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US 11,448,632 B2Granted
System and method for the determination of produce shelf life
AssigneeWalmart Apollo, LLC
InventorsCkristian Velez, Mohit Mehrotra
Life of this patent
Estimating the term…
Abstract
A system and a method for the determination of product shelf life in a supply chain environment are discussed. The system receives periodic readings from various sensors that are associated with a shipment of produce. The system determines ambient deviations throughout the supply chain for temperature, humidity and ethylene. The system determines a product shelf life based on a calculated sensitivity and exposure to temperature, humidity, and ethylene. The system determines a remaining shelf life based on the determined product shelf life, and generates an event based on the remaining shelf life meeting a threshold. The system updates an indication of the remaining shelf life on a graphical interface for action.
Claims13
A system for determining a shelf life of produce within a supply chain comprising:
- a plurality of sensors distributed at a plurality of locations throughout a produce supply chain, the plurality of locations including an initial location at which the produce originated;
- an imaging sensor, wherein the imaging sensor is configured to capture images of the produce;
- a computing device communicatively coupled to the plurality of sensors and configured to execute a freshness indicator module, the freshness indicator module when executed:
- receiving periodic readings from the plurality of sensors associated with a shipment of produce,
- determining ambient deviations throughout the supply chain for temperature, humidity and ethylene from pre-defined criteria for the shipment of produce based at least in part on the periodic readings,
- calculating a sensitivity to temperature, a sensitivity to humidity, and a sensitivity to ethylene for the shipment of produce based at least in part on the periodic readings, wherein the calculation of the sensitivity to temperature, the sensitivity to humidity, and the sensitivity to ethylene for the shipment of produce is calculated using machine learning to periodically recalculate sensitivity based on additional readings received from the plurality of sensors,
- determining a product shelf life based on the calculated sensitivity to temperature in conjunction with an amount of time of temperature deviation and an amount of temperature deviation, the calculated sensitivity to humidity in conjunction with an amount of time of humidity deviation and an amount of humidity deviation, and the calculated sensitivity to ethylene in conjunction with an amount of time of ethylene deviation and an amount of ethylene deviation,
- capturing, via the imaging sensor, an image of the shipment of produce,
- determining a first set of characteristics within the image of the shipment of produce,
- comparing the first set of characteristics against a second set of characteristics consistent with a known condition of a control shipment of the produce,
- determining a remaining shelf life based on the determined product shelf life, an age of the shipment of produce, conditions of the shipment of product in transit, and the comparison of the first set of characteristics against the second set of characteristics, the remaining shelf life representing a time period the shipment of produce is fit for sale,
- generating an event based on the remaining shelf life meeting a threshold, and
- updating an indication of the remaining shelf life on a graphical user interface.
10 more elements
A method for determining shelf life of produce within a supply chain comprising:
- receiving periodic readings associated with a shipment of produce from a plurality of sensors distributed at a plurality of locations throughout a produce supply chain, the plurality of locations including an initial location at which the produce originated;
- determining ambient deviations throughout the supply chain for temperature, humidity and ethylene from pre-defined criteria for the shipment of produce based at least in part on the periodic readings;
- calculating a sensitivity to temperature, a sensitivity to humidity, and a sensitivity to ethylene for the shipment of produce based at least in part on the periodic readings, wherein the calculation of the sensitivity to temperature, the sensitivity to humidity, and the sensitivity to ethylene for the shipment of produce is calculated using machine learning to periodically recalculate sensitivity based on additional readings received from the plurality of sensors;
- determining a product shelf life based on the calculated sensitivity to temperature in conjunction with an amount of time of temperature deviation and an amount of temperature deviation, the calculated sensitivity to humidity in conjunction with an amount of time of humidity deviation and an amount of humidity deviation, and the calculated sensitivity to ethylene in conjunction with an amount of time of ethylene deviation and an amount of ethylene deviation;
- capturing, via an imaging sensor, an image of the shipment of produce;
- determining a first set of characteristics within the image of the shipment of produce;
- comparing the first set of characteristics against a second set of characteristics consistent with a known condition of a control shipment of the produce;
- determining a remaining shelf life based on the determined product shelf life, an age of the shipment of produce, conditions of the shipment of product in transit, and the comparison of the first set of characteristics against the second set of characteristics, the remaining shelf life representing a time period the shipment of produce is fit for sale;
- generating an event based on the remaining shelf life meeting a threshold;
- and
- updating an indication of the remaining shelf life on a graphical user interface.
8 more elements
A non-transitory computer readable medium holding instructions for determining shelf life of produce within a supply chain, the instructions when executed by a processor causing at least one computing device to:
- receive periodic readings associated with a shipment of produce from a plurality of sensors distributed at a plurality of locations throughout a produce supply chain, the plurality of locations including an initial location at which the produce originated;
- determine ambient deviations throughout the supply chain for temperature, humidity and ethylene from pre-defined criteria for the shipment of produce based at least in part on the periodic readings;
- calculate a sensitivity to temperature, a sensitivity to humidity, and a sensitivity to ethylene for the shipment of produce based at least in part on the periodic readings, wherein the calculation of the sensitivity to temperature, the sensitivity to humidity, and the sensitivity to ethylene for the shipment of produce is calculated using machine learning to periodically recalculate sensitivity based on additional readings received from the plurality of sensors;
- determine a product shelf life based on the calculated sensitivity to temperature in conjunction with an amount of time of temperature deviation and an amount of temperature deviation, the calculated sensitivity to humidity in conjunction with an amount of time of humidity deviation and an amount of humidity deviation, and the calculated sensitivity to ethylene in conjunction with an amount of time of ethylene deviation and an amount of ethylene deviation,
- capture, via an imaging sensor, an image of the shipment of produce;
- determine a first set of characteristics within the image of the shipment of produce;
- compare the first set of characteristics against a second set of characteristics consistent with a known condition of a control shipment of the produce;
- determine a remaining shelf life based on the determined product shelf life, an age of the shipment of produce, conditions of the shipment of product in transit, and the comparison of the first set of characteristics against the second set of characteristics, the remaining shelf life representing a time period the shipment of produce is fit for sale;
- generate an event based on the remaining shelf life meeting a threshold;
- and
- update an indication of the remaining shelf life on a graphical user interface.
8 more elements
Dependencies are inferred from the claim text.