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Managing Inventory System and Method (Tech Patents and Software Patents)

Patent no: 11,983,672
Issued: May 14, 2024
Attorney: Michael Feigin

Abstract

There are provided methods and systems for managing inventory of inventory items in a storage area, and for automatically carrying out an action in response to a change in at least one inventory item in the storage area.

Claims

1. A method for managing inventory in a storage area associated with a user, the storage area housing a plurality of inventory items and having a plurality of sensors associated therewith, the method comprising: responsive to at least one triggering event, receiving a first input signal from a first sensor of said plurality of sensors and a second input signal from a second sensor of said plurality of sensors; uniquely identifying one of said plurality of inventory items based on said first input signal and second input signal, wherein each of said first input signal and said second input signal is insufficient, on its own, for facilitating unique identification of said one of said plurality of inventory items; based on at least one of said first input signal and said second input signal, identifying a change in said one of said plurality of inventory items; and in response to said identifying said change, automatically purchasing said one of said plurality of inventory items, said automatically purchasing occurring at a time of said identifying or being scheduled to occur at a future time at which said at least one inventory item is predicted to expire or to be consumed, wherein said first input signal is selected from the group consisting of: a photospectrometry signal; a raman spectrometry signal; a material oscillation measurement signal; a magnetic resonance measurement signal; a dynamic pressure signal indicative of a kinetic wave decay pattern; a dynamic pressure signal indicative of a pattern of material oscillations or vibrations; and a kinetic wave decay signal, wherein said at least one triggering event is detected by at least one triggering sensor, and includes at least one of: movement of at least one inventory item within said storage area; removal of at least one inventory item from said storage area; insertion of at least one storage item into said storage area; and a change in pressure distribution within said storage area, wherein the user is associated with at least one segment of users, the at least one segment of users including a plurality of users sharing at least one common characteristic with the user, at least one of said plurality of users being associated with a different inventory than the inventory of said user, wherein said uniquely identifying said one of said plurality of inventory items is further based on segment-specific information for said at least one segment of users, wherein said segment-specific information is learned over time using machine-learning techniques by a machine learning module, based on information received from said user and from other users in said segment of users, and wherein said segment-specific information is common to at least a majority of users in said at least one segment of users.

2. The method of claim 1, wherein said identifying said change further comprises processing said first and second signals together with user-specific information learned over time using machine-learning techniques to identify said change.

3. The method of claim 1, wherein said second signal is selected from the group consisting of: an image signal; a pressure signal; a time based signal; a calendar based signal; an optical signal; a radio frequency signal; a photospectrometry signal; a raman spectrometry signal; a material oscillation measurement signal; a magnetic resonance measurement signal; a kinetic wave decay signal; an ultrasonic signal; and a chemical signal.

4. The method of claim 1, wherein said triggering sensor is one of said plurality of sensors, and is distinct from said first sensor and from said second sensor.

5. The method of claim 1, wherein said first input signal is a photospectrometry signal.

6. The method of claim 1, wherein said first input signal is a raman spectrometry signal.

7. The method of claim 1, wherein said first input signal is a material oscillation measurement signal.

8. The method of claim 1, wherein said first input signal is a magnetic resonance measurement signal.

9. The method of claim 1, wherein said first input signal is a kinetic wave decay signal.

10. The method of claim 1, wherein said first input signal is a dynamic pressure signal indicative of a kinetic wave decay pattern.

11. The method of claim 1, wherein said first input signal is a dynamic pressure signal indicative of a pattern of material oscillations or vibrations.

12. The method of claim 1, wherein said first image signal and said second input signal relate directly to one of said plurality of inventory items in said storage area.

13. The method of claim 2, wherein said user-specific information learned over time includes information relating to a consumption rate of said one of said plurality of inventory items.

14. The method of claim 2, wherein said user-specific information learned over time includes information relating to a specific location in the storage area of said one of said plurality of inventory items.

15. The method of claim 2, wherein said user-specific information learned over time includes information relating to a purchasing pattern of said one of said plurality of inventory items.

16. The method of claim 2, wherein said user-specific information learned over time includes information relating to a use pattern of said one of said plurality of inventory items.

Description

Background/Summary
 

 

RELATED APPLICATIONS (1) The present application is a continuation of U.S. patent application Ser. No. 15/814,966, filed Nov. 16, 2017 and entitled “A system and a Method for Managing Inventory”, which gains priority from U.S. Provisional Patent Application 62/423,338, filed 17 Nov. 2016 and entitled “A System and a Method for Tracking Inventory Using Sensors and Computer Vision Techniques”. Both U.S. application Ser. No. 15/814,966 and Provisional Patent Application No. 62/423,338 are incorporated herein by reference as if fully set forth herein.
 

 

FIELD AND BACKGROUND OF THE INVENTION

(1) The invention, in some embodiments, relates to the field of managing inventory, and more particularly to methods and systems for automatically tracking inventory and consumption rates of inventory items and carrying out one or more actions based on identified changes in inventory.

(2) In many homes and businesses, the quantity of different products, or inventory items, needs to be tracked in order to determine which items need to be replenished and should be purchased, and for which items there is a sufficient quantity, so as to ensure proper stocking of the home or business and to prevent waste. Such determination is often time consuming, and is prone to errors.

(3) The ability to gauge inventory levels automatically, without user interaction, is complex, as it requires an identification of a package of a product within a storage area and monitoring of a quantity of the product within the package. This requires an understanding of the dimensions and contents of packages, which have posed a significant challenge to developers to date.

(4) Additionally, one of the actions users perform when checking inventory, is determining the usability of the remaining product for example, when users check whether they need to buy milk, they typically check not only how much milk they have, but also when that milk will expire, or how long that milk will be usable. As such, an automatic system must also determine whether or not the identified product is usable, or for how long the product will remain useable, in order to determine the effective inventory of the product.

(5) There is thus a need in the art for an inventory gauging system and method which automatically identifies an inventory item, gauges its effective inventory by determining the available quantity and the usability of that quantity of the inventory item, and carries out an action, such as purchasing the inventory item, reminding the user to discard an inventory item, or providing an advertisement for a corresponding inventory item, in response to identification of the effective inventory.

SUMMARY OF THE INVENTION

(6) Some embodiments of the invention relate to methods and systems for managing inventory, such as identifying inventory items in a storage area, gauging an effective quantity or inventory of the inventory items or a change in the inventory items, and carrying out an action in response to such gauging.

(7) In accordance with a first aspect of the present invention, there is provided a method for managing inventory in a storage area of a user, the storage area housing at least one inventory item and having a plurality of sensors associated therewith, the method including: receiving at least a first input signal from a first sensor of the plurality of sensors and a second input signal from a second sensor of the plurality of sensors, the first sensor and the second sensor being sensors of different types and the first input signal and the second input signal being signals of different types; processing first and second signals, based on the first and second input signals, respectively, together with user-specific information learned over time using machine-learning techniques to identify a change in at least one inventory item in the storage area; based on the identified change, carrying out at least one action, the at least one action including at least one of: adding the at least one inventory item to an inventory replenishment list; removing the at least one inventory item from an inventory replenishment list; updating a data repository to reflect the change to the at least one inventory item; purchasing the at least one inventory item; predicting a time at which the at least one inventory item will expire; predicting a time at which the at least one inventory item will be consumed; providing to the user an advertisement for an inventory item corresponding to or useable instead of the at least one inventory item; providing to the user an indication that the at least one inventory item has expired; and providing to the user a recommendation to discard or to add the at least one inventory item.

(8) In some embodiments of the first aspect, at least the first signal is selected from the group consisting of: a photospectrometry input signal; a raman spectrometry input signal; a material oscillation measurement signal; a magnetic resonance measurement signal; a kinetic wave decay signal; an ultrasonic signal; and a chemical signal.

(9) In accordance with a second aspect of the present invention, there is provided a method for managing inventory in a storage area, the storage area housing at least one inventory item and having a plurality of sensors associated therewith, the method including: receiving a first input signal from a first sensor of the plurality of sensors and a second input signal from a second sensor of the plurality of sensors; processing first and second signals, based on the first and second input signals, respectively, to identify a change in at least one inventory item in the storage area; based on the identified change, carrying out at least one action, wherein the first input signal is selected from the group consisting of: a photospectrometry input signal; a raman spectrometry input signal; a material oscillation measurement signal; a magnetic resonance measurement signal; a kinetic wave decay signal; an ultrasonic signal; and a chemical signal, and based on the identified change, carrying out at least one action, the at least one action including at least one of: adding the at least one inventory item to an inventory replenishment list; removing the at least one inventory item from an inventory replenishment list; updating a data repository to reflect the change to the at least one inventory item; purchasing the at least one inventory item; predicting a time at which the at least one inventory item will expire; predicting a time at which the at least one inventory item will be consumed; providing to the user an advertisement for an inventory item corresponding to or useable instead of the at least one inventory item; providing to the user an indication that the at least one inventory item has expired; and providing to the user a recommendation to discard the at least one inventory item.

(10) In some embodiments of the second aspect, the first sensor and the second sensor are sensors of different types and the first input signal and the second input signal are signals of different types. In some such embodiments, the processing further includes processing the first and second input signals together with user-specific information learned over time using machine-learning techniques to identify the change.

(11) In some embodiments of the first and second aspects, the second signal is selected from the group consisting of: an image signal; a pressure signal; a time based signal; a calendar based signal; an optical signal; a radio frequency signal; a photospectrometry input signal; a raman spectrometry input signal; a material oscillation measurement signal; a magnetic resonance measurement signal; a kinetic wave decay signal; an ultrasonic signal; and a chemical signal.

(12) In some embodiments of the first and second aspects, the user-specific information learned over time includes at least one of: information relating to a consumption rate of the at least one inventory item; information relating to a specific location in the storage area of the at least one inventory item; information relating to a purchasing pattern of the at least one inventory item; and information relating to a use pattern of the at least one inventory item.

(13) In some such embodiments, the information relating to a consumption rate includes at least one of: a time from purchase by which the at least one inventory item is consumed; and a number of times the at least one inventory item is removed from the storage area until the at least one inventory item is consumed.

(14) In some such embodiments, the information relating to a specific location includes a storage location in the storage area, assigned by a user of the storage area to the at least one inventory item.

(15) In some such embodiments, the information relating to a purchasing pattern includes at least one of: information relating to a frequency at which the at least one inventory item is purchased; information relating to a quantity of the at least one inventory item which is purchased when the at least one inventory item is purchased; information relating to a quantity of the at least one inventory item available in the storage area when an additional quantity of the at least one inventory item is purchased; information relating to a minimum threshold quantity of the at least one inventory item; and information relating to a maximum threshold quantity of the at least one inventory item.

(16) In some such embodiments, the information relating to a use pattern of the at least one inventory item includes at least one of: information relating to a number of times the at least one inventory item is used before it is consumed; information relating to a quantity of the at least one inventory item consumed in a pre-defined time unit; information relating to a change in a use pattern of the at least one inventory item based on availability or consumption of at least one other inventory item; information relating to at least one other inventory item which may be interchanged with the at least one inventory item; information relating to at least one other inventory item consumed or used together with the at least one inventory item; and information relating to a quantity of the at least one inventory item consumed in a single use of the at least one inventory item.

(17) In some embodiments of the first and second aspects, the user is associated with at least one segment of users, wherein segment-specific information for the at least one segment of users is learned over time using machine-learning techniques, and wherein the processing is also based on segment-specific information learned over time. In some such embodiments, the segment specific information includes at least one of: information relating to a consumption rate of the at least one inventory item; information relating to a specific location in the storage area of the at least one inventory item; information relating to a purchasing pattern of the at least one inventory item; and information relating to a use pattern of the at least one inventory item.

(18) In some embodiments of the first and second aspects, the processing is also based on item-specific information relating to characteristics of the at least one inventory item, item-specific information is learned over time using machine learning techniques. In some such embodiments, the item-specific information includes at least one of: information relating to one or more dimensions of the at least one inventory item; information relating to a footprint of the at least one inventory item; information relating to a color of the at least one inventory item; information relating to a barcode of the at least one inventory item; information relating to an expected expiration date of the at least one inventory item; information relating to a shape of the at least one inventory item; and information relating to an initial weight of the at least one inventory item.

(19) In some embodiments of the first and second aspects, processing the first and second signals further includes, prior to identifying the change, processing at least the first and second signals to uniquely identify the at least one inventory item in the storage area. In some embodiments, processing the first and second signals to uniquely identify the at least one inventory item further includes using data obtained from a data repository including information about inventory items to uniquely identify the at least one inventory item.

(20) In some embodiments, using data obtained from a data repository includes using data obtained from a user-specific data repository including information about inventory items used by the user, and wherein the at least one action further includes updating the user-specific data repository with information relating to the at least one inventory item. In some embodiments, using data obtained from a data repository includes using data obtained from a segment-specific data repository including information about inventory items used by uses in a segment of users with which the user is associated. In some embodiments, using data obtained from a data repository includes using data obtained from an inventory-item data repository including information about characteristics of inventory items.

(21) In some embodiments of the first and second aspects, the change in the at least one inventory item includes at least one of: a reduction in the number of units of the at least one inventory item; a reduction in the weight of the at least one inventory item; a reduction in the volume of the at least one inventory item; an increase in the number of units of the at least one inventory item; an increase in the weight of the at least one inventory item; an increase in the volume of the at least one inventory item; removal of the at least one inventory item from the storage area; insertion of the at least one inventory item into the storage area; a change in the location of the at least one inventory item within the storage area; and a change in the orientation of the at least one inventory item within the storage area.

(22) In some embodiments of the first and second aspects, the storage area includes at least one of: a portion of a pantry; a portion of a refrigerator; a portion of a freezer; a portion of a cabinet; and a container.

(23) In some embodiments of the first and second aspects, receiving the first and second input signals occurs periodically. In some embodiments of the first and second aspects, receiving the first and second input signals occurs intermittently.

(24) In some embodiments of the first and second aspects, receiving the first and second input signals is responsive to at least one triggering event. In some such embodiments, the at least one triggering event includes at least one of: a change in an environment of the storage area; movement of at least one inventory item within the storage area; removal of at least one inventory item from the storage area; insertion of at least one inventory item into the storage area; opening or closing of the storage area; a change in pressure distribution within the storage area; and disruption of an electronic circuit associated with the storage area.

(25) In some embodiments of the first and second aspects the method further includes, following receiving and prior to processing, pre-processing the first and second input signals to obtain the first and second signals.

(26) In some embodiments of the first and second aspects, processing the first and second signals based on the first and second input signals includes processing the first and second input signals.

(27) In accordance with the first aspect of the present invention, there is provided a system for managing inventory in a storage area of a user, the storage area housing at least one inventory item, the system including: a plurality of sensors functionally associated with the storage area; an input module adapted to receive at least a first input signal from a first sensor of the plurality of sensors and a second input signal from a second sensor of the plurality of sensors, the first sensor and the second sensor being sensors of different types and the first input signal and the second input signal being signals of different types; a learning module adapted to learn user-specific information over time using machine learning techniques; and a processor adapted to: receive at least two signals from the input module, the at least two signals being based on the first and second input signals; process the first and second signals together with the user-specific information to identify a change in at least one inventory item in the storage area; and based on the identified change, carry out at least one action, the at least one action including at least one of: adding the at least one inventory item to an inventory replenishment list; removing the at least one inventory item from an inventory replenishment list; updating a data repository to reflect the change to the at least one inventory item; predicting a time at which the at least one inventory item will expire; predicting a time at which the at least one inventory item will be consumed; purchasing the at least one inventory item; providing to the user an advertisement for an inventory item corresponding to or useable instead of the at least one inventory item; providing to the user, via a user interface associated with the system, an indication that the at least one inventory item has expired; and providing to the user, via the user interface associated with the system a recommendation to discard the at least one inventory item.

(28) In some embodiments of the first aspect, at least the first signal is selected from the group consisting of: a photospectrometry signal; a raman spectrometry signal; a material oscillation measurement signal; a magnetic resonance measurement signal; a kinetic wave decay signal; an ultrasonic signal; and a chemical signal.

(29) In accordance with the first aspect of the present invention, there is provided a system for managing inventory in a storage area of a user, the storage area housing at least one inventory item, the system including: a plurality of sensors functionally associated with the storage area; an input module adapted to receive at least a first input signal from a first sensor of the plurality of sensors and a second input signal from a second sensor of the plurality of sensors; a processor adapted to: receive at least two signals from the input module, the at least two signals being based on the first and second input signals; process the first and second signals to identify a change in at least one inventory item in the storage area; and based on the identified change, carry out at least one action, the at least one action including at least one of: adding the at least one inventory item to an inventory replenishment list; removing the at least one inventory item from an inventory replenishment list; updating a data repository to reflect the change to the at least one inventory item; predicting a time at which the at least one inventory item will expire; predicting a time at which the at least one inventory item will be consumed; purchasing the at least one inventory item; providing to the user an advertisement for an inventory item corresponding to or useable instead of the at least one inventory item; providing to the user, via a user interface associated with the system, an indication that the at least one inventory item has expired; and providing to the user, via the user interface associated with the system a recommendation to discard the at least one inventory item, wherein at least the first signal is selected from the group consisting of: a photospectrometry signal; a raman spectrometry signal; a material oscillation measurement signal; a magnetic resonance measurement signal; a kinetic wave decay signal; an ultrasonic signal; and a chemical signal.

(30) In some embodiments of the second aspect, the first sensor and the second sensor are of different types. In some embodiments of the second aspect, the system further includes a learning module functionally associated with the processor and adapted to learn user-specific information over time using machine learning techniques, wherein the processor is adapted to process the at least two signals together with the user-specific information to identify the change.

(31) In some embodiments of the first and second aspects, the second signal is selected from the group consisting of: an image signal; a pressure signal; a time based signal; a calendar signal; an optical signal; a radio frequency signal; a photospectrometry signal; a raman spectrometry signal; a material oscillation measurement signal; a magnetic resonance measurement signal; a kinetic wave decay signal; an ultrasonic signal; and a chemical signal.

(32) In some embodiments of the first and second aspects, the plurality of sensors includes at least one of: to an image sensor; a pressure sensor; a time of flight camera; a stills camera; a video camera; an optical-spectrometry sensor; a radio-frequency absorption spectrometry sensor; a Raman spectrometry system; a sensor adapted to detect the decay of a kinetic wave pattern; an ultrasonic sensor; a magnetic resonance measuring device; a USID reader; an RFID reader; a barcode reader; a QR code reader; a chemical sensing device; a mass spectrometer; a odor sensor; an air sampling device; and a vibration sensor.

(33) In some embodiments of the first and second aspects, the input module includes a pre-processing module, adapted to receive the first and second input signals, to pre-process the first and second input signals, and to provide the pre-processed input signals to the processor as the at least two signals.

(34) In some embodiments of the first and second aspects, the input module is adapted to provide the first input signal and the second input signal to the processor as the at least two signals.

(35) In some embodiments of the first and second aspects, the system further includes at least one light projector adapted to project light in the storage area during operation of at least one of the plurality of sensors.

(36) In some embodiments of the first and second aspects, the user-specific information learned over time includes at least one of: information relating to a consumption rate of the at least one inventory item; information relating to a specific location in the storage area of the at least one inventory item; information relating to a purchasing pattern of the at least one inventory item; and information relating to a use pattern of the at least one inventory item.

(37) In some such embodiments, the information relating to a consumption rate includes at least one of: a time from purchase by which the at least one inventory item is consumed; and a number of times the at least one inventory item is removed from the storage area until the at least one inventory item is consumed.

(38) In some such embodiments, the information relating to a specific location includes a storage location in the storage area, assigned by a user of the storage area to the at least one inventory item.

(39) In some such embodiments, the information relating to a purchasing pattern includes at least one of: information relating to a frequency at which the at least one inventory item is purchased; information relating to a quantity of the at least one inventory item which is purchased when the at least one inventory item is purchased; information relating to a quantity of the at least one inventory item available in the storage area when an additional quantity of the at least one inventory item is purchased; information relating to a minimum threshold quantity of the at least one inventory item; and information relating to a maximum threshold quantity of the at least one inventory item.

(40) In some such embodiments, the information relating to a use pattern of the at least one inventory item includes at least one of: information relating to a number of times the at least one inventory item is used before it is consumed; information relating to a quantity of the at least one inventory item consumed in a pre-defined time unit; information relating to a change in a use pattern of the at least one inventory item based on availability or consumption of at least one other inventory item; information relating to at least one other inventory item which may be interchanged with the at least one inventory item; information relating to at least one other inventory item consumed or used together with the at least one inventory item; and information relating to a quantity of the at least one inventory item consumed in a single use of the at least one inventory item.

(41) In some embodiments of the first and second aspects, the user is associated with at least one segment of users, the learning module is adapted to learn segment-specific information for the at least one segment of users over time using machine-learning techniques, and the processor is adapted to process the first and second signals also based on segment-specific information learned over time.

(42) In some such embodiments, the segment specific information includes at least one of: information relating to a consumption rate of the at least one inventory item; information relating to a specific location in the storage area of the at least one inventory item; information relating to a purchasing pattern of the at least one inventory item; and information relating to a use pattern of the at least one inventory item.

(43) In some embodiments of the first and second aspects, the learning module is adapted to learn item-specific information, relating to characteristics of the at least one inventory item, over time using machine learning techniques, and the processor is further adapted to process the first and second signals also based on the item-specific information.

(44) In some such embodiments, the item-specific information includes at least one of: information relating to one or more dimensions of the at least one inventory item; information relating to a footprint of the at least one inventory item; information relating to a color of the at least one inventory item; information relating to a barcode of the at least one inventory item; information relating to an expected expiration date of the at least one inventory item; information relating to a shape of the at least one inventory item; and information relating to an initial weight of the at least one inventory item.

(45) In some embodiments of the first and second aspects, the processor is further adapted, prior to identifying the change, to process at least the first and second signals to uniquely identify the at least one inventory item in the storage area. In some such embodiments, the system further includes at least one data repository including information about inventory items, the data repository functionally associated with the processor, wherein the processor is adapted to use data obtained from the data repository to uniquely identify the at least one inventory item.

(46) In some embodiments, the data repository includes a user-specific data repository including information about inventory items used by the user. In some embodiments, the data repository includes a segment-specific data repository including information about inventory items used by uses in a segment of users with which the user is associated. In some embodiments, the data repository includes an inventory-item data repository including information about characteristics of inventory items.

(47) In some embodiments of the first and second aspects, the change in the at least one inventory item includes at least one of: a reduction in the number of units of the at least one inventory item; a reduction in the weight of the at least one inventory item; a reduction in the volume of the at least one inventory item; an increase in the number of units of the at least one inventory item; an increase in the weight of the at least one inventory item; an increase in the volume of the at least one inventory item; removal of the at least one inventory item from the storage area; insertion of the at least one inventory item into the storage area; a change in the location of the at least one inventory item within the storage area; and a change in the orientation of the at least one inventory item within the storage area.

(48) In some embodiments of the first and second aspects, the first and second sensors are adapted to provide the first and second input signals periodically. In some embodiments of the first and second aspects, the first and second sensors are adapted to provide the first and second input signals intermittently.

(49) In some embodiments of the first and second aspects, the first and second sensors are adapted to provide the first and second input signals in response to at least one triggering event. In some such embodiments, the at least one triggering event includes at least one of: a change in an environment of the storage area; movement of at least one inventory item within the storage area; removal of at least one inventory item from the storage area; insertion of at least one inventory item into the storage area; opening or closing of the storage area; a change in pressure distribution within the storage area; and disruption of an electronic circuit associated with the storage area.

(50) Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention pertains. In case of conflict, the specification, including definitions, will take precedence.

(51) As used herein, the terms “including”, “including”, “having” and grammatical variants thereof are to be taken as specifying the stated features, integers, steps or components but do not preclude the addition of one or more additional features, integers, steps, components or groups thereof. These terms encompass the terms “consisting of” and “consisting essentially of”.

(52) As used herein, the indefinite articles “a” and “an” mean “at least one” or “one or more” unless the context clearly dictates otherwise.

(53) As used herein, when a numerical value is preceded by the term “about”, the term “about” is intended to indicate +/?10%.

(54) Embodiments of methods and/or devices of the invention may involve performing or completing selected tasks manually, automatically, or a combination thereof. Some embodiments of the invention are implemented with the use of components that include hardware, software, firmware or combinations thereof. In some embodiments, some components are general-purpose components such as general purpose computers or oscilloscopes. In some embodiments, some components are dedicated or custom components such as circuits, integrated circuits or software.

(55) For example, in some embodiments, some of an embodiment is implemented as a plurality of software instructions executed by a data processor, for example which is part of a general-purpose or custom computer. In some embodiments, the data processor or computer includes volatile memory for storing instructions and/or data and/or a non-volatile storage, for example, a magnetic hard-disk and/or removable media, for storing instructions and/or data. In some embodiments, implementation includes a network connection. In some embodiments, implementation includes a user interface, generally including one or more of input devices (e.g., allowing input of commands and/or parameters) and output devices (e.g., allowing reporting parameters of operation and results.
Description
 

 

BRIEF DESCRIPTION OF THE FIGURES

(1) Some embodiments of the invention are described herein with reference to the accompanying figures. The description, together with the figures, makes apparent to a person having ordinary skill in the art how some embodiments of the invention may be practiced. The figures are for the purpose of illustrative discussion and no attempt is made to show structural details of an embodiment in more detail than is necessary for a fundamental understanding of the invention. For the sake of clarity, some objects depicted in the figures are not to scale.

(2) In the Figures:

(3) FIG. 1 is a schematic depiction of an embodiment of a system for managing inventory in a storage area according to an embodiment of the teachings herein; and

(4) FIG. 2 is a flow chart of an embodiment of a method for managing inventory in a storage area according to an embodiment of the teachings herein.

DESCRIPTION OF SOME EMBODIMENTS OF THE INVENTION

(5) The invention, in some embodiments, relates to the field of managing inventory, and more particularly to methods and systems for automatically tracking inventory and consumption rates of inventory items and carrying out one or more actions based on identified changes in inventory.

(6) The principles, uses and implementations of the teachings herein may be better understood with reference to the accompanying description and figures. Upon perusal of the description and figures present herein, one skilled in the art is able to implement the invention without undue effort or experimentation.

(7) Before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not limited in its applications to the details of construction and the arrangement of the components and/or methods set forth in the following description and/or illustrated in the drawings and/or the Examples. The invention can be implemented with other embodiments and can be practiced or carried out in various ways. It is also understood that the phraseology and terminology employed herein is for descriptive purpose and should not be regarded as limiting.

(8) In the context of the present application, the term “inventory item” relates to any object which a user stocks in a home, retail, or commercial setting, including purchasable products, retail products, wholesale products, warehouse products, and manufacturing products, and may relate to products of any type, including for example groceries, electronics, health care products, cosmetic products, books, toys, games, and paper products.

(9) In the context of the present application the terms “feature” and “characteristic” may be used interchangeably, and, when applied to an inventory item, relate to any characteristic of the inventory item which provides information regarding the inventory item, and which may be used to uniquely identify the inventory item and/or to identify substitutes for the inventory item.

(10) In the context of the present application, the term “segment of users” relates to a group of users sharing at least one common characteristic, such as, for example, the segment of “children”, the segment of “vegetarians”, the segment of “people above the age of 65”, and the like. A segment may also be defined by the habits of the users, for example the segment of “all people who use at least three quarts of milk and at least a dozen eggs each week” or the segment of “all the users from California who tend to consume 2 gallons of orange juice, 3 packages of kale, and at least three cans of beans each week”. A single user may be associated with multiple segments. For example, a vegetarian child would be associated with the segment of children, with a segment of vegetarians, and with a segment of vegetarian children. Machine learning algorithms may use the common characteristic(s) of users in the segment to learn information, or make predictions, about each user within the segment. The association of a user to a segment may be based on information explicitly provided by the user, or may be automatically learned over time, for example based on the correlation of user-specific information with segment-specific information.

(11) In the context of the present application, the term “segment-specific information” relates to information which is common to at least a majority of users in a user segment, if not to all the users in a user segment. For example, the segment-specific information for vegan users may indicate that they never buy eggs or milk, and, at a high likelihood, buy beans and vegetables. Some segment-specific information may be inherent in the definition of the segment, for example, the users of the segment “all people who consume more than a gallon of milk per week” clearly consume a gallon of milk each week. Some segment-specific information may be learned automatically over time using machine learning techniques, while the association of a user to a segment may be based on information explicitly provided by the user, or may be learned over time.

(12) In the context of the present application, the term “user-specific information” relates to information which is specific to the user or the user's habits, and which is learned automatically using machine learning techniques and is not explicitly provided by the user.

(13) In the context of the present application, the term “effective inventory” relates to the usable amount of an item or product. In other words, the amount of the item or product which is available for use, and which is not expired, rotten, spoiled, or otherwise unusable. Frozen items which may be defrosted and then used are considered part of the effective inventory of the item.

(14) In accordance with the disclosed invention, inputs are received from various sensors located in one or more storage areas, such as pantries and refrigerators. The received inputs are analyzed together with additional information, in order to detect and/or calculate the current inventory of one or more inventory items in the storage area(s). The additional data used when analyzing the received input may include a user profile, information relating to user habits, information relating to one or more characteristics of the inventory item, and the like, to identify at least some of the products in the storage area(s), and to estimate the effective inventory of the identified products in the storage area(s).

(15) In some embodiments, input from at least two different types of sensors is used for identification of an inventory item and/or of its quantity or inventory. In some embodiments, input from at least two different types of sensor is required to make such an identification, because input from a single type of sensor is insufficient for accurate, or reasonably accurate, package identification and/or quantity estimation. The inventors have found that a combination of inputs from several types of sensors provides sufficient information to facilitate identification of the package and/or the quantity of the product therein with high probability.

(16) For example, if a partial barcode has been captured by an image sensor, and the partial barcode can represent two different items, gathering additional information regarding the weight of the item, for example by one or more pressure sensitive sensor arrays, may provide additional information and enable accurate identification of the item, at least in high probability. If one of the two items which may be represented by the partial barcode is typically light, such as a bag of potato chips, and the other item which may be represented by the partial barcode is typically heavy, such as a gallon of juice, the additional pressure information, which is indicative of the weight of the item, would facilitate identification of the item with a high probability. Specifically, if the sensed weight is greater than the weight of the bag of potato chips, the system could identify with certainty that the item is the gallon of juice.

(17) As another example, when a product has two package versions having similar color signatures but different package sizes, identification of the color signature of the package by visual sensors such as image sensors would be insufficient for accurate identification of the inventory item, and accurate identification could be facilitated by using additional input relating to the weight of the package.

(18) The identification of inventory items and monitoring of their quantity may also take into account information not sensed by sensors in the system, such as information relating to the user's habits. For example, the system may know that a user stores cereals and cookies on the same shelf, and is used to eating cereal in the morning. In the morning hours, the sensors provide input indicating that a package has been removed from the shelf, but the input is insufficient for determining whether the removed item was a package of cereal or a package of cookies. The processor may then associate a high probability score with the cereal item, indicating that it is more likely that the removed product was cereal, due to the fact that it is morning and that the information relating to the user's habits indicates use of cereal in the morning.

(19) In some cases, the identification of an inventory item, even using multiple different sensor inputs and/or sources of information, is not 100% certain, but rather is associated with a probability score indicating the probability that the identification is correct. In such cases, an action will be carried out only if the probability score is above an identification threshold, indicating that there is a high enough chance that the identification is correct. The identification threshold may be the same for all inventory items, or may be different for different inventory items. For example, if an inventory item is very expensive or is hard to store, it would be more important to ensure that the identification is correct before buying more of the item, whereas this would be less important for non-perishables that are regularly consumed by the user. The specific threshold used may be defined by the user, for example when setting up the system, may be learned over time, or may be a default value.

(20) When an item is taken out of its typical storage location in the storage area, this event can serve as an indication of consumption, and the system can use predefined settings and/or automatically learned information relating to the user's habits to identify a duration from removal of the product which is indicative of complete consumption of the product.

(21) The system may also use product-to-product associations, which can be predefined or may be automatically learned by the system, in order to identify inventory items. For example, if the system recognizes that an inventory item taken out by the user is either a jar of coffee or a package of chewing gum, and immediately thereafter detects removal from the storage area of paper cups, the system may conclude, based on information relating to the user's habits, to the habits of a segment of users, or to the habits of all users, that the user probably took the coffee and not the chewing gum.

(22) In some embodiments, the system may predict when an inventory item will be consumed, based on information relating to the user's habits. For example, if the sensor input indicates that there are three apples in the refrigerator, and the information relating to the user's habits indicates that the user eats two apples a day, the system will be able to predict that the apples would be consumed by the next day, and additional apples should be purchased.

(23) In some embodiments, the system may learn the features of a specific item and characteristic patterns of sensed input relating to the item by drawing conclusions regarding unknown or uncertain characteristics based on reliable input. For example, the system may automatically learn the weight of a product that has been identified with high probability by visual input, or the system may automatically learn to identify the package of a certain product that has been positively identified by its barcode.

(24) When an inventory item has been identified and its effective quantity assessed, and/or when there is a change to an inventory item, the system may automatically carry out an action associated with the inventory item or with the identified change. For example, when complete consumption of an inventory item is identified, the system may automatically add the inventory item to a grocery list of the user, present to the user a notification that the item has been consumed and should be purchased, or automatically purchase the inventory item using an online shopping system.

(25) Additionally, following identification of a change to an inventory item, the system may update one or more data repositories to reflect the identified change or statistics related thereto. For example, once the system identified a certain occasion in which a gallon of orange juice was consumed in two days, the system updates the average consumption rate for orange juice.

(26) Reference is now made to FIG. 1, which is a schematic depiction of an embodiment of a system 100 for managing inventory in a storage area 102 according to an embodiment of the teachings herein. The storage area includes at least one inventory item 101, illustrated in FIG. 1 as a plurality of inventory items.

(27) As seen in FIG. 1, the system 100 is functionally associated with a storage area 102, here shown as a refrigerator. However, the system may be associated with any suitable storage area, such as a portion of a refrigerator, a portion of a freezer, a portion of a pantry, a cabinet, a container, a portion of a room, or any other storage area used for storing inventory items.

(28) System 100 further includes a plurality of sensors 103, which are adapted to sense various characteristics of the storage area. The plurality of sensors 103 may include multiple sensors of a single type, or sensors of different types, as described herein. As explained in further detail hereinbelow, signals provided by the plurality of sensors 103 are used to identify inventory items in the storage area and/or gauge an effective quantity of inventory items in the storage area.

(29) In some embodiments, the plurality of sensors 103 includes one or more cameras or other image capturing sensors 104. Each such camera may be a video camera, a stills camera, or any other suitable type of camera. Each camera 104 is adapted to capture images of the storage area and of inventory items therein. Each camera 104 may be placed inside, above, below, or on a side of the storage area and may be used for collecting visual information related to inventory items in or near the storage area. In some embodiments, the plurality of sensors 103 includes multiple cameras 104 allowing images to be captured from multiple points of view, thereby providing additional information about the storage area and its contents.

(30) In some embodiments, one or more cameras 104 may be Time of Flight (ToF) cameras, which may be used for collecting information regarding the three dimensional features of objects and inventory items in the storage area.

(31) Each of cameras 104 may be stationary or may be mobile relative to the storage area. Mobile cameras 104 may automatically change location as needed, under the operation of a camera controller (not shown), so as to get a better of view of the storage area or of one or more specific inventory items therein.

(32) In some embodiments, the plurality of sensors 103 includes one or more pressure sensors 106, adapted to sense a pressure of one or more inventory items in the storage area. In some embodiments, the pressure sensor(s) 106 is provided in the base of the storage area, such as on a refrigerator or cabinet shelf, and senses the pressure applied to the base of the storage area by one or more inventory items. As explained in further detail hereinbelow, pressure signals provided by pressure sensor(s) 106 may be used to gauge the weight or mass of one or more inventory items in the storage area, and/or to provide input relating to the shape and/or footprint of an inventory item.

(33) In some embodiments, the plurality of sensors 103 includes at least one optical-spectrometry sensors 108, adapted to collect spectroscopic data, which provides fast and efficient analysis of food items, using a remote sampling capability to determine the components of the food items. In some embodiments, the optical-spectrometry sensor is an infrared spectrometry sensor adapted to collect spectroscopic data on the infra-red spectrum, which data can serve as an indication of the temperature of a sensed object. For example, infra-red spectroscopic data of an inventory item in the storage area may indicate the temperature of the inventory item.

(34) In some embodiments, the plurality of sensors 103 includes a radio-frequency absorption-spectrometry sensor 110, adapted to collect spectroscopic data.

(35) Spectroscopic signals provided by sensors 108 and/or 110 may be used to extract information regarding characteristics of an inventory item in the storage area, and/or regarding the content of an inventory item in the storage area.

(36) In some embodiments, the plurality of sensors 103 includes a Raman spectrometry system 112 adapted to collect data regarding the chemical composition of an object or inventory item, which may be used to validate the identification of an item, and/or to validate that the item is still usable.

(37) In some embodiments, the plurality of sensors 103 includes a sensor 114 that detects the decay of a kinetic wave pattern caused by an object when being placed on a surface. In some embodiments, the surface may be a base surface in the storage area on which inventory items may be placed, such as the surface of a shelf.

(38) In some embodiments, the plurality of sensors 103 includes an ultrasonic volumetric sensor 116, whose signals may provide information relating to the three-dimensional characteristics of a sensed object. Signals provided by sensor 116 may be used to extract information relating to the three dimensional shape and/or characteristics of inventory items in the storage area and/or to a content level of such inventory items. Sensor 116 is functionally associated with an ultrasound generator (not shown), which forms part of the system 100 in embodiments which include sensor 116.

(39) In some embodiments, the plurality of sensors 103 includes a magnetic resonance measuring device 118 adapted to collect magnetic resonance information from the storage area, which information may be used to extract information relating to the content of an inventory item in the storage area.

(40) In some embodiments, the plurality of sensors 103 includes an Ultra Sound Identification (USID) reader 120 and/or a Radio-Frequency Identification (RFID) reader 122. Such sensors are suitable for reading corresponding tags attached to inventory items in the storage area, so as to provide an identification of the inventory items.

(41) In some embodiments, the plurality of sensors 103 includes one or more chemical sensing devices 124, adapted to collect information about the environment in or near the storage area. For example, a chemical sensing device 124 may include a mass spectrometry apparatus adapted to provide information relating to the chemical structure of the inventory item. In some embodiments, the chemical sensing device may include an odor sensor, such as an “electronic nose” device, adapted to provide information about odors in the storage area, which may assist in identifying inventory items in the storage area, or indicate spillage of inventory items in the storage area.

(42) In some such embodiments, the system 100 may include a mechanism (not shown) for drawing air towards the chemical sensing device 124, such as a fume hood or any other type of air sampling apparatus, so as to enable device 124 to detect and sample air in or near the storage area.

(43) In some embodiments, the plurality of sensors 103 may include a system 126 for inducing vibrations or oscillations in an object and for sensing such vibrations. For example, such a system may include a sound or infrasound generator that can induce oscillations in an object, and a laser beam projector functionally associated with a dynamic pressure sensor adapted to detect the oscillation patterns. Detection of the oscillation patterns enables the system to detect the viscosity of the material, which can assist in identification of the material and in estimation of a quantity in a container.

(44) In some embodiments, the plurality of sensors 103 may include a time sensor 128, such as a clock and/or calendar.

(45) In some embodiments, system 100 may include additional sensors 130, which are not disposed in or near the storage area. For example, a camera may be disposed in or near a waste-basket or garbage can 132, and may monitor items discarded into the garbage can 132. Sensors 130 may provide information relating to discarded inventory items, thereby providing information regarding the effective inventory of those items.

(46) Signals obtained from the plurality of sensors 103, including any one or more of sensors 104, 106, 108, 110, 112, 114, 116, 118, 120, 122, 124, 126, and 130, are provided to an input module 136, which is functionally associated with a processor 140. The input unit may form part of the device housing processor 140, such as part of a computer or server, or may be a dedicated input unit communicating with processor 140 via a communication network

(47) In some embodiments, the input unit 136 may include a pre-processing module 138 which is adapted to receive input signals from the plurality of sensors 103, and to pre-process the received input signals to generate processed signals, which processed signals are transmitted to the processor 140 for further processing thereof. In other embodiments, the input unit 136 receives the input signals from the plurality of sensors 103, and transmits the received input signals to the processor 140 without any pre-processing.

(48) Processor 140 is adapted to uniquely identify inventory items in storage area 102, gauge an inventory level of such inventory items and/or identify a change in such inventory items, and initiate one or more actions in response to identification of such a change, as explained in detail hereinbelow.

(49) Processor 140 may form part of a dedicated device custom-made to implement the teachings herein, or may be a processor of any suitable computing device, such as, for example, a stationary, mobile, or wearable computing device (server, cell phone, PDA, smartphone, mobile computer, tablet computer, desktop computer, augmented reality glasses, smart watch). In some embodiments, the processor 140 is local to the storage area 102, as illustrated in FIG. 1. In other embodiments, the processor 140 is remote from the storage area 102, and communicates with additional components of the system 100 via a wired or wireless communication network.

(50) In some embodiments, processor 140 comprises a learning module 142, functionally associated with one or more data repositories 144, such as a user information database, an inventory item database, a user-segment database, and the like. The learning module 142 is adapted to use machine-learning techniques to learn user-specific information, segment-specific information, and/or item-specific information, over time, as explained in further detail hereinbelow. In some embodiments, information learned by the learning module 142 is used by processor 140, together with the received sensor signals or pre-processed sensor signals, to identify inventory items in storage area 102 and/or to identify changes to such inventory items, as explained in further detail hereinbelow.

(51) In some embodiments, processor 140 may be associated with a user interface 146. User interface 146 may be used for receiving input from the user, such as information relating to a user profile, and for providing information to a user, for example via a display of the user interface. User interface 146 may be any suitable user interface, such as a user interface including a display screen, a keyboard, and a mouse or other pointing utility. In some embodiments, the user interface 146 is a dedicated device, as described in Applicant's co-pending U.S. patent application Ser. No. 14/895,375 which is incorporated herein by reference as if fully set forth herein.

(52) In some embodiments, system 100 may further include a triggering module 150, functionally associated with one or more of the plurality of sensors 103, with the input module 136, and/or with the processor 140. The triggering module 150 is adapted to automatically activate some or all of the plurality of sensors 103, the input module, and/or the processor in response to a triggering event. In some embodiments, some of the sensors in the plurality of sensors 103 may also form part of the triggering module 150. Such sensors may be operative constantly, periodically, or intermittently, in order to sense a triggering event, and once a triggering event is sensed, may provide input signals to the input module as explained hereinbelow.

(53) For example, if the storage area is the freezer, the triggering module may include an electronic circuit which detects when the freezer is opened. When the freezer is opened (the triggering event occurs), it is assumed that a change is made to an item within the freezer, and as such the sensors are activated to collect information from the freezer and the processor is activated to identify the change.

(54) In other embodiments, the plurality of sensors 103 provide signals to the input module 136 without any triggering thereof. For example, the sensors may provide signals to the input module 136 periodically at an input rate, or intermittently. Different sensors may have different input rates, for example according to the complexity of the obtained signal.

(55) In some embodiments, system 100 further includes at least one illumination device 160, such as a light bulb, which may illuminate the storage area 102 during collection of information by the plurality of sensors 103. In some such embodiments, triggering module 150 also triggers operation of the illumination device 160.

(56) Reference is now additionally made to FIG. 2, which is a flow chart of an embodiment of a method for managing inventory in a storage area according to an embodiment of the teachings herein, for example using system 100 of FIG. 1.

(57) For use, at step 202 the input module 136 of system 100 receives input signals from at least two sensors of the plurality of sensors 103, and in some embodiments from all the sensors in the plurality of sensors 103. In some embodiments, the input signals include a first input signal received from a first sensor of the plurality of sensors, and a second input signal received from a second sensor of the plurality of sensors, where the first and second sensors are of different types.

(58) The signals received by the input module 136 include at least two input signals, each of which may be any one of: an image signal; a pressure signal; a time based signal; a calendar based signal; an optical signal; a radio frequency signal; a photospectrometry input signal; a raman spectrometry input signal; a material oscillation measurement signal; a magnetic resonance measurement signal; a kinetic wave decay signal; an ultrasonic signal; and a chemical signal.

(59) In some embodiments, at least one of the received input signals is one of: a photospectrometry input signal; a raman spectrometry input signal; a material oscillation measurement signal; a magnetic resonance measurement signal; a kinetic wave decay signal; an ultrasonic signal; and a chemical signal.

(60) In some embodiments, the plurality of sensors 103 provide the signals to the input module 136 periodically, at a sensing rate. For example, the sensors 103 may provide signals once every minute, once every half-hour, or once every hour. In some embodiments, the sensing rate may be specific for each sensor in the plurality of sensors, and need not be the same for all the sensors.

(61) In some embodiments, the plurality of sensors 103 provide the signals to the input module 103 intermittently.

(62) In some embodiments, the operation of the system 100 and/or of the plurality of sensors 103 is triggered at step 200, prior to step 202, and the system and sensors thereof are in a sleeping mode until such triggering. For example, triggering of the system may be carried out in response to at least one triggering event, which is generated by, or is sensed by, triggering module 150.

(63) In some embodiments, the triggering event may include a change in an environment of storage area 102, which is sensed by one or more suitable sensors included in the triggering module, such as a temperature sensor or a chemical sensor. For example, a change in the temperature in the refrigerator or freezer (storage area) may indicate that the door of the refrigerator or freezer has been opened, triggering the system 100 to begin operation to determine whether there has been a change to an inventory item in the storage area. As another example, a change in the odor felt by a chemical sensor in the storage area, may trigger the system 100 into operation to determine whether a change has occurred, such as for example addition of a new spice having a strong odor to the storage area, spillage of an item in the storage area (in which case the inventory of the item must be updated), or rotting of an item in the storage area (in which case the rotten item should be discarded and its effective inventory should be updated). As yet further examples, an illumination sensor may sense a change in the illumination in the storage area, which may be indicative of a change in the contents of the storage area, or of opening or closing of the storage area. Similarly, a sound sensor may sense a change in the storage area based on the sounds audible within the storage area, such as, for example, sounds within the storage area being louder when the door to the storage area is open, or footsteps approaching the storage area being indicative of a user approaching the storage area.

(64) In some embodiments, the triggering event may include motion in or near the storage area 102, which is sensed by a suitable sensor included in triggering module 150 and mounted in or near the storage location and/or in or near the garbage can 132. For example, a motion sensor may trigger operation of the system 100 following opening and/or closing of the storage location, or movement of an inventory item within the storage area 102. Such triggering may enable the system and/or sensors to operate only when at least one inventory item is expected to be in motion, and therefore a change to the at least one item can be expected. As another example, a USID tag or an RFID tag reader may read RFID tags mounted onto inventory items in the storage area 102, to detect a change in location, or motion, of the inventory item. Motion of inventory items within the storage area may also be detected by one or more cameras or other image capturing devices forming part of the triggering module 150.

(65) In some embodiments, the triggering event may include insertion of an inventory item into the storage area 102 or removal of an inventory item from the storage area 102. In some such embodiments, the triggering module may include USID and/or RFID tag readers, adapted to read USID and/or RFID tags attached to or embedded into the inventory items, which may be read by the tag reader(s) of the triggering module upon insertion into and/or removal from the storage area 102, or upon any other change to the inventory item bearing the tag. A change in the inventory items included within the storage area may also be detected by one or more cameras or other image capturing devices forming part of the triggering module 150.

(66) In some embodiments, the triggering event Back to patents

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