identified and the identification information output to the refrigerator is correct; and The image information and the identification information of the identified item are correspondingly updated to the network database.
- the query processing module is further configured to:
- the confirmation information is that the matching result of the image information of the item to be identified and the identification information output to the refrigerator is incorrect;
- the output module is further configured to: match the image information and the identification information of the item to be identified one by one, and synchronously send the same to the refrigerator to display through the display interface of the refrigerator.
- the query processing module is further configured to: display the to-be-displayed on a display interface of the refrigerator
- the image information of the identified item and the corresponding identification information are reversely audited by means of the network database, and if approved, the network database is updated.
- the present invention also provides a smart refrigerator configured to employ any of the control methods of the present invention; and/or configured to include any of the control systems of the present invention.
- the control method and control system for a smart refrigerator of the present invention identifies and matches image information of an item to be identified based on a network; further, updates a network database based on data generated during use of the refrigerator, when a new one is generated again When the image information is used, it can be processed according to the updated network database.
- the data stored in the network database is increased, the accuracy of the background food identification is ensured, and the user is further improved.
- FIG. 1 is a flow chart showing a control method for a smart refrigerator according to an embodiment of the present invention
- FIG. 2 is a block diagram of a control system for a smart refrigerator in accordance with an embodiment of the present invention.
- the present invention provides a smart refrigerator control method, the method comprising:
- the image information of the item to be identified is image information of the item stored in the refrigerator, which is usually acquired by a collecting device provided in the refrigerator, for example, a camera.
- a plurality of control buttons are usually disposed on the outside of the refrigerator.
- the corresponding control button When the corresponding control button is activated, it is regarded as issuing an identification signal, and starting to activate the image information of the stored article in the refrigerator.
- a device such as a sensor may be disposed on the refrigerator for issuing an identification signal.
- the refrigerator door when opened, it is regarded as an identification signal, which will not be described in detail herein.
- the number and color of the acquired items may be different according to the installation position and the change of the brightness of the light, for example, an item may exist on the image of the obtained item. There may also be many different items, which will not be described in detail here.
- connection mode of the network is not specifically limited, for example, RFID, Bluetooth, WIFI, Internet, LAN, and the like.
- the method further includes:
- the network database includes: attribute information of the item and corresponding identification information.
- the network database can be stored in a cloud or a separate server, and the refrigerator of the client side is connected to and exchanged with the network database through a network.
- the data stored in the network database can be updated according to the operation of the user's refrigerator. Therefore, the initial data stored in the network database is not required to be very large, thereby saving manpower and material cost of building a database. Introduction.
- the identification information is usually the item name.
- the step S2 specifically includes:
- the image information is preprocessed by using contour detection technology and background segmentation technology to obtain a feature vector group of image information, and the feature vector group includes: shape, color, texture, and the like of the article.
- the identification information corresponding to the feature vector class having the largest correlation is assigned to the image information corresponding to the object to be tested.
- each feature vector class includes multiple sets of feature vectors.
- the similarity may be represented by a numerical value; it may be an average value, a median value, a weighted average value, and the like of the similarities of the respective feature vectors in the feature vector group.
- the similarity is expressed by the average of the similarities of the individual feature vectors in the feature vector group.
- the method further includes:
- the image information is directly sent to the network database for analysis, and simultaneously sent to the display interface of the refrigerator. Further, only the identification information matched by the network database is returned to the refrigerator, and further displayed on the display interface of the refrigerator.
- the image information and the identification information of the item to be identified are matched one by one, and are synchronously sent to the refrigerator to be displayed through the display interface of the refrigerator.
- the identification information is synchronously displayed in the display area of the image information; or in the form of a list, the image information and the corresponding identification information are displayed one by one, and no detailed information is provided here. Narration.
- the image information of the item to be identified matches the identification information
- the image information of the item to be identified and the matching identification information are matched one by one and returned to the refrigerator at the same time, and displayed through the refrigerator.
- the interface is displayed.
- the method further includes:
- the confirmation information is that the matching result of the image information of the item to be identified and the identification information outputted to the refrigerator is correct; and the image information and the identification information of the item to be identified are correspondingly updated to the Network database.
- the confirmation information is that the matching result of the image information of the item to be identified and the identification information outputted to the refrigerator is incorrect; and the correct identification information is configured for the image information of the item to be identified, and Image information of the item to be identified and corresponding correct identification
- the information is updated to the network database.
- a similarity threshold is set, and when the similarity between the feature vector group of the image information of the item to be identified and the feature vector class in the network database is greater than the similarity threshold, the output is judged.
- the matching result of the image information and the identification information of the item to be identified to the display interface is correct; otherwise, it is an error.
- the similarity threshold is a fixed value, and the range of values is usually between 50% and 100%.
- the similarity threshold is 70%
- the similarity of the item to be identified 1 is greater than the similarity threshold preset by the system, it is determined that the matching result of the image information and the identification information of the item to be identified output to the display interface is correct. If the similarity of the item to be identified 2 is less than the similarity threshold preset by the system, it is determined that the matching result of the image information and the identification information of the item to be identified output to the display interface is an error.
- the data stored in the network database is actively expanded by the operation of the refrigerator at the user end, thereby saving the labor and material cost of building the database.
- the method may further include:
- the reverse auditing process querying the network database with the identifier information, acquiring a unique feature vector class corresponding to the identifier information in the network database; and image information of the item to be identified and the feature The vector class is compared, and the item to be identified is determined by the comparison result Whether the image information and the corresponding identification information can be reverse audited by the network database.
- the image information of the item to be identified may be preprocessed by using the contour detection technology and the background segmentation technology to acquire the feature vector group of the image information of the item to be identified.
- the feature vector group includes: an object shape, a color, a texture, and the like.
- an audit similarity threshold is set, when the similarity between the feature vector group of the image information of the item to be identified and the known feature vector class in the network database is greater than the similarity threshold, determining to return to the network database. The image information and the identification information of the item to be identified are reviewed, so that the user's misoperation can be avoided to disturb the network database.
- the audit similarity threshold is also a fixed value, and the range of values is usually between 50% and 100%.
- the identification information corresponding to the item is identified as “orange”
- further "orange” is The picture information and the matching identification information are sent to the refrigerator for display through the display interface of the refrigerator.
- the picture information displayed on the display interface and the matching identification information are not changed.
- the network database is reversely queried with the identification information as "orange”. After the comparison, the confirmation is passed, and the current acquisition is confirmed.
- the picture information and identification information of the identified item are updated to the network database.
- the identification information corresponding to the item is identified as “orange”
- further "orange” is The picture information and the matching identification information are sent to the refrigerator for display through the display interface of the refrigerator.
- the picture information displayed on the display interface and the matching identification information are changed, for example, the user misuses, and the identification information of the picture information corresponding to the "orange” is changed to "banana”; and the identification information is further reversed as "banana”
- the network database After querying the network database, after re-compare, it can be confirmed that the changed data fails to pass the audit. At this time, in order to simplify the program and prevent entry into an infinite loop, the corresponding data can be directly discarded.
- the image information of "orange” is received through the network. After querying the network database, due to factors such as light and dark changes in light, the collected picture information is queried after querying the database, and the identification information corresponding to the item is mistakenly considered as “orange”, and the image of "orange” is further The information and the matching identification information are sent to the refrigerator for display through the display interface of the refrigerator.
- Modifying the picture information displayed on the display interface and the matching identification information for example, changing the identification information of the picture information corresponding to "orange” from “orange” to “orange”; and further reversing the identification information as "orange”
- the modified data is confirmed to pass the audit, and then the picture information and the identification information of the item to be identified acquired at the time are updated to the network database.
- the number of times threshold may be set. After the user end modifies the identification information given by the network database N times in a time period, if the N is greater than or equal to the threshold number, the user end Set to maliciously operate the client and restrict it from making changes to the data for a certain period of time, so I won't go into details here.
- the update period of the network database may also be set, for example, 1 hour, 1 day, one week, etc., or the administrator of the network database may periodically update according to the demand, when the network After receiving the corresponding update information, the database first stores the corresponding update information, and then updates the data uniformly under the set update period. Thus, the calculation amount is reduced, and details are not described herein.
- the administrator of the network database may also detect the validity of the uploaded data, and then perform a corresponding update operation. This will not be described in detail.
- the image information may be processed according to the updated network database, so that the data stored in the network database is increased by the data fed back by the user terminal to ensure background food identification. The accuracy.
- the network database of the present invention is uniformly managed through the network, so that a better service can be provided according to the needs of the customer, and at the same time, the push content can be added to the refrigerator of the user terminal through the network database, thereby facilitating unified management. .
- a control system for a smart refrigerator includes: a user end and a server end connected to the network; the user end includes: an image acquisition module 100, configured to collect the to-be-identified Image information of the item.
- the server side includes: a data acquisition module 200, query processing module 300, output module 400, network database 500.
- the data obtaining module 200 is configured to receive, by using a network, image information of an item to be identified sent by the refrigerator;
- the image information of the item to be identified is image information of the item stored in the refrigerator, which is usually acquired by the image collecting module 100 provided in the refrigerator, for example, a camera.
- a plurality of control buttons are usually disposed on the outside of the refrigerator.
- the corresponding control button When the corresponding control button is activated, it is regarded as issuing an identification signal, and the image acquisition module 100 is started to recognize the image information of the stored articles in the refrigerator.
- a device such as a sensor may be disposed on the refrigerator for issuing an identification signal.
- the refrigerator door when opened, it is regarded as an identification signal, which will not be described in detail herein.
- the number and color of the acquired items may be different according to the installation position and the change of the brightness of the light, for example, an item may exist on the image of the obtained item. There may also be many different items, which will not be described in detail here.
- connection mode of the network is not specifically limited, for example, RFID, Bluetooth, WIFI, Internet, LAN, and the like.
- the query processing module 300 is configured to: query the network database 500 by using the received image information of the item to be identified, and obtain the identification information matched thereto;
- the network database 500 includes attribute information of the item and corresponding identification information.
- the network database 500 can be stored in a cloud or on a separate server, and the refrigerator of the client is connected to and exchanged with the network database 500 through a network.
- the data stored in the network database 500 can be updated according to the operation of the user's client refrigerator.
- the network database 500 may not store data, or only store a small amount of data, thereby saving manpower and material cost of building a database. The details will be described below.
- the identification information is usually the item name.
- the query processing module 300 is specifically configured to:
- the image information is preprocessed by using contour detection technology and background segmentation technology to obtain a feature vector group of image information, and the feature vector group includes: shape, color, texture, and the like of the article.
- the identification information corresponding to the feature vector class having the largest correlation is assigned to the image information corresponding to the object to be tested.
- each feature vector class includes multiple sets of feature vectors.
- the similarity may be represented by a numerical value; it may be an average value, a median value, a weighted average value, and the like of the similarities of the respective feature vectors in the feature vector group.
- the similarity is expressed by the average of the similarities of the individual feature vectors in the feature vector group.
- the similarity of the corresponding item 1 is 90%, and the shape similarity is 96%.
- the output module 400 is configured to: send the identification information to a refrigerator through a network to display through a display interface of the refrigerator.
- the image information of the item is recognized, the image information is directly sent to the network database 500 for analysis, and simultaneously sent to The display interface of the refrigerator is displayed; further, only the identification information that has been analyzed after being parsed by the network database 500 is returned to the refrigerator, and further displayed on the display interface of the refrigerator.
- the output module 400 is configured to match the image information and the identification information of the item to be identified one by one, and simultaneously send it to the refrigerator to be displayed through the display interface of the refrigerator.
- the identification information is synchronously displayed in the display area of the image information; or in the form of a list, the image information and the corresponding identification information are displayed one by one, and no detailed information is provided here. Narration.
- the output module 400 matches the image information of the item to be identified and the identification information matched thereto, and returns to the refrigerator at the same time.
- the display interface of the refrigerator is displayed.
- the query processing module 300 is further configured to: if the confirmation information is received, the confirmation information is that the matching result of the image information of the item to be identified and the identification information output to the refrigerator is correct; The image information and the identification information of the item to be identified are correspondingly updated to the network database 500.
- the query processing module 300 is further configured to: if the confirmation information is received, the confirmation information is that the matching result of the image information of the item to be identified and the identification information output to the refrigerator is incorrect; and the image information of the item to be identified is correctly configured
- the identification information is updated, and the image information of the item to be identified and the corresponding correct identification information are updated to the network database 500.
- a similarity threshold is set, and the query processing module 300 determines that the similarity between the feature vector group of the image information of the item to be identified and the feature vector class in the network database 500 is greater than the similarity.
- the threshold it is determined that the matching result of the image information and the identification information of the item to be identified output to the display interface is correct; otherwise, it is an error.
- the similarity threshold is a fixed value, and the range of values is usually between 50% and 100%.
- the similarity threshold is 70%
- the similarity of the item to be identified 1 is greater than the similarity threshold preset by the system, it is determined that the matching result of the image information and the identification information of the item to be identified output to the display interface is correct.
- the similarity of the item to be identified 2 is less than the similarity preset by the system If the degree threshold is used, it is determined that the matching result of the image information and the identification information of the item to be identified output to the display interface is an error.
- the data stored in the network database 500 is actively expanded by the operation of the refrigerator at the user end, thereby saving the labor and material cost of building the database.
- the query processing module 300 is further configured to: perform reverse auditing on the image information of the item to be identified and the corresponding identification information displayed on the display interface of the refrigerator through the network database 500, if The network database 500 is updated upon review.
- the query processing module 300 queries the network database 500 with the identification information, and acquires a unique feature vector class corresponding to the identifier information in the network database 500; and image information of the item to be identified Comparing with the feature vector class, and determining, by the comparison result, whether the image information of the item to be identified and the corresponding identification information can pass the reverse review of the network database.
- the query processing module 300 may also perform pre-processing on the image information of the item to be identified by using the contour detection technology and the background segmentation technology to acquire a feature vector group of the image information of the item to be identified.
- the feature vector group includes: the shape, color, texture, and the like of the item.
- the audit similarity threshold is also a fixed value, and the range of values is usually between 50% and 100%.
- the identification information corresponding to the item is identified as “orange”
- further "orange” is The picture information and the matching identification information are sent to the refrigerator for display through the display interface of the refrigerator.
- the picture information displayed on the display interface and the matching identification information are not changed.
- the network database is reversely queried with the identification information as "orange”. After the comparison, the confirmation is passed, and the current acquisition is confirmed.
- the picture information and identification information of the identified item are updated to the network database.
- the identification information corresponding to the item is identified as “orange”
- further "orange” is The picture information and the matching identification information are sent to the refrigerator for display through the display interface of the refrigerator.
- the picture information displayed on the display interface and the matching identification information are changed, for example, the user misuses, and the identification information of the picture information corresponding to the "orange” is changed to "banana”; and the identification information is further reversed as "banana”
- the network database After querying the network database, after re-compare, it can be confirmed that the changed data fails to pass the audit. At this time, in order to simplify the program and prevent entry into an infinite loop, the corresponding data can be directly discarded.
- the item to be identified is “orange”
- the collected picture information is queried after querying the database due to factors such as light and dark changes of light.
- the identification information corresponding to the item is mistaken as “orange”
- the picture information of the "orange” and the matching identification information are further sent to the refrigerator for display through the display interface of the refrigerator.
- Modifying the picture information displayed on the display interface and the matching identification information for example, changing the identification information of the picture information corresponding to "orange” from “orange” to “orange”; and further reversing the identification information as "orange”
- the modified data is confirmed to pass the audit, and then the picture information and the identification information of the item to be identified acquired at the time are updated to the network database.
- the number of times threshold may be set. After the user end modifies the identification information given by the network database N times in a time period, if the N is greater than or equal to the threshold number, the user end Set to maliciously operate the client and restrict it from making changes to the data for a certain period of time, so I won't go into details here.
- an update period of the network database 500 may also be set, for example, 1 hour, 1 day, one week, etc., or the administrator of the network database 500 may periodically update according to requirements. After the network database 500 receives the corresponding update information, the corresponding update information is stored first, and then the data is uniformly updated under the set update period. Thus, the calculation amount is reduced, and details are not described herein.
- the administrator of the network database 500 may also detect the validity of the uploaded data, and then perform a corresponding update operation. I will not go into details here.
- the image information may be processed according to the updated network database 500.
- the data stored in the network database 500 is increased to ensure the background. The accuracy of food identification.
- the network database 500 of the present invention is uniformly managed through the network, so that a better service can be provided according to the needs of the customer, and at the same time, the push content can be added to the refrigerator of the user terminal through the network database 500, which is convenient. Unified management.
- the smart refrigerator control method and control system of the present invention identifies and matches image information of an item to be identified based on a network; further, updates a network database based on data generated during use of the refrigerator, when regenerated When the new image information is processed, it can be processed according to the updated network database, so that the data stored in the network database is increased by the data fed back by the user-side refrigerator to ensure the accuracy of the background food identification, and further Improve user experience.
- a smart refrigerator configured to employ a control method in accordance with any of the embodiments of the present invention; and/or configured to include a control system in accordance with any of the embodiments of the present invention.
- the modules described as separate components may or may not be physically separated.
- the components displayed as modules may or may not be physical modules, that is, may be located in one place, or may be distributed to multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
- each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated in one In the module.
- the above integrated modules can be implemented in the form of hardware or in the form of hardware plus software function modules.
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Data Mining & Analysis (AREA)
- General Physics & Mathematics (AREA)
- Library & Information Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- Thermal Sciences (AREA)
- Cold Air Circulating Systems And Constructional Details In Refrigerators (AREA)
Abstract
Description
Claims (12)
- 一种用于智能冰箱的控制方法,包括:通过网络接收冰箱发送的待识别物品的图像信息;以接收的待识别物品的图像信息查询网络数据库,获取与其匹配的标识信息;将所述标识信息通过网络发送至冰箱,以通过冰箱的显示界面显示。
- 根据权利要求1所述的控制方法,还包括若接收到确认信息,所述确认信息为所述待识别物品的图像信息和输出至冰箱的标识信息的匹配结果正确;将所述待识别物品的图像信息及标识信息对应更新至所述网络数据库。
- 根据权利要求1所述的控制方法,还包括:若接收到确认信息,所述确认信息为所述待识别物品的图像信息和输出至冰箱的标识信息的匹配结果错误;为所述待识别物品的图像信息配置正确的标识信息,并将所述待识别物品的图像信息以及对应的正确的标识信息更新至网络数据库。
- 根据权利要求1所述的控制方法,其中以接收的待识别物品的图像信息查询网络数据库,获取与其匹配的标识信息后,所述方法还包括:将所述待识别物品的图像信息和标识信息一一进行匹配,并同步发送至冰箱,以通过冰箱的显示界面显示。
- 根据权利要求2所述的控制方法,还包括:对在冰箱的显示界面显示的所述待识别物品的图像信息以及对应的标识信息借助所述网络数据库进行反向审核,若通过审核,则更新所述网络数据库。
- 一种用于智能冰箱的控制系统,包括:数据获取模块,用于通过网络接收冰箱发送的待识别物品的图像信息;查询处理模块,用于以接收的待识别物品的图像信息查询网络数据库,获取与其匹配的标识信息;输出模块,用于将所述标识信息通过网络发送至冰箱,以通过冰箱的显示界面显示。
- 根据权利要求6所述的控制系统,其中所述查询处理模块还用于:若接收到确认信息,所述确认信息为所述待识别物品的图像信息和输出至冰箱的标识信息的匹配结果正确;将所述待识别物品的图像信息及标识信息对应更新至所述网络数据库。
- 根据权利要求6所述的控制系统,其中所述查询处理模块还用于:若接收到确认信息,所述确认信息为所述待识别物品的图像信息和输出至冰箱的标识信息的匹配结果错误;为所述待识别物品的图像信息配置正确的标识信息,并将所述待识别物品的图像信息以及对应的正确的标识信息更新至网络数据库。
- 根据权利要求6所述的控制系统,其中所述输出模块还用于:将所述待识别物品的图像信息和标识信息一一进行匹配,并同步发送至冰箱,以通过冰箱的显示界面显示。
- 根据权利要求6所述的控制系统,其中所述查询处理模块还用于:对在冰箱的显示界面显示的所述待识别物品的图像信息以及对应的标识信息借助所述网络数据库进行反向审核,若通过审核,则更新所述网络数据库。
- 一种智能冰箱,其配置成采用权利要求1所述的控制方法。
- 一种智能冰箱,其配置成包括权利要求6所述的控制系统。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| EP16901039.4A EP3438577B1 (en) | 2016-05-06 | 2016-12-30 | Control method and control system for identifying items stored in an intelligent refrigerator |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610302282.X | 2016-05-06 | ||
| CN201610302282.XA CN105953520B (zh) | 2016-05-06 | 2016-05-06 | 智能冰箱控制方法及其控制系统 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2017190518A1 true WO2017190518A1 (zh) | 2017-11-09 |
Family
ID=56914470
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/CN2016/113927 Ceased WO2017190518A1 (zh) | 2016-05-06 | 2016-12-30 | 智能冰箱及其控制方法和控制系统 |
Country Status (3)
| Country | Link |
|---|---|
| EP (1) | EP3438577B1 (zh) |
| CN (1) | CN105953520B (zh) |
| WO (1) | WO2017190518A1 (zh) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112861684A (zh) * | 2021-01-29 | 2021-05-28 | 北京电解智科技有限公司 | 一种物品展示方法和装置 |
| CN114508895A (zh) * | 2019-03-13 | 2022-05-17 | 青岛海尔电冰箱有限公司 | 用于冰箱的数据交互方法及交互系统 |
| CN115923020A (zh) * | 2022-11-17 | 2023-04-07 | 长虹美菱股份有限公司 | 一种冰箱柜箱体发泡防差错系统及方法 |
| CN116629285A (zh) * | 2023-07-24 | 2023-08-22 | 长沙智医云科技有限公司 | 一种rfid温度导入智能冰箱的管理方法 |
Families Citing this family (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105953520B (zh) * | 2016-05-06 | 2018-08-10 | 青岛海尔股份有限公司 | 智能冰箱控制方法及其控制系统 |
| CN107062794A (zh) * | 2017-03-29 | 2017-08-18 | 青岛海尔股份有限公司 | 智能冰箱,其控制方法及控制系统 |
| CN107665247B (zh) * | 2017-09-19 | 2020-12-25 | 北京奇艺世纪科技有限公司 | 一种物品召回方法、装置及电子设备 |
| CN110955791A (zh) * | 2018-09-27 | 2020-04-03 | 上海小蚁科技有限公司 | 物品入库、物品信息检索方法及装置、存储介质、终端 |
| CN109784193A (zh) * | 2018-12-20 | 2019-05-21 | 上海扩博智能技术有限公司 | 用于智能冰箱的终端数据采集装置及系统 |
| CN110013197A (zh) * | 2019-04-16 | 2019-07-16 | 上海天诚通信技术股份有限公司 | 一种扫地机器人物体识别方法 |
| CN112988765B (zh) * | 2019-12-02 | 2023-11-03 | 青岛海尔电冰箱有限公司 | 冰箱保鲜模型数据更新方法、设备及存储介质 |
| CN113465251B (zh) * | 2020-05-28 | 2022-10-18 | 海信集团有限公司 | 智能冰箱及食材识别方法 |
| CN113468936A (zh) * | 2020-06-23 | 2021-10-01 | 青岛海信电子产业控股股份有限公司 | 一种食材识别方法、装置和设备 |
| CN112270217A (zh) * | 2020-10-13 | 2021-01-26 | 深圳拓邦股份有限公司 | 应用于智能家电设备的本地图像识别装置、系统及方法 |
| CN113065394B (zh) * | 2021-02-26 | 2022-12-06 | 青岛海尔科技有限公司 | 用于图像识别物品的方法、电子设备及存储介质 |
| CN118168234B (zh) * | 2024-05-11 | 2024-09-10 | 苏州零距云控人工智能科技有限公司 | 可精确分析光影数据的智能统计冰箱 |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001349661A (ja) * | 2000-06-05 | 2001-12-21 | Sharp Corp | 冷蔵庫 |
| KR20120117464A (ko) * | 2011-04-15 | 2012-10-24 | 엘지전자 주식회사 | 냉장고 및 냉장고의 제어방법 |
| CN103604273A (zh) * | 2013-11-13 | 2014-02-26 | 四川长虹电器股份有限公司 | 智能冰箱食品管理的方法 |
| CN103604271A (zh) * | 2013-11-07 | 2014-02-26 | 四川长虹电器股份有限公司 | 一种基于智能冰箱的食品识别方法 |
| CN104197632A (zh) * | 2014-09-19 | 2014-12-10 | 合肥美的电冰箱有限公司 | 一种智能调温冰箱 |
| EP2843336A1 (en) * | 2013-09-03 | 2015-03-04 | Panasonic Corporation | Refrigerator and refrigerator system for monitoring food |
| CN104896868A (zh) * | 2015-06-18 | 2015-09-09 | 合肥美菱股份有限公司 | 一种根据远程图像识别管理冰箱食品列表的方法 |
| CN105953520A (zh) * | 2016-05-06 | 2016-09-21 | 青岛海尔股份有限公司 | 智能冰箱控制方法及其控制系统 |
| CN106016892A (zh) * | 2016-05-24 | 2016-10-12 | 青岛海尔股份有限公司 | 智能冰箱控制方法及其控制系统 |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014031976A1 (en) * | 2012-08-23 | 2014-02-27 | Medchain Systems, Inc. | Smart storage of temperature sensitive pharmaceuticals |
| WO2016036015A1 (en) * | 2014-09-04 | 2016-03-10 | Samsung Electronics Co., Ltd. | Refrigerator and controlling method thereof |
-
2016
- 2016-05-06 CN CN201610302282.XA patent/CN105953520B/zh active Active
- 2016-12-30 WO PCT/CN2016/113927 patent/WO2017190518A1/zh not_active Ceased
- 2016-12-30 EP EP16901039.4A patent/EP3438577B1/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001349661A (ja) * | 2000-06-05 | 2001-12-21 | Sharp Corp | 冷蔵庫 |
| KR20120117464A (ko) * | 2011-04-15 | 2012-10-24 | 엘지전자 주식회사 | 냉장고 및 냉장고의 제어방법 |
| EP2843336A1 (en) * | 2013-09-03 | 2015-03-04 | Panasonic Corporation | Refrigerator and refrigerator system for monitoring food |
| CN103604271A (zh) * | 2013-11-07 | 2014-02-26 | 四川长虹电器股份有限公司 | 一种基于智能冰箱的食品识别方法 |
| CN103604273A (zh) * | 2013-11-13 | 2014-02-26 | 四川长虹电器股份有限公司 | 智能冰箱食品管理的方法 |
| CN104197632A (zh) * | 2014-09-19 | 2014-12-10 | 合肥美的电冰箱有限公司 | 一种智能调温冰箱 |
| CN104896868A (zh) * | 2015-06-18 | 2015-09-09 | 合肥美菱股份有限公司 | 一种根据远程图像识别管理冰箱食品列表的方法 |
| CN105953520A (zh) * | 2016-05-06 | 2016-09-21 | 青岛海尔股份有限公司 | 智能冰箱控制方法及其控制系统 |
| CN106016892A (zh) * | 2016-05-24 | 2016-10-12 | 青岛海尔股份有限公司 | 智能冰箱控制方法及其控制系统 |
Non-Patent Citations (1)
| Title |
|---|
| See also references of EP3438577A4 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114508895A (zh) * | 2019-03-13 | 2022-05-17 | 青岛海尔电冰箱有限公司 | 用于冰箱的数据交互方法及交互系统 |
| CN112861684A (zh) * | 2021-01-29 | 2021-05-28 | 北京电解智科技有限公司 | 一种物品展示方法和装置 |
| CN115923020A (zh) * | 2022-11-17 | 2023-04-07 | 长虹美菱股份有限公司 | 一种冰箱柜箱体发泡防差错系统及方法 |
| CN116629285A (zh) * | 2023-07-24 | 2023-08-22 | 长沙智医云科技有限公司 | 一种rfid温度导入智能冰箱的管理方法 |
| CN116629285B (zh) * | 2023-07-24 | 2023-10-13 | 长沙智医云科技有限公司 | 一种rfid温度导入智能冰箱的管理方法 |
Also Published As
| Publication number | Publication date |
|---|---|
| EP3438577B1 (en) | 2025-11-05 |
| CN105953520A (zh) | 2016-09-21 |
| EP3438577A4 (en) | 2019-05-08 |
| CN105953520B (zh) | 2018-08-10 |
| EP3438577A1 (en) | 2019-02-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2017190518A1 (zh) | 智能冰箱及其控制方法和控制系统 | |
| CN106016892B (zh) | 智能冰箱控制方法及其控制系统 | |
| US11120311B2 (en) | Adjusting machine settings through multi-pass training of object detection models | |
| US10559194B2 (en) | System and method for providing customized connected device functionality and for operating a connected device via an alternate object | |
| US10168675B2 (en) | Industrial machine management system, industrial machine management device, industrial machine management method, and information storage medium | |
| CN105243060B (zh) | 一种检索图片的方法及装置 | |
| US20170206439A1 (en) | Providing Image Search Templates | |
| US20220012523A1 (en) | Repair diagnostic system and method | |
| WO2020026643A1 (ja) | 情報処理装置、情報処理方法及び情報処理プログラム | |
| CN105091491A (zh) | 智能冰箱的食品管理方法及装置 | |
| CN110825973A (zh) | 场景和联动的推荐方法及系统、存储介质和网络侧设备 | |
| WO2021028442A1 (en) | An automated support system for connected devices | |
| CN113269828A (zh) | 物品查找方法、装置、空调设备和存储介质 | |
| CN107563467A (zh) | 物品寻找方法和装置 | |
| CN107578018A (zh) | 基于情感识别的试衣满意度处理方法、系统及智能试衣镜 | |
| CN112770126A (zh) | 直播间的推送方法、装置、服务器及存储介质 | |
| CN114417988A (zh) | 操作信息的确定方法和装置、存储介质及电子装置 | |
| CN112183914B (zh) | 一种菜项的评价方法及装置 | |
| CN112458695B (zh) | 洗涤方法、装置、电子设备及可读存储介质 | |
| CN105933744B (zh) | 遥控终端配对方法、装置及终端 | |
| CN112269894B (zh) | 物品池生成方法、图片搜索方法、装置、电子设备及介质 | |
| CN113296680A (zh) | 菜品图片上传方法、装置、计算机设备及可读存储介质 | |
| CN111435511B (zh) | 订单处理方法、装置、设备、系统及可读存储介质 | |
| CN114898842A (zh) | 一种食物营养成分的处理方法、装置以及存储介质 | |
| CN114511380A (zh) | 用于确定物品属性的方法和装置 |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| WWE | Wipo information: entry into national phase |
Ref document number: 2016901039 Country of ref document: EP |
|
| NENP | Non-entry into the national phase |
Ref country code: DE |
|
| ENP | Entry into the national phase |
Ref document number: 2016901039 Country of ref document: EP Effective date: 20181102 |
|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 16901039 Country of ref document: EP Kind code of ref document: A1 |
|
| WWG | Wipo information: grant in national office |
Ref document number: 2016901039 Country of ref document: EP |