Food preparation appliance with tool for chopping
US-2019254481-A1 · Aug 22, 2019 · US
US12357128B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12357128-B2 |
| Application number | US-202017609394-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 20, 2020 |
| Priority date | May 6, 2019 |
| Publication date | Jul 15, 2025 |
| Grant date | Jul 15, 2025 |
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A food processing device adapted to identify an ingredient and an associated recipe. The device includes a container for receiving an ingredient to be processed and a blending blade located in the container. The device further includes a sensor for sensing characteristics of the ingredient received at the container, a processor for analyzing the characteristics, and a communications system for sending the characteristics to a remote data processing resource for analyzing or further analyzing, where the analyzing is for identifying ingredient types for a plurality of added ingredients and for identifying a recipe consistent with the added ingredient types. The device further includes an output device for guiding a user to follow remainder of the identified recipe.
Opening claim text (preview).
The invention claimed is: 1. A food processing device, comprising: a container to receive an ingredient to be processed; a blending blade located in the container; a sensor to sense characteristics of the ingredient received at the container; a processor to analyze the characteristics; a communications system to send the characteristics to a remote data processing resource to analyze the characteristics to identify ingredient types for a plurality of added ingredients and to identify a recipe consistent with the added ingredient types; and an output device to guide a user to follow a remainder of the identified recipe, wherein the sensor comprises a weight sensor, wherein the characteristics of the ingredient comprise a response curve generated by the weight sensor, wherein the response curve represents a weight detected by the weight sensor over time from receiving the ingredient at the container until equilibrium in the detected weight is reached, wherein the response curve includes oscillations in the detected weight of the ingredient between receiving the ingredient at the container and the equilibrium in the detected weight being reached, and wherein identification of the ingredient types comprises analyzation of the oscillations in the detected weight of the ingredient. 2. The food processing device as claimed in claim 1 , wherein the sensor further comprises a camera, and wherein the characteristics of the ingredient comprise a visual ingredient indicator generated by the camera. 3. The food processing device as claimed in claim 2 , further comprising: a base unit adapted to be removably coupled to the container, wherein the camera is located within the base unit; and a light guide adapted to direct light from an upper portion of the container to the camera. 4. The food processing device as claimed in claim 3 , wherein the container comprises a handle, and wherein at least a portion of the light guide is located within the handle. 5. The food processing device as claimed in claim 1 , wherein the sensor further comprises one or more of: a microphone, wherein the characteristics of the ingredient comprise an audio signal of the ingredient being received in the container; a torque sensor coupled to the blending blade, wherein the characteristics of the ingredient comprise a blending resistance; an electrical measurement sensor, wherein the characteristics of the ingredient comprise an ingredient impedance; a temperature sensor, wherein the characteristics of the ingredient comprise a temperature of the ingredient; and a gas sensor, wherein the characteristics of the ingredient comprise a gas composition of air within the container. 6. The food processing device as claimed in claim 1 , wherein the communications system is adapted to be in communication with a smart device of the user. 7. The food processing device as claimed in claim 1 , wherein the processor is adapted to apply a machine learning algorithm to the characteristics of the ingredient for analyzing said characteristics of the ingredient. 8. The food processing device as claimed in claim 1 , wherein the response curve is based on at least one of: the detected weight of the ingredient, elasticity of the ingredient, a shape of the ingredient, viscosity of the ingredient, and ingredients already present in the container. 9. A system for guiding a user according to a recipe identified based on an identified ingredient, the system comprising: one or more food processing devices as claimed in claim 7 ; a remote data processing resource coupled to the one or more food processing devices by way of the communications system, the remote data processing resource comprising a collaborative machine learning algorithm, wherein the system is adapted to: update the machine learning algorithm of the one or more food processing devices based on the collaborative machine learning algorithm; and upload the analyzed characteristics of the ingredient from the one or more food processing devices to the remote data processing resource for use in the collaborative machine learning algorithm. 10. A recipe guiding method, comprising: sensing characteristics of an ingredient when the ingredient is received in a container, the characteristics of the ingredient comprising a response curve generated by a weight sensor; analyzing the characteristics of the ingredient and communicating the characteristics of the ingredient to a remote data processing unit for further analyzing the characteristics of the ingredient; identifying an ingredient type of the ingredient received at the container based on the analysis of the characteristics of the ingredient; identifying a recipe based on the identified ingredient type; and guiding a user to follow a remainder of the identified recipe, wherein the response curve represents a weight detected by the weight sensor over time from receiving the ingredient at the container until equilibrium in the detected weight is reached, wherein the response curve includes oscillations in the detected weight of the ingredient between receiving the ingredient at the container and the equilibrium in the detected weight being reached, and wherein identifying the ingredient type comprises analyzing the oscillations in the detected weight of the ingredient. 11. The method as claimed in claim 10 , wherein identifying the ingredient type further comprises applying a machine learning algorithm to the ingredient characteristics. 12. The method as claimed in claim 11 , wherein the method further comprises: obtaining a collaborative machine learning algorithm from a remote data processing resource; and updating the machine learning algorithm based on the collaborative machine learning algorithm. 13. The method as claimed in claim 12 , wherein the method further comprises: obtaining a user input indicating whether the identified recipe has been followed; and if the user input indicates that the identified recipe has been followed, updating the collaborative machine learning algorithm based on the analyzed characteristics of the ingredient. 14. The method as claimed in claim 10 , wherein the method further comprises suggesting an additional ingredient based on the identified recipe. 15. The method as claimed in claim 10 , wherein the response curve is based on at least one of: the detected weight of the ingredient, elasticity of the ingredient, a shape of the ingredient, viscosity of the ingredient, and ingredients already present in the container. 16. A non-transitory computer readable recording medium storing a computer program comprising computer program code means which is adapted, when said computer program is run on a computer, to implement the steps of: obtaining sensed characteristics of an ingredient when the ingredient is received in a container, the characteristics of the ingredient comprising a response curve generated by a weight sensor; analyzing the characteristics of the ingredient and communicating the characteristics of the ingredient to a remote data processing unit for further analyzing the characteristics of the ingredient; identifying an ingredient type of the ingredient received at the container based on the analysis of the characteristics of the ingredient; identifying a recipe based on the identified ingredient type; and generating guidance for a user to follow a remainder of the identified recipe, wherein the response curve represents a weight detected by the weight sensor over time from receiving the ingredient at the container until equilibrium in the detected weight is reached,
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