Abstract: Examples provide a fruit ripening rack having a plurality of chambers for on-site produce ripening at a retail location. A controller component generates predicted demand for ripened fruit on a selected date at a selected location based on transaction history data and/or seasonal demand. The controller component calculates the quantity of fruit based on the predicted demand. The controller component determines conditions within each chamber to accelerate ripening of the calculated quantity of one or more types of fruit to one or more selected levels of ripeness on the selected date. The conditions include amount of ethylene gas in each chamber, length of exposure to the ethylene gas, temperature inside the chamber and/or humidity level inside the chamber. The fruit ripening rack controls internal conditions within each chamber to provide variable fruit ripening in accordance with per-chamber configurations to satisfy predicted daily demand at the selected location.

Abstract: Examples provide a system for cold-chain compliant item selection. A set of perishable items are selected for retrieval by a user based on item data, cold-chain compliance score(s), and/or cold-chain compliance restrictions associated with each user. The selected set of items are assigned to the user for retrieval in accordance with a set of cold-chain compliance parameters, including a per-item maximum dwell-time specifying a maximum time interval between removal of a perishable item from a temperature-controlled display area and receipt of the perishable item at an intake area. A dwell-time is calculated for an item received at an intake area. The item is accepted if the per-item maximum dwell-time exceeds the calculated dwell-time and the item is rejected if the calculated dwell-time exceeds the per-item maximum dwell-time. An incentive is provided to the identified user based on a cold-chain compliance score for the user.

Abstract: Examples provide a system for dynamic allocation of supplemental space to items based on predicted variable demand. Item data is analyzed using a set of item selection criteria to identify an item located within a predetermined distance of available flex-space associated with a topstock shelf which has a predicted time-supply predicted to be less than a threshold time-supply during a predicted time-period. A portion of flex-space sufficient to increase the time-supply enough to meet the predicted increase in demand is identified. Additional instances of the item are assigned to the portion of the flex-space during the predetermined time-period. When an expiration date for the flex-space assignment occurs, remaining instances of the item in the portion of the flex-space are removed. The portion of the flex-space is assigned to a next item predicted to experience temporary context-dependent increased demand exceeding time-supply and/or capacity of permanent display space of the item.

Abstract: Examples provide a system for cold-chain compliant item selection. A set of perishable items are selected for retrieval by a user based on item data, cold-chain compliance score(s), and/or cold-chain compliance restrictions associated with each user. The selected set of items are assigned to the user for retrieval in accordance with a set of cold-chain compliance parameters, including a per-item maximum dwell-time specifying a maximum time interval between removal of a perishable item from a temperature-controlled display area and receipt of the perishable item at an intake area. A dwell-time is calculated for an item received at an intake area. The item is accepted if the per-item maximum dwell-time exceeds the calculated dwell-time and the item is rejected if the calculated dwell-time exceeds the per-item maximum dwell-time. An incentive is provided to the identified user based on a cold-chain compliance score for the user.

Abstract: Systems, methods, and machine readable media are provided for image-based replenishment. In exemplary embodiments, a system periodically obtains an image from one or more imaging devices in a facility of a selected rack of items among a group of racks. The system determines, based on the image, a first volume indicative of a volume of items on the rack. The system retrieves a sales forecast for the items on the selected rack and determines an expected second volume of items on the rack based on the sales forecast for the item. The system then determines whether the first volume is within a predetermined threshold of the second volume, and transmits instructions based on whether or not the first volume is determined to be within the predetermined threshold of the second volume.

Abstract: Examples provide a system for cold-chain compliant item selection. A set of perishable items are selected for retrieval by a user based on item data, cold-chain compliance score(s), and/or cold-chain compliance restrictions associated with each user. The selected set of items are assigned to the user for retrieval in accordance with a set of cold-chain compliance parameters, including a per-item maximum dwell-time specifying a maximum time interval between removal of a perishable item from a temperature controlled display area and receipt of the perishable item at an intake area. A dwell-time is calculated for an item received at an intake area. The item is accepted if the per-item maximum dwell-time exceeds the calculated dwell-time and the item is rejected if the calculated dwell-time exceeds the per-item maximum dwell-time. An incentive is provided to the identified user based on a cold-chain compliance score for the user.

Abstract: Examples provide a perpetual inventory (PI) reconciliation system. A PI controller analyzes item data using a set of PI purge criteria and a set of weighted prioritization variables to select a highest priority seasonal inventory item having a positive PI value a per-item threshold time after an end-of-season (EOS) date for PI purge analysis. A PI controller determines if the selected item is a high confidence item or a low confidence item based on a set of confidence rules and item data. If the selected item is a high confidence item, a PI purge component sets an inventory value for the selected item to zero to eliminate the positive PI. If the selected item is a low confidence item, a verification component verifies the number of physical instances of the selected item. The inventory value is updated using the verified number of physical instances.

Abstract: Systems, methods, and machine readable media are provided for image-based replenishment. In exemplary embodiments, a system periodically obtains an image from one or more imaging devices in a facility of a selected rack of items among a group of racks. The system determines, based on the image, a first volume indicative of a volume of items on the rack. The system retrieves a sales forecast for the items on the selected rack and determines an expected second volume of items on the rack based on the sales forecast for the item. The system then determines whether the first volume is within a predetermined threshold of the second volume, and transmits instructions based on whether or not the first volume is determined to be within the predetermined threshold of the second volume.

Abstract: A parking space allocation system comprises a special-purpose allocation computer that communicates with at least one electronic sensor to identify a state of a plurality of parking spaces, including a determination whether the parking spaces are occupied or unoccupied and that automatically modifies an unoccupied parking space to be visually identifiable for authorized use by a vehicle or vehicle occupant; and a special-purpose authorization computer that authenticates the vehicle or vehicle occupant for the authorized use of the unoccupied parking space by the vehicle. The special-purpose allocation computer further allocates the unoccupied parking space to the authenticated vehicle or vehicle occupant according to a predetermined criterion that requires the unoccupied parking space to be in proximity to or a predetermined distance from a destination of interest by the vehicle occupant.

Abstract: Examples provide a fruit ripening rack having a plurality of chambers for on-site produce ripening at a retail location. A controller component generates predicted demand for ripened fruit on a selected date at a selected location based on transaction history data and/or seasonal demand. The controller component calculates the quantity of fruit based on the predicted demand. The controller component determines conditions within each chamber to accelerate ripening of the calculated quantity of one or more types of fruit to one or more selected levels of ripeness on the selected date. The conditions include amount of ethylene gas in each chamber, length of exposure to the ethylene gas, temperature inside the chamber and/or humidity level inside the chamber. The fruit ripening rack controls internal conditions within each chamber to provide variable fruit ripening in accordance with per-chamber configurations to satisfy predicted daily demand at the selected location.

Abstract: Examples provide a fruit ripening drawer for ripening fruit at variable rates in multiple air-tight compartments staggering completion of fruit ripening within each compartment. A user selects a level of ripeness and a date for consumption for fruit within each compartment. A calculation component calculates customized settings for each compartment, including an amount of ethylene gas, temperature, duration of gas exposure and/or humidity within each compartment. A metering device delivers the calculated amount of ethylene gas into each compartment. A thermostat device controls the temperature and/or humidity within each compartment. The fruit ripening drawer controls conditions within each compartment and duration of ethylene gas exposure to accelerate or delay fruit ripening within each compartment based on the user-selected level of ripeness and consumption date for fruit in each compartment. The fruit ripening drawer is a stand-alone counter-top device.

Abstract: Produce ripening systems and apparatuses are described. A produce ripening apparatus may include a sealed inner package positioned inside a sealed outer package. The sealed inner package may be breakable and may seal a ripening agent inside the sealed inner package. The sealed outer package may be openable and may have an elasticity sufficient to allow pressure to be applied to the sealed inner package through squeezing of the sealed outer package without breaking the sealed outer package. The pressure may be sufficient to break the sealed inner package.

Abstract: A bagging station, comprises a base; a carousel that rotates relative to the base, the carousel including a plurality of bag holding elements; an indicator at each bag holding element that provides a status regarding a bag hanging from the bag holding element; and a bag selection system that controls the indicators to identify bags for allocating items according to a predetermined criteria about at least one of the bag or the items.

Abstract: Examples provide a system for dynamic allocation of supplemental space to items based on predicted variable demand. Item data is analyzed using a set of item selection criteria to identify an item located within a predetermined distance of available flex-space associated with a topstock shelf which has a predicted time-supply predicted to be less than a threshold time-supply during a predicted time-period. A portion of flex-space sufficient to increase the time-supply enough to meet the predicted increase in demand is identified. Additional instances of the item are assigned to the portion of the flex-space during the predetermined time-period. When an expiration date for the flex-space assignment occurs, remaining instances of the item in the portion of the flex-space are removed. The portion of the flex-space is assigned to a next item predicted to experience temporary context-dependent increased demand exceeding time-supply and/or capacity of permanent display space of the item.

Abstract: Examples provide a system for crowdsourced item selection. A request fulfillment component selects a set of one or more items from a plurality of requested items for retrieval by an identified user. A set of items are selected based on an analysis of item data, per-user retrieval score(s), user-provided data, and/or per-user restriction(s). The request fulfillment component analyzes sensor data associated with a set of retrieved items received at an intake area to identify the items retrieved by the identified user and/or a level of compliance with retrieval criteria for the set of items. The request fulfillment component assigns a reward to the identified user, one or more retrieval scores ranking quality of items retrieved by the user, and/or one or more retrieval restrictions are assigned to the user based on the number of retrieved items and the level of compliance with the retrieval criteria.

Abstract: Examples provide a system for cold-chain compliant item selection. A set of perishable items are selected for retrieval by a user based on item data, cold-chain compliance score(s), and/or cold-chain compliance restrictions associated with each user. The selected set of items are assigned to the user for retrieval in accordance with a set of cold-chain compliance parameters, including a per-item maximum dwell-time specifying a maximum time interval between removal of a perishable item from a temperature controlled display area and receipt of the perishable item at an intake area. A dwell-time is calculated for an item received at an intake area. The item is accepted if the per-item maximum dwell-time exceeds the calculated dwell-time and the item is rejected if the calculated dwell-time exceeds the per-item maximum dwell-time. An incentive is provided to the identified user based on a cold-chain compliance score for the user.

Abstract: Examples provide a customized cart management system. A cart monitoring component monitors a location of one or more unattended carts outside a cart intake area. A cart intake component generates cart intake data for each cart returned to the cart intake area, including a cart identifier and a cart return time. A verification component analyzes the cart intake data using a set of reward criteria, including a minimum cart return time threshold, to determine if the user is eligible to receive a cart reward. If the user is eligible, an incentives generation component assigns a first reward to the identified user. A feedback query component outputs a feedback query associated with the one or more returned carts to a user device. If the user provides feedback in response to the feedback query, the incentives generation component assigns a second reward to the user.

Abstract: Examples provide a perpetual inventory (PI) reconciliation system. A PI controller analyzes item data using a set of PI purge criteria and a set of weighted prioritization variables to select a highest priority seasonal inventory item having a positive PI value a per-item threshold time after an end-of-season (EOS) date for PI purge analysis. A PI controller determines if the selected item is a high confidence item or a low confidence item based on a set of confidence rules and item data. If the selected item is a high confidence item, a PI purge component sets an inventory value for the selected item to zero to eliminate the positive PI. If the selected item is a low confidence item, a verification component verifies the number of physical instances of the selected item. The inventory value is updated using the verified number of physical instances.

Abstract: Described in detail herein are systems and methods for an data interception and transmission system. A wireless access point disposed in a facility can detect a mobile device in the facility executing an facility application associated with the facility. The wireless access point can intercept internet browsing data associated with one or more domains unrelated to a domain associated with the facility within a specified time interval from the mobile device. The computing system can receive the internet browsing data of the at least one mobile device. The computing system can detect information associated with a physical object. The computing system can determine the physical object is disposed in the facility. The computing system can control the operation of the facility application, residing on the mobile device, via the wireless access point to render information associated with the physical object on a display of the mobile device.