Methods and systems for processing an order are disclosed. A unified shopping cart receives a first request from a first tenant interface and second request from a second tenant interface, different from the first tenant interface. Each request includes first request data including a customer identifier, a selection of one or more items, and a desired delivery mode. The first request and the second request are associated with the same customer, and are processed using a unified payment transaction.
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
The present disclosure provides methods and systems for tracking a shipping vessel travel route through a retail enterprise during a stock cycle. Location information associated with assets can be collected at a retail location, from which a detailed route through the retail location may be recreated and overlaid on map data reflecting a retail location layout. Further analysis may be performed on the route. Additionally, the route may be overlaid on a map, including product information and packaging information, allowing for various metrics and metric visualizations to be generated that can be further analyzed to achieve various objectives.
A clustering and routing platform that applies capacity constraints at individualized routes as part of the process of clustering deliveries into groups is provided. In particular, vehicle capacity, route length, route efficiency/timing, and various other constraints may be used as part of the clustering process to better group delivery locations into routes.
A stabilizer facilitates mounting an image sensor at an imaging device. The stabilizer removably holds the image sensor. The stabilizer is removably mounted to the imaging device. In certain examples, the image sensor is snap-fit to the stabilizer and the stabilizer is snap-fit to the imaging device. Certain imaging devices define a thermal regulation channel.
H04N 23/52 - Elements optimising image sensor operation, e.g. for electromagnetic interference [EMI] protection or temperature control by heat transfer or cooling elements
H04N 23/54 - Mounting of pick-up tubes, electronic image sensors, deviation or focusing coils
Methods, systems, and platforms for managing machine learning models are described. A model registry system receives first data including a model and second data including metadata and at least one metric of the model. Via a local network, the first data is stored to a data storage device and the second data is sent to an application programming interface (API). The first data is retrieved from the data storage device to a model use case program operating in a software development environment native to where the model registry system stores the model. The second data, including the metadata and the at least one metric of the model, is sent to a user interface (UI) via the API. The stored model can be deployed from the model use case program via the API.
In one embodiment, a storage container is disclosed. The storage container includes a plurality of sidewalls and a bottom wall operably coupled to the plurality of sidewalls. The bottom wall and the plurality of sidewalls together define a storage cavity. A storage container also includes a support bracket that transitions from a first position where the support bracket is contained within an exterior perimeter of the bottom wall to a second position where the support bracket extends past the exterior perimeter of the bottom wall. The support bracket may be used to support the storage container on an adjacent storage container, such that the storage container can be nested within an adjacent storage container or positioned above the adjacent storage container.
B65D 21/06 - Containers specially shaped, or provided with fittings or attachments, to facilitate nesting, stacking, or joining together with movable parts adapted to be placed in alternative positions for nesting the containers when empty and for stacking them when full
B65D 1/22 - Boxes or like containers with side walls of substantial depth for enclosing contents
Methods and systems for generating and distributing data visualizations are provided. One method includes displaying a user interface including a canvas and a card builder toolset, the card builder toolset including a plurality of selectable options, each of the plurality of selectable options responsive to user input to present a definition screen including one or more card definition parameter input fields. The method further includes receiving user input into the one or more card definition parameter input fields for each of the plurality of selectable options and, in response, defining at least one aspect of a card to be included within a user dashboard presented on the canvas. The method also includes rendering a card within the canvas in accordance with parameters defined by the user input, the card being included within a dashboard to be displayed to users.
The present application describes a method and systems for enterprise supply chain optimization by accounting for time, cost, product demand, capacity constraints, and other factors. The described application relates to solving for the optimal flow of products through a supply chain including overseas vendors and a selected set of import gateways by using a custom-built model based on linear programming techniques. The model described in the present disclosure relates to a model that optimizes the overall cost or time (or a balance of both cost and time) to ship products from origin ports to domestically located distribution centers. By doing so, the model also optimally allocates how shipping containers are sent to domestic ports. The model subsequently outputs the optimal flow, cost, and time for each route in the network, as well as providing other relevant output.
The disclosed technology provides for managing and delivering orders having special items to customers at an order fulfillment location. A method can include receiving, at a user device in a group of user devices, information that causes the user device to display a first graphical user interface (GUI) including a list of orders for customers for fulfillment at a fulfillment location, presenting, at the user device and for each order in the list, an amount of time that the order has been scanned out of a hold location and awaiting customer arrival, receiving, at the user device, instructions to update the first GUI based on a determination, for each order in the list, that the amount of time for the order exceeds a first threshold amount of time, and presenting, at the user device and based on the instructions, the order in the list in a first indicia.
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
A network based order fulfillment systems having an improved user interface at both a customer device and at an order fulfillment location employee device. Both customer and employee devices scan collect user input and other information using one or more sensors of the user devices to provide proper notifications to both the customer and the employee based on the actions of each. Location information for a customer computing device can be used to continually update ETA and time since arrival information displayed at the employee's computing device.
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 40/109 - Font handling; Temporal or kinetic typography
24.
VALIDATING, AGGREGATING, AND TRANSLATING CONFIGURATION CODE
In some implementations, a method performed by data processing apparatuses includes determining that a change has been made to interface configuration code of a service-providing platform. In response to determining that the change has been made, each interface configuration code unit of the interface configuration code of the platform can be validated. In response to successful validation of all of the interface configuration code units, an aggregated configuration code unit can be generated that includes computer code of each of the interface configuration code units, the aggregated configuration code unit can be translated into a computer language that is different from that of the interface configuration code units, and a translated configuration code unit can be generated. The translated configuration code unit can be used to configure the multiple different services of the platform.
A wiper heating device for selectively heating a wiper blade and wiper blade holder to melt snow and ice that has built up on each includes a wiper assembly comprising a wiper blade, a blade holder, and an arm. A blade heating element is embedded within and extends throughout the wiper blade, the blade heating element selectively heating the wiper blade. A holder heating element is embedded within and extends throughout the blade holder, the holder heating element selectively heating the blade holder. Each of the blade heating element and the holder heating element are electrically powered by a battery.
H01M 50/249 - Mountings; Secondary casings or frames; Racks, modules or packs; Suspension devices; Shock absorbers; Transport or carrying devices; Holders specially adapted for aircraft or vehicles, e.g. cars or trains
H01M 10/46 - Accumulators structurally combined with charging apparatus
H01M 50/298 - Mountings; Secondary casings or frames; Racks, modules or packs; Suspension devices; Shock absorbers; Transport or carrying devices; Holders characterised by the wiring of battery packs
The present application describes a system and method which may enable an enterprise to map existing planograms for a group of stores in order to facilitate a modification of an item category in a planogram for the stores. One or more planograms associated with a desired item category may be chosen, and a list of stores for the planogram(s) may be provided. From the list of stores having a common planogram allocated to the item category, a subset of stores may be chosen for which to change the planogram(s). Changes to a planogram may require the creation of a separate child planogram, in some examples. Updates to the child planograms may apply to all stores in the chosen subset of stores, to avoid a requirement of individual planogram edits.
In some implementations, a method performed by data processing apparatuses includes receiving stored map data corresponding to a digital map, identifying a discrepancy between the digital map and a physical space which the digital map represents, updating the digital map to correct the identified discrepancy, storing the updated digital map, and optionally providing the updated digital may for presentation on a device display.
The disclosed technology provides for implementing remediations to item listing data in an online retail environment. A method can include receiving, by a computing system from a data management system, a topic for a change in item listing data, retrieving, from a data store, at least one model trained to (i) identify changes in other item listing data, (ii) determine at least one suggested remediation to the changes to generate accurate item listing data, and (iii) determine at least one confidence metric indicating a likelihood that the at least one suggested remediation will result in generating the accurate item listing data, inputting the item listing data to the at least one model, receiving output from indicating at least one suggestion to remediate the item listing data, determining that the at least one suggestion satisfies auto-remediation criteria, and auto-remediating the item listing data with the at least one suggestion.
A recommendation system is disclosed. The recommendation system may receive a sequence of items selected by a user. Based on the sequence of items, the recommendation system may recommend one or more items. To do so, the recommendation system may apply a graph neural network. The recommendation system may receive a second sequence of items that includes the first sequence of items plus one or more items. Based on the second sequence of items, the recommendation system may recommend one or more different items by applying the graph neural network.
The present application describes a method of utilizing a mathematical model to determine appropriate locations for redistribution or drop-off of items with last mile delivery services at a consolidation point representing an intermediate sortation or warehousing in a retail enterprise's supply chain downstream of retail locations. Items may be brought from a consolidation point, such as a warehouse downstream of retail locations, to such a redistribution location (herein referred to as a “Transload” point). A last-mile delivery carrier may pick up items from the Transload point and deliver them to customer delivery locations in the geographical area served by the Transload point. In examples, relocation of selected deliveries from the consolidation point to a Transload point reduces the per-mile cost for last mile deliveries. A model uses candidate locations to assess optimal locations for such a Transload facility, for example, based on delivery locations and associated costs.
G06Q 10/08 - Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
35.
COMPUTER-VISION BASED DETECTION OF SCAMS AT PHYSICAL POINT OF SALE TERMINALS
The disclosed technology provides for detecting a scam attempt in a physical retail environment. A system can include a camera that captures image data of a checkout area, a cash register that generates event data during a checkout process, and an edge computing device that accesses scam detection criteria identifying combinations of visual and event features corresponding to checkout scams, receive the image data, receive the event data, which includes (i) an indication that the checkout process is a cash transaction and/or (ii) a cash register drawer open event, detect, based on processing the image data, physical movement of a form of payment in or around the checkout area, correlate timestamps for the physical movement with the event data, generate an indication of the checkout scams based on satisfying the scam detection criteria, and return the indication of the checkout scams being performed.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check of credit lines or negative lists
A system for managing and transferring a virtual shopping cart. The system includes a product identification system that is programmed to identify products from a product identification tag, a cart identification system that is configured to generate a cart identifier that uniquely identifies the virtual shopping cart, and a cart management engine. The cart management engine is configured to receive products to add to the virtual shopping cart from the product identification system, associate the products with the cart identifier, and transfer access to the virtual shopping cart from a first device to a second device.
A website vulnerability test is performed by automatically checking that a website has not been compromised by malicious third party scripts. A system can test a dynamic behavior of a website that indicates a functional user flow through the website. A set of rules are applied against a log of dynamic behavior of the website, as well as static code of the website, to identify potential compromise by malicious scripts. Some rules can be configured for detecting modification of a third party script, or modified behavior of a third party script, in an attempt to detect security monitoring activity against the script and hide its presence from the security monitoring activity.
The present application describes a database performance and usage footprint monitoring and analysis platform and related user application, which may provide insights across the whole of an enterprise's database inventory to increase visibility, accountability, and efficiency. The platform and related application may provide insight into enterprise database footprint and utilization, including displaying the data and associated metrics and analysis in a customizable interface. The platform may ingest and capture performance data and events to provide resource properties and cost analyses across enterprise groups. Future performance may be predicted by the platform, future data trends identified, and platform may provide usage prediction, perform root cause analysis to recommend action items, and provide alerts, among other functions. These improvements may reduce operational downtime, reactive events and efforts, and information gaps; enable informed business decisions; and make more efficient use of database resources.
G06F 16/21 - Design, administration or maintenance of databases
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
40.
IDENTIFYING BARCODE-TO-PRODUCT MISMATCHES USING POINT OF SALE DEVICES
Disclosed herein are systems and methods for determining whether an unknown product matches a scanned barcode during a checkout process. An edge computing device or other computer system can receive, from an overhead camera at a checkout lane, image data of an unknown product that is placed on a flatbed scanning area, identify candidate product identifications for the unknown product based on applying a classification model and/or product identification models to the image data, and determine based on the candidate product identifications, whether the unknown product matches a product associated with a barcode that is scanned at a POS terminal in the checkout lane. The classification model can be used to determine n-dimensional space feature values for the unknown product and determine which product the unknown product likely matches. The product identification models can be used to determine whether the unknown product is one of the products that are modeled.
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 20/52 - Surveillance or monitoring of activities, e.g. for recognising suspicious objects
G06F 18/2413 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
41.
SYSTEMS AND METHODS FOR USING ENTERPRISE IDP FUNCTIONALITY TO AUTHORIZE USER ACCESS ACROSS SERVERS
The disclosed technology provides for authenticating server access using enterprise credentials. A method can include authenticating, by a client computing device operating within an enterprise environment, a user with an enterprise identity provider (“IdP”) system that authenticates based on user enterprise credentials, receiving, in response to the user being authenticated, a bearer token from the system, transmitting the bearer token to a certificate service for use in obtaining a secure shell (“SSH”) certificate signed by an SSH certificate authority (“CA”) within the enterprise, receiving, at the client computing device, the signed SSH certificate, updating an SSH agent on the client computing device to use the SSH certificate with the enterprise identifier for the user, and remotely accessing any of a group of servers within the enterprise using the SSH certificate and enterprise identifier, where each server authenticates the remote access based on the SSH certificate signed by the SSH CA.
An order management tool, method, and system are disclosed. The order management tool can use clusters of two or more locations to generate fulfillment plans for orders. The order management tool can determine whether a cluster can fulfill an order and, if so, can determine, for each item of an order, a location within the cluster from which to send the item. The items may be consolidated at a sortation center. The locations can be stores and the clusters can cover a geographical area. The order management tool can also generate two fulfillment plans, one of which allocates the order within the cluster and one of which may use one or more locations outside of the cluster, and the order management tool can apply rules to compare the two fulfillment plans and select one of them.
The disclosed technology provides for generating best images of a person in a retail environment. A method may include receiving, by an edge computing device from a camera, a continuous stream of image data of the retail environment, detecting, using object detection techniques, a person in the image data, the image data including a group of images that are part of a time series, generating bounding boxes for each of the group of images around the person based on detecting the person as they move in the images, identifying, based on applying a features model to each bounding box, at least one feature of the group of images depicting the person, selecting a subset of the bounding boxes having at least one feature that satisfies best images criteria, the subset having best images of the person, and returning the best images of the person.
G06V 10/26 - Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
G06V 10/774 - Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
G06V 10/77 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
45.
AUTOMATIC ENTITY CREATION FOR USE IN KEYWORD FILTER OF ITEM REVIEWS
This disclosure relates to automatic creation and display of keyword filters useable to filter product reviews on an e-commerce website. One aspect is a method for generating entities for filtering item reviews, the method comprising extracting attributes for an item associated with a set of item reviews, generating a list of entities relevant to the item based on the set of item reviews and the extracted attributes for the item, ranking the list of entities based on a frequency of terms related to each entity in the set of item reviews, selecting at least one entity from the list of entities based on the ranking, and associating the at least one entity with the item.
The disclosed technology provides for for identifying items likely stolen from a physical retail environment, like a store, in an online marketplace. A method can include receiving, from item detection sensors in the store, item data indicating items leaving the store, receiving, from a checkout station, transaction data, identifying a subset in the item data that don't match items in the transaction data as an item shortage, grouping items in the subset into a cluster, retrieving, from a server system hosting an online marketplace, seller listing data including groups of items offered for sale associated with different online seller profiles, comparing the cluster to each of the groups to determine cluster similarity scores for the groups, and identifying, based on the cluster similarity scores, a particular group and a particular seller profile as having a greatest likelihood of listing the cluster of items for sale.
The present application describes a modeling process, model, and applications thereof which may provide a method for organizing and interpreting data related to online pick-up orders to predict future demand growth. The model may allow an enterprise such as a retail enterprise or a grocery enterprise to more efficiently anticipate increases in demand for online pick-up ordering; predict the overall staging area storage for each store; and more efficiently allocate retail space, refrigeration/freezer equipment, parking spots, staff, and other related resources to meet online pick-up ordering demand. In some examples, the disclosed model provides a method for predicting future pick-up demand and associated resource needs based on inputs such as historical financial data and unique store data. The outputs may be used by enterprise personnel to determine which and how many resources, such as refrigerator equipment, will be required to meet demand in a specified future time period.
Physical shopping carts can have product detection systems and associate physical shopping carts with mobile computing devices (e.g., smartphones, tablet computing devices, smart watches, wearable computing devices). For example, physical shopping carts can be equipped with one or more product detection systems (e.g., scanners, sensors, cameras) that can electronically tally products that are placed in physical shopping carts. Mobile computing devices can be associated with and mounted on the physical shopping carts to provide a variety of enhanced shopping cart features not possible with conventional physical shopping carts, such as electronically tracking the contents of a shopping cart, checking-out from the mobile computing device (instead of at conventional check-out areas, such as point of sale terminals), and others.
B62B 5/00 - Accessories or details specially adapted for hand carts
B62B 3/14 - Hand carts having more than one axis carrying transport wheels; Steering devices therefor; Equipment therefor characterised by provisions for nesting or stacking, e.g. shopping trolleys
51.
RISK-BASED ADAPTIVE RESPONSES TO USER ACTIVITY IN A RETAIL ENVIRONMENT
The disclosed technology provides for automatically detecting and responding to potentially suspicious or risky activity in a retail environment. A method can include receiving, from monitoring devices in a retail environment, a stream of activity data, applying a model to the stream of activity data to identify a portion of the data corresponding to guest activity during a checkout process, identifying whether a risk event is associated with the activity, determining a guest risk impact score, selecting (i) a particular manual response from among candidate manual responses and (ii) a particular automated response from among candidate automated responses based on the risk impact score satisfying manual response criteria and/or automated response criteria, transmitting instructions to a POS terminal to implement the particular automated response, and/or transmitting instructions to implement the particular manual response to one or more mobile devices, that prompt employees to perform the manual response.
The disclosed technology provides for determining whether to audit a shopper in a retail environment based on a trust score assigned to the shopper. A method can include receiving, by a computer system, shopper information including an identifier for the shopper, retrieving bag checkout history data associated with the shopper based on the identifier, which includes the shopper's trust score, determining a weighted probability score for the shopper based on the trust score and shopper trust score groupings, determining, using a randomization process, whether to perform a bag check on the shopper based on the weighted probability score, returning bag check instructions based on the determination, receiving bag check data from performing the bag check after the shopper completes checkout, adjusting the trust score based on the bag check history data and the bag check data, and providing the adjusted shopper trust score for use in the shopper's subsequent visits.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check of credit lines or negative lists
G06Q 30/0201 - Market modelling; Market analysis; Collecting market data
53.
INCREMENTAL VALUE ASSESSMENT TOOL AND USER INTERFACE
A tool, method, and system for assessing an incremental value of one or more items in an item assortment are disclosed. The tool can receive historical purchasing data, which can include a plurality of customers purchasing one or more items of a plurality of items in an item assortment. The tool can use the historical purchasing data for the plurality of customers to simulate execution of removal of an item from the item assortment, wherein removal of the item from the item assortment causes an incremental loss associated with the item. The tool can order any number of items of the historical purchasing data. The tool can execute scenario simulations, and the tool can account for probabilities when interacting with the historical purchasing data. The tool can display assessment data and receive inputs via an interactive user interface. The tool can launch the assessment data in a downstream application.
In some implementations, a computer-implemented method verifies item placed in physical shopping carts, using location data. An item verification engine receives an item scanned notification indicating that a mobile computing device has scanned an item, an item sensed notification indicating that a cart computing system has sensed the item being added to a shopping cart, item verification data that specifies an expected location of the scanned item, and actual location data that represents an actual location of the item in the retail environment. After receiving the item scanned notification, the item sensed notification, the item verification data, and the actual location data, a verification of the item is performed based at least in part on the item verification data and the actual location data. The item verification engine provides verification results based on performing the verification of the item, for receipt by the mobile computing device.
A multi-modal machine learning model is disclosed that may be implemented in a recommender system. The model may generate a multi-modal embedding based on a user query, one or more user-selected items, and a conversation history. The one or more user-selected items may include text data and visual data. In some embodiments, the recommender system may use the multi-modal embeddings to recommend one or more items of a plurality of items. In some embodiments, the multi-modal model may be integrated with other systems.
A method can include providing, by a computing system to a group of user devices, information to display a first graphical user interface (GUI) including a list of customer orders for fulfillment, receiving, from a first user device, selection of a control to prepare an order in the list, providing, to a subset of the group, instructions to update the first GUI to include an indication that the order is being prepared, providing, at the first user device, information to display a second GUI including indications of order hold locations and bags associated with the locations for the selected order, and receiving, from the first user device, identifying information for the bags, providing, to the first user device, instructions to update the second GUI such that the bag indications are updated from a first indicia to a second indicia.
The disclosed technology provides for performing website anomaly tests by automatically checking whether a website is compromised by malicious code. A system can test dynamic behavior of the website indicating a functional user flow through the website. A set of rules can be applied against a log of the behavior and static code of the website to identify potential compromises. A first rule can be satisfied based on identifying patterns of plain text encodings in portions of website event data. A second rule can be applied to the portions of event data representing information transmitted from a client device to a third party device. The second rule can be satisfied based on identifying third party account information that is not included in a whitelist of allowed third party accounts information. A likelihood of potential security vulnerability can also be determined based on the first and/or second rules being satisfied.
A processor on a computing device executes a monitoring module to perform steps that include sending a request to a baseboard management controller in the computing device to search for an event in an event log maintained by the baseboard management controller. A response is received from the baseboard management controller in response to the request and is used with a current state of the monitoring module to determine whether to send an event message to a central controller located on a network to indicate that the computing device is malfunctioning.
A swimwear garment configured to be worn by a wearer having buttocks, the swimwear garment comprising an outer rear layer and a rear compression layer. The outer rear layer defines rear portions of two leg openings and extends upwardly toward a waist of the swimwear garment in a manner configured to at least partially cover the buttocks of the wearer. The rear compression layer is coupled to the outer rear layer along an inside surface of the outer rear layer and defines a bottom periphery and opposing side edges. The rear compression layer extends upwardly from the bottom periphery to at least to the waist of the swimwear garment. Each of the opposing side edges of the rear compression layer are sewn to the outer rear layer. The bottom periphery of compression fabric layer is entirely positioned above the at least rear portions of the leg openings.
The disclosed technology provides for training a model to predict defective bins in a distribution center. A method includes retrieving bin data for a distribution center, partitioning the bin data into testing data and training data, designating a portion of the training data as defective bin data, designating a remaining portion of the training data as non-defective bin data, iteratively generating and testing models until a test model satisfies performance testing criteria, designating a portion of the bin data as complete defective bin data and a remaining portion as non-defective bin data, generating a complete model training data set combining the complete defective bin data and a portion of the non-defective bin data, and training a runtime model using the complete model training data set and training parameters determined in the iterative generating and testing steps.
Methods and systems for simulating fulfillment of digital orders within a retail supply chain are disclosed. One method includes receiving a selection of a first operational parameter of a supply chain model. The supply chain simulation model is a transaction-level model representative of a digital order fulfillment process within a retail supply chain network. The selection of the first operational parameter includes a default value for the first operational parameter and an experimental value for the first operational parameter that is different from the default value. Simulations of a set of predicted digital orders within the retail supply chain network, using the supply chain simulation model as modified in accordance with the first operational parameter, are performed. Scenario evaluations including predicted metrics associated with each of a cost, a capacity, and a guest experience for the digital order fulfillment process may be output and displayed on a user interface.
In general, methods and system for modeling the incremental value of a response to different types of treatment are disclosed. Some examples include modeling discount sensitivity for specific guests. One aspect is a method for modeling incremental sales for a retail enterprise which includes generating a proxy campaign. In some embodiments, the proxy campaign is used to train an uplift model to predict an uplift score for each guest in response to a proposed campaign. In some embodiments, the uplift score is used to select guests for the proposed campaign.
Methods, systems, and platforms are described for digital placement and allocation planning. An unconstrained distribution of items in a retail supply chain may be determined from digital demand forecasts by aggregating the digital demand forecasts based on location identifiers. An item allocation ratio between shipping locations may be determined using a model based on items being ordered together and the speed of items being ordered. An unconstrained DPA plan may be generated, with the distribution and the ratio, for placing and allocating a projected total quantity. Constraints relating to the supply chain may be identified. In response to the constraints, a constrained distribution may be generated from an unconstrained distribution. A constrained plan may be generated in response to the constrained distribution. The unconstrained or constrained DPA plan may be sent to a plan executor for initiating movements of items according to the plan within the supply chain.
Methods and systems for visualizing an inventory management and control. One method comprises receiving and aggregating inventory data from a plurality of nodes of a retail enterprise, scheduling a plurality of purchase orders for at least one item type based on the inventory data, generating inventory projections for the at least one item type based on the inventory data and the plurality of purchase orders, and rendering on a display, as part of a visualization tool user interface, a graphical view representing the inventory projections for the at least one item type, wherein the graphical view automatically updates based on inputs received for adjusting at least one purchase order of the plurality of purchase orders and inputs received for selecting at least one node or at least one group of nodes from the plurality of nodes.
Methods and systems for inventory management and control. One aspect is a method for inventory management and control, the method comprising receiving and aggregating inventory data from a plurality of nodes in a retail enterprise, receiving scheduled inventory actions and at least one constraint definition, detecting at least one inventory issue cause by the at least one constraint definition, and adjusting, automatically, at least one scheduled inventory action of the scheduled inventory actions based on the at least one inventory issue.
For a measurement period, signal strengths, device identifiers and access point identifiers are received from a plurality of access points. A record for the measurement period is stored in random access memory with the record being associated with a single device identifier and containing access point identifiers associated with signal strengths received for the measurement period. The location of a device is determined for the measurement period by retrieving spatial coordinates of a corresponding access point for each access point identifier in the record for the measurement period and setting the location of the device for the measurement period to the average of the retrieved spatial coordinates.
Systems and methods for providing prioritization of specific items at specific times in a manner that is provided to an overseas transport logistics software program, and that provide for visibility and prediction of status and risks. In examples, a set of enterprise priorities may be input from a variety of enterprise planning teams into a prioritization software tool. The prioritization software tool may then, based on relative priorities of items currently scheduled for overseas transport, generate a prioritization of items included in pending purchase orders. The prioritization is made accessible to an overseas transport logistics software program. The prioritization may assign individual items to a set of tiers, with each tier having a different handling and overseas shipment prioritization. Shipment information is then received and consolidated, and a dynamic lead time is calculated. The dynamic lead time is utilized to automatically calculate a dynamic risk factor.
Network infrastructure can be automatically detected. A network sensor detects a new network message. A source-address of the new network message is extracted. A plurality of addresses are assembled based on the source-address. These are recursed, using each of the unique similar-addresses as current addresses. Metadata is assembled for each of the addresses in the plurality of addresses. For each particular address in the plurality of addresses, a risk-label is assigned out of a plurality of possible risk-labels, by weighing a plurality of factors; and performing a network security action with the risk-label.
H04L 61/3015 - Name registration, generation or assignment
H04L 45/00 - Routing or path finding of packets in data switching networks
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
A network based order fulfillment systems having an improved user interface at both a customer device and at an order fulfillment location employee device. Both customer and employee devices can collect user input using unique user interface elements to elicit input from a customer in a retail environment on proper placement of items for an order in a vehicle. The unique user interface elements can be customized based on information specific to the user's vehicle. The elicited user input can be used to update a user interface of a second computing device.
A platform, web application, system, and methods are disclosed for creating digital 3D scenes having digital 3D objects and for creating images of the digital 3D scenes. The platform can be communicatively coupled with the web application. The platform can apply a multi-stage method to convert high-fidelity digital 3D objects into low-fidelity digital 3D objects, store a mapping between them, and transmit low-fidelity digital 3D objects to the web application. The web application can include user interfaces for manipulating low-fidelity digital 3D objects to create low-fidelity digital 3D scenes. The platform can automatically convert low-fidelity digital 3D scenes received from the web application into high-fidelity digital 3D scenes and create high-fidelity 2D images.
G06T 3/40 - Scaling of a whole image or part thereof
G06F 3/04845 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
G06T 19/20 - Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
A computer-implemented method includes receiving a certificate signing request and digital certificate serial number and extracting a public key modulus from the certificate signing request. A stored public key modulus is retrieved for the digital certificate serial number and an error is returned if the public key modulus and the stored public key modulus match so as to improve security of the network server.
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
H04L 9/30 - Public key, i.e. encryption algorithm being computationally infeasible to invert and users' encryption keys not requiring secrecy
Methods and systems for forecasting demand for items across multiple channels are disclosed. In some implementations, multi-channel demand forecasting may be performed on a per-item, per-location basis, by selectively generating item-location forecasts for each item and location within a supply chain for each channel, or disaggregating a chain level forecast on a per-item basis to each location. Particular selection of an appropriate model, and selective training of models, allows for efficient computation of such forecasts across a large supply chain with thousands of locations and hundreds of thousands, or millions, of items for which forecasts are generated.
An integrated asynchronous interface for data retrieval from across a plurality of data sources is described. An interface may include a plurality of Application Programming Interfaces (APIs) as well as a database for constructing responsive data. A search request may be decomposed at the interface to sub-search requests to be distributed to multiple data sources via a search request API. Data responsive to the sub-search requests may be aggregated at an interface database. A status API may maintain a status of the search request, and can update a tenant regarding the status of the tenant's search request. A response API may be used to provide reconstructed data responsive to the search request from the interface database to the tenant.
G06F 16/2458 - Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
A collapsible storage bin comprising a base, at least two sidewalls each rotatably coupled to the base, and at least one corner rail. Each of the at least two sidewalls rotates from a storage position within the base to a use position extending out of the base. Opposing ends of each of the at least two sidewalls is formed by a channel open toward the channel of the other of the first side end and the second side end top to define a first coupling flange as part of the first side end and a second coupling flange as part of the second side end. The at least one corner rail includes a first planar segment and a second planar segment coupled edge-to-edge to each other. Each of the first planar segment and the second planar segment terminates with a return to form a different elongated reception channel open toward the other of the first planar segment and the second planar segment. The at least one corner rail selectively and slidably receives the first coupling flange of a first one of the at least two sidewalls within the elongated reception channel of the first planar segment, and the at least one corner rail selectively and slidably receives the second coupling flange of a second one of the at least two sidewalls within the elongated reception channel of the second planar segment to hold the at least two sidewalls substantially perpendicular to one another.
The disclosed system and method relate to automatically detecting empty spaces on retail store shelves, identifying the missing product(s) and causing the space to be replenished or restocked. For example, stores may use shelf-mounted imaging devices to capture images of shelves across the aisle from the imaging devices. The images captured by the imaging devices may be pre-processed to de-warp, de-skew images and stitch together multiple images in order to retrieve an image that captures a full width of a shelf. The pre-processed images can then be used to detect products on the shelf, identify the detected products. For example, the captured image may be compared against a reference background image using a background modeling algorithm to identify empty spaces and mis-shelved items within the shelf.
The disclosed system and method relate to automatically detecting empty spaces on retail store shelves, identifying the missing product(s) and causing the space to be replenished or restocked. For example, stores may use shelf-mounted imaging devices to capture images of shelves across the aisle from the imaging devices. The images captured by the imaging devices may be pre-processed to de-warp, de-skew images and stitch together multiple images in order to retrieve an image that captures a full width of a shelf. The pre-processed images can then be used to detect products on the shelf, identify the detected products. An iterative projection algorithm or product fingerprint matching algorithm can be used to identify the products. When an incorrect product listing or an empty shelf space is encountered, a message may be sent to the store employee to remedy the issue.
The disclosed system and method relate to automatically detecting empty spaces on retail store shelves, identifying the missing product(s) and causing the space to be replenished or restocked. For example, stores may use shelf-mounted imaging devices to capture images of shelves across the aisle from the imaging devices. The images captured by the imaging devices may be pre-processed to de-warp, de-skew images and stitch together multiple images in order to retrieve an image that captures a full width of a shelf. The pre-processed images can then be used to detect products on the shelf, identify the detected products. An iterative projection algorithm or product fingerprint matching algorithm can be used to identify the products. When an incorrect product listing or an empty shelf space is encountered, a message may be sent to the store employee to remedy the issue.
In general, the subject matter of the disclosure relates to an orientation agnostic battery placement device. Connecting a battery in a reversed polarity configuration may cause the battery-powered electronic devices to not work or in some cases may even cause damage to the device itself. The disclosed orientation agnostic battery placement device includes a latch relay device that includes a first latch switch that electrically connects the first and second terminals of a battery compartment to the positive and negative electrical power connections of a load circuitry associated with the battery-powered electronic device respectively when the battery received within the battery compartment is in a first orientation and a second switch that electrically connects the first and second terminals of the battery compartment to the negative and positive electrical power connections of the load circuitry respectively when the battery received within the battery compartment is in a second orientation.
A nursing garment is configured to be worn by a wearer having breasts and for use with a pumping apparatus and includes a band, a pair of inner soft cups, and an exterior front panel. The band extends around a torso of the wearer. The pair of inner soft cups are secured to the band, and each includes a top retaining panel and a bottom retaining panel overlapping one another. The top retaining panel and the bottom retaining panel are configured to be selectively pulled away from each other forming an opening therebetween to permit a portion of the pumping apparatus to extend through the opening during milk expression. The exterior front panel extends over the pair of inner soft cups having a bottom edge that is free from mid-length securement can be at least partially pulled upwardly to expose one or both of the pair of inner soft cups.
In some implementations, a method performed by data processing apparatuses includes receiving map data that identifies a layout of physical objects within a physical area, identifying contiguous groups of the physical objects as composite objects, selecting bounding algorithms to use for generating graphical shapes for the composite objects, generating graphical shapes by applying the selected bounding algorithms to the composite objects, and testing the graphical shapes against one or more criteria. For candidate graphical shapes that fail a test, a new bounding algorithm can be selected and the generating and the testing can be repeated using the new bounding algorithm. A simplified graphical map can be output that represents the physical objects within the physical area using the graphical shapes.
A platform for customer and prospective customer messaging is provided. The platform generally coordinates message audience selection, message timing, and message content for delivery on any of a variety of communication channels (e.g., email, text message, push notification) for messages from marketing tenants and operational tenants to ensure a coordinated customer experience.
Disclosed are systems and methods for determining quality of item listings in an online retail environment. A method can include receiving, by a computing system, item listing data having information about items of item categories available in the online retail environment for purchase at computing devices of end consumers, determining, for each of the item categories, one or more quality index scores based on the information included in the item listing data, determining, for each of the item categories, a composite quality index score based on aggregating the quality index scores for the items in each of the item categories, and generating, based on the composite quality index score, output for each of the item categories for presentation on a display screen of a computing device of a retail employee. The quality index scores can quantify quality levels of the item listing data.
An in-store system for empty shelf detection substantially reduces computational resources required to determine where out-of-stock conditions are present. Such systems can prioritize analysis of product displays having different levels of turnover or importance, and can use on-site resources to make quick and accurate determinations of out-of-stock conditions that impact customer satisfaction.
Disclosed are systems and techniques for determining out of stock conditions on shelves. The techniques can include receiving, by a computing system, image data from a camera having pixel locations that each uniquely address and store a pixel value, generating a backing map having cell locations that each uniquely address and share a unique address with a corresponding pixel location in the image data, each cell location storing a backing value being an empty value if the pixel value is classified as showing the backing of a shelf and the backing value being a nonempty value if the pixel value is classified as not showing the backing of the shelf, determining, in the backing map, a shelf area representing a location of the captured shelf, and identifying an empty area by finding an area above the shelf area containing a threshold number of cell locations storing the empty value.
G06Q 10/087 - Inventory or stock management, e.g. order filling, procurement or balancing against orders
G06F 18/241 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
Methods and systems for securely transferring and merging an electronic shopping cart curated by an affiliate online service for purchase on a retailer online service is disclosed. The retailer online service provides an anonymous token to the affiliate online service that allows the affiliate online service to curate an anonymous electronic shopping cart for a user that does not include any identifying information that links the user to a guest account of the retailer online service. When the user is redirected from the affiliate online service to the retailer online service, the anonymous token is validated. Upon validation of the anonymous token, the retailer online service obtains identifying information linking the user to the guest account of the retailer online service and obtain a pre-existing electronic shopping cart linked to the guest account. The retailer online service then merges the anonymous electronic shopping cart with the pre-existing electronic shopping cart.
Disclosed are techniques for monitoring internal security vulnerabilities in an enterprise based on determining composite risk scores for enterprise users. A method can include receiving information about an enterprise user, such as their role, identifying risks associated with the role, determining, based on the risks, a role-based risk score for the user, receiving, event alerts from a network security detection system, each event alert having been generated by the network security detection system identifying network activity on the enterprise's network that satisfies one or more security event rules indicative of a potential network security issue, determining that one or more of the event alerts are associated with the user in the enterprise to generate user-event pairings, determining, based on the user-event pairings, an event-based risk score for the user, and generating a composite risk score for the user based on aggregating the role-based risk score and the event-based risk score.
Disclosed are techniques for associating users of a network infrastructure to network or endpoint events within the network infrastructure. A method can include receiving, by a network security system that monitors and protects the network infrastructure, a packet for a network event, the packet including (i) information identifying a user device from which the network event originates and (ii) a payload, determining whether the packet triggers at least one association rule in a group of association rules, determining candidate users to be associated with the network event based on the rule triggered by the packet, determining confidence values for the candidate users to be associated with the network event based on the rule triggered by the packet, and returning the candidate users to associate with the network event and the corresponding confidence values.
Disclosed are techniques for monitoring and identifying attempts to subvert a security wall within a network infrastructure. A method can include receiving, by a network security system monitoring and protecting the network infrastructure, network activity for the network infrastructure, determining whether the network activity triggers at least one security event rule, blocking the network activity when the network activity triggers the rule, determining a sensitivity level associated with the network activity, starting a timer based on the sensitivity level satisfying a threshold level of sensitivity, continuously monitoring subsequent network activity until the timer expires, determining whether the subsequent network activity triggers one or more security event rules before the timer expires, associating the blocked network activity with the subsequent network activity if the subsequent network activity triggers the rules, and generating an alert indicating the associated network activity as an attempt to subvert a security wall within the network infrastructure.
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