CN110597139A - Self-learning method and system of cooking appliance - Google Patents
Self-learning method and system of cooking appliance Download PDFInfo
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- CN110597139A CN110597139A CN201910910490.1A CN201910910490A CN110597139A CN 110597139 A CN110597139 A CN 110597139A CN 201910910490 A CN201910910490 A CN 201910910490A CN 110597139 A CN110597139 A CN 110597139A
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- 238000010411 cooking Methods 0.000 title claims abstract description 87
- 238000000034 method Methods 0.000 title claims abstract description 28
- 230000000694 effects Effects 0.000 claims abstract description 17
- 235000019640 taste Nutrition 0.000 claims abstract description 13
- 238000010438 heat treatment Methods 0.000 claims description 19
- 230000035807 sensation Effects 0.000 claims 1
- 235000019615 sensations Nutrition 0.000 claims 1
- 235000013305 food Nutrition 0.000 abstract description 22
- 230000009246 food effect Effects 0.000 abstract description 2
- 235000021471 food effect Nutrition 0.000 abstract description 2
- 230000008901 benefit Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000013473 artificial intelligence Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000004580 weight loss Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 241000251468 Actinopterygii Species 0.000 description 1
- 240000008415 Lactuca sativa Species 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000004880 explosion Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 235000021485 packed food Nutrition 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 235000012045 salad Nutrition 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 235000013311 vegetables Nutrition 0.000 description 1
Classifications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
- G05B19/0428—Safety, monitoring
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/26—Pc applications
- G05B2219/2643—Oven, cooking
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Electric Ovens (AREA)
- Electric Stoves And Ranges (AREA)
Abstract
The invention discloses a self-learning method and a self-learning system for a cooking appliance. The method comprises the following steps: receiving an indication of a user input; finishing cooking according to an instruction input by a user; receiving the grade of the user on the cooking effect; and adjusting the cooking program according to the grade of the user, and recording the adjusted cooking program. The system comprises: a user instruction receiving unit for receiving an instruction input by a user; a cooking unit for completing cooking according to an instruction input by a user; the user score receiving unit is used for receiving the score of the user on the cooking effect; and the cooking program adjusting and recording unit is used for adjusting the cooking program according to the score of the user and recording the adjusted cooking program. After the work of the cooking product is finished, the method and the system need the user to provide feedback of food effect obtained by personal subjectivity and record the feedback, and the food is cooked according to the program automatically modified by the algorithm when the food is cooked next time, so that the program is gradually improved, and the best taste which is preferred by the user is expected to be achieved.
Description
Technical Field
The invention relates to an intelligent household appliance technology and an artificial intelligence technology, in particular to a self-learning method and a self-learning system for a cooking appliance.
Background
Patent document CN102200307A discloses an intelligent menu mode, which introduces a menu library function, and not only can classify, name, store and retrieve various menus of kitchen equipment, perform multi-polarization programming and dynamic cooking, and provide a function of replying default values of the system, but also adopts intelligent operation and control, and constructs a good man-machine interface, so that the intelligent menu mode has strong functions, fast cooking and improved food cooking quality.
Patent document No. CN109953657A discloses an intelligent cooking control method, in which an intelligent menu control database is pre-stored in an oven controller, and the intelligent menu control database is provided with preset food material weight loss ratios of different food material types after being cooked and before being cooked, when food is placed in a baking tray of an inner container and an intelligent menu cooking control program starts to be executed, the oven controller first obtains the food material type and the original weight which are mistakenly placed in the baking tray, and then bakes the food according to the intelligent menu cooking control program, and during the whole baking process, obtains whether the real-time weight loss ratio of the food in the baking tray is the same as the preset food material weight loss ratio, and if so, the baking is finished. Compared with the prior art, the intelligent menu cooking control program has the advantage that the optimal cooking effect of the intelligent menu cooking control program can be realized.
The above 2 patent documents lack the progressive development of self-learning performance, and only provide the user with the effect of preliminary intelligent cooking based on the original programming.
Disclosure of Invention
The invention aims to provide a self-learning method and a self-learning system for a cooking appliance, which are used for perfecting an intelligent menu library, cooking programs and parameters through continuous learning so as to achieve the best taste which is preferred by a user.
In order to solve the technical problems, the invention adopts the following technical scheme:
in one aspect, the present invention provides a self-learning method of a cooking appliance. The self-learning method of the cooking appliance includes: receiving an indication of a user input; completing cooking according to the instruction input by the user; receiving a user's score for the completed cooking effect; and adjusting the cooking program according to the grade of the user, and recording the adjusted cooking program.
Optionally, for a self-learning method of the cooking appliance, the score represents at least one of a different color, aroma, taste, and mouthfeel for a user; for a self-learning system, the score corresponds to at least one of total heating time, on and off time of heating power, temperature, and humidity.
Optionally, for the self-learning method of the cooking appliance, the receiving the indication of the user input comprises: receiving an indication of a user input through a human-machine voice dialog and/or receiving a user rating of a completed cooking effect comprises: and receiving the scores of the cooking effect of the user through man-machine voice conversation.
Optionally, the self-learning method for the cooking appliance further includes storing the adjusted cooking program to a cloud terminal through a wired connection and/or a wireless connection after recording the adjusted cooking program.
Optionally, for the self-learning method of the cooking appliance, when the adjusted cooking program is stored in the cloud via a wireless connection, the wireless connection includes WIFI.
In another aspect, the present invention provides a self-learning system for a cooking appliance. The self-learning system of the cooking appliance includes: a user instruction receiving unit for receiving an instruction input by a user; a cooking unit for completing cooking according to the instruction input by the user; a user score receiving unit for receiving a score of the user for the completed cooking effect; and the cooking program adjusting and recording unit is used for adjusting the cooking program according to the score of the user and recording the adjusted cooking program.
Optionally, for a self-learning system of the cooking appliance, the score represents at least one of a different color, aroma, taste, and mouthfeel for a user; for a self-learning system, the score corresponds to at least one of total heating time, on and off time of heating power, temperature, and humidity.
Optionally, for the self-learning system of the cooking appliance, the user indication receiving unit and/or the user rating receiving unit comprises a human-machine conversation voice module.
Optionally, the self-learning system of the cooking appliance further comprises a wired connection unit and/or a wireless connection unit.
Optionally, for the self-learning system of the cooking appliance, when the wireless connection unit is included, the wireless connection unit includes a WIFI module.
Compared with the prior art, the technical scheme of the invention has the following main advantages:
according to the self-learning method and the self-learning system for the cooking appliance, after the work of the cooking product is finished, a user is required to provide feedback of food effect obtained subjectively by the user and record the feedback, and the food is cooked according to the program automatically modified by the algorithm when the food is cooked next time, so that the software program is progressively improved, and the best taste which is preferred by the user is expected to be achieved. The human-computer conversation voice module is adopted, so that a user can directly communicate with a cooking appliance in a human-computer mode, the user provides information required by the cooking appliance, the cooking appliance works and heats according to a preset program according to the information, and an original interface set by the user for operation and control is weakened.
The self-learning method and the system of the cooking appliance provided by the embodiment of the invention can upgrade the program of the cooking equipment into a system with a function similar to artificial intelligence, can correct the contents such as menu cooking heating time, heating temperature, placing position, heat preservation temperature and the like set by the user in the process of continuously executing the cooking program according to the feedback of the user, and provide a better program for the next cooking so as to achieve the best taste which is preferred by the user. And a man-machine conversation interface is also provided, so that the original interface set and controlled by a user is weakened.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a flowchart illustrating a self-learning method of a cooking appliance according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a self-learning system of a cooking appliance according to another embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Fig. 1 is a flowchart illustrating a self-learning method of a cooking appliance according to an embodiment of the present invention. As shown in fig. 1, at step S110, an indication of a user input is received. As an alternative embodiment, the indication of user input may be received through a man-machine voice dialog. The man-machine interaction can be realized not through a display screen, a knob, a key and the like of the product, but through a higher-level voice module, such as a loudspeaker and a microphone, a user can realize the man-machine interaction through the most natural method, and the purpose of product control is realized.
In step S120, cooking is completed according to the instruction input by the user. The voice dialogue set by the program acts according to the requirement of the user on the premise of not violating the risk, communicates with the user language, knows the type, weight, quantity and maturity of the food cooked by the user, and then starts to heat according to the program set earlier according to the prompt of the user. Here, the non-offending risk includes 2 aspects, the first is to protect the personal safety of the user, such as that the microwave oven cannot heat the packaged food can (explosion), the oven cannot heat the bread-type food for a long time (fire), etc.; secondly, food cannot be cooked excessively, for example, fish steamed by a steam oven for a long time can be cooked excessively and lose the taste, vegetables or salad are baked by an oven, the temperature is too high, and the food is not appetized after being discolored.
In step S130, the user' S score for the cooking effect is received. As an alternative, the user's score for the cooking effect may be received through a man-machine voice conversation. And after the work is finished according to the temperature and time set by the program, prompting the user to score, and providing suggestions and modification contents of cooking effects.
In step S140, the cooking program is adjusted according to the score of the user, and the adjusted cooking program is recorded. The program modifies the internal parameters according to the algorithm set earlier by the program, generates a new food cooking program, and saves the newly generated food cooking program for the next use. The scores represent at least one of different color, aroma, taste, and mouthfeel for the user. For the self-learning system, the score corresponds to at least one of total heating time, on and off time of heating power, temperature, and humidity.
To take a specific example: the scoring design is numerically based, e.g., 1 to 5, or 1 to 9, with 1 lowest, 5 or 9 highest. Each number represents a level, a sense, each representing a color, aroma, taste and feel, and each corresponding scoring number in the program system corresponds to the total heating time, the on/off time of the heating power, the temperature and the humidity. And the program system adjusts the total heating time, the on-off time of heating and electrifying, the temperature and the humidity according to the scores. Then the user is prompted by voice that the program has been adjusted, the food is re-scored the next time it is cooked, and the system and the user compare the effect of the food after the program is adjusted and score again. By analogy, improvement is continuously carried out.
The self-learning method of the cooking appliance of the embodiment may further include storing the adjusted cooking program to a cloud terminal through wired connection and/or wireless connection after recording the adjusted cooking program. Further, the wireless connection may include WIFI. The cooking utensil can be connected with the cloud end through the WIFI, so that a manufacturer can update programs and correct BUG, and daily and monthly data of a user can be stored and backed up.
Fig. 2 is a schematic structural diagram of a self-learning system of a cooking appliance according to another embodiment of the present invention. The self-learning system 200 of the cooking appliance of the embodiment includes a user indication receiving unit 210, a cooking unit 220, a user score receiving unit 230, and a cooking program adjustment recording unit 240.
The user instruction receiving unit 210 is used for receiving an instruction input by a user.
The cooking unit 220 is used to complete cooking according to an instruction input by a user.
The user score receiving unit 230 is used for receiving the score of the user on the cooking effect.
The cooking program adjustment recording unit 240 is configured to adjust a cooking program according to the score of the user and record the adjusted cooking program.
As an alternative embodiment, the score represents at least one of a different color, aroma, taste, and mouthfeel for the user. For the self-learning system, the score corresponds to at least one of total heating time, on and off time of heating power, temperature, and humidity.
The user indication receiving unit 210 and/or the user score receiving unit 230 may include a man-machine conversation voice module. The man-machine conversation voice module receives information of a user through a microphone for example and starts to start, and after the user puts food into the cooking appliance, the man-machine conversation voice module receives requirements and prompts of the user and starts to start a cooking program.
The self-learning system 200 of the cooking appliance of the embodiment may further include a wired connection unit and/or a wireless connection unit. Further, the wireless connection unit may include a WIFI module.
Further, in a more specific example, the self-learning system 200 of the cooking appliance is a complete system, including input, output, storage, calculation, optimization algorithms, voice conversations, menu libraries, etc., and may be connected to the cloud via WIFI. Wherein the menu library comprises the variety, heating time and temperature, and weight of the dish.
The embodiment of the invention is used in the program of the cooking appliance by the artificial intelligence technology of the simple matching board, and is continuously upgraded and adjusted on the basis of the existing intelligent menu of the cooking appliance, so as to achieve the most suitable taste which is favored by the user, and enable the user to cook various delicious foods more easily.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the claims, and all equivalent structures or equivalent processes that are transformed by the content of the specification and the drawings, or directly or indirectly applied to other related technical fields are included in the scope of the claims.
Claims (10)
1. A self-learning method of a cooking appliance, comprising:
receiving an indication of a user input;
completing cooking according to the instruction input by the user;
receiving a user's score for the completed cooking effect;
and adjusting the cooking program according to the grade of the user, and recording the adjusted cooking program.
2. The self-learning method of a cooking appliance according to claim 1,
for the user, the scores represent at least one of different color, aroma, taste, and mouthfeel sensations;
for a self-learning system, the score corresponds to at least one of total heating time, on and off time of heating power, temperature, and humidity.
3. The self-learning method of a cooking appliance as claimed in claim 1, wherein receiving the indication of the user input comprises: receiving an indication of user input via a man-machine voice conversation, and/or
Receiving the user's score for the completed cooking effect includes: and receiving the grading of the finished cooking effect by the user through the man-machine voice conversation.
4. The self-learning method of a cooking appliance according to claim 1, further comprising storing the adjusted cooking program in a cloud via a wired connection and/or a wireless connection after recording the adjusted cooking program.
5. The self-learning method of a cooking appliance according to claim 4, wherein the wireless connection comprises WIFI when the adjusted cooking program is stored in the cloud via the wireless connection.
6. A self-learning system for a cooking appliance, comprising:
a user instruction receiving unit for receiving an instruction input by a user;
a cooking unit for completing cooking according to the instruction input by the user;
a user score receiving unit for receiving a score of the user for the completed cooking effect;
and the cooking program adjusting and recording unit is used for adjusting the cooking program according to the score of the user and recording the adjusted cooking program.
7. The self-learning system of a cooking appliance of claim 6, wherein the scores represent at least one of different color, aroma, taste and mouthfeel for the user;
for a self-learning system, the score corresponds to at least one of total heating time, on and off time of heating power, temperature, and humidity.
8. The self-learning system of a cooking appliance according to claim 6, wherein the user indication receiving unit and/or the user score receiving unit comprises a human-machine conversation voice module.
9. The self-learning system of a cooking appliance according to claim 6, further comprising a wired connection unit and/or a wireless connection unit.
10. The self-learning system of a cooking appliance of claim 9, wherein when the wireless connection unit is included, the wireless connection unit includes a WIFI module.
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CN201910910490.1A CN110597139A (en) | 2019-09-25 | 2019-09-25 | Self-learning method and system of cooking appliance |
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CN201910910490.1A CN110597139A (en) | 2019-09-25 | 2019-09-25 | Self-learning method and system of cooking appliance |
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Application publication date: 20191220 |