Abstract: In some embodiments, apparatuses and methods are provided herein useful to automatically balance and buffer the return of empty containers or other totes to a plurality of areas. In some embodiments, a control circuit employs a logic system in which empty totes are directed along primary, secondary, or tertiary paths depending on information gathered from sensors regarding the availability of space for empty totes at a plurality of potential destinations. In this way, the return of empty totes to one or more points of origin may be buffered to balance the number of empty totes in one or more areas.

Abstract: A template generation system includes a computing device configured to, in response to receiving a request for a resource from a user device, identify a set of network identifiers based on the request and select a subset of identifiers of the set of network identifiers based on filtering criteria and the request. The computing device is further configured to, for each identifier of the subset of identifiers, in response to a record being associated with the corresponding identifier, clean the record and generate a new record defining the resource by mapping the requested resource to the corresponding identifier. The computing device is also configured to populate a template based on a set of rules identifying the subset of identifiers and the new record and transmit the template to a deployment system.

Abstract: Systems, apparatuses, and methods are provided herein for in-store production management. A method comprises training a probabilistic demand model using the training dataset based on a machine learning algorithm, determining a probabilistic forecast of a demand for a perishable product at a store location on a date based on the probabilistic demand model, applying an objective function to each of the plurality of demand values in the probabilistic forecast to determine an objective value for each of the plurality of demand values, determining a target supply value based on a select demand value with a highest objective value, determining a production plan based on the target supply value and a carryover value retrieved from the store data database, and providing a production management user interface that comprises a display of an identifier of the perishable product and the production plan associated the perishable product.

Abstract: An electronic indication of a nil pick is received. Item information associated with the desired product, sales data concerning the desired product, supply chain information associated with the desired product, and a perpetual inventory (PI) value of the desired product are stored. An adjustment to the PI of the desired product is blocked when a predetermined event occurs at the retail store, or when information that contradicts the validity of the nil pick is received from the retail store. When the adjustment to the PI of the desired product is not blocked, an amount of the adjustment is determined based upon one or more of: the item information associated with the product, the sales data concerning the product, and the supply chain information associated with the desired product.

Abstract: A supply chain forecasting system with blockchain controls is discussed. The supply chain forecasting system can include a central computing system communicating with a third party computing system. The central computing system and third party computing system can initiate, adjust, and fulfill smart contracts associated with the delivery of physical objects using blockchain controls.

Abstract: There are provided systems and methods for managing network vulnerability scanning to avoid interference and disruption of network operations. In one form, the system includes: a network of computing devices; a network vulnerability scanner for evaluating insecurity and vulnerability of the network; a network traffic monitor for measuring the volume of network traffic at a certain time; and a scanning scheduler that includes scanning blackout events limiting operation of the scanner. Each blackout event includes an event name, a country or region for the blackout, a blackout start time and end time, and a blackout type that may include a level of the blackout and an authorization required for the network scan to proceed. In the system, a control circuit controls operation of the scanner; interrupts, delays, or cancels a network scan when the network traffic exceeds a certain threshold; and enforces blackout events according to the scanning scheduler.

Abstract: A systems including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of: receiving a query image comprising at least one target object and at least one candidate image; generating a plurality of proposals based on the at least one candidate image; selecting a portion of the plurality of proposals to produce a reduced proposal set; generating a query embedding corresponding to the query image; generating candidate embeddings corresponding to the portion of the plurality of proposals included in the reduced proposal set; computing similarity scores for the portion of the plurality of proposals; and comparing the similarity scores to a threshold to determine if the at least one candidate image comprises the at least one target object. Other embodiments are disclosed herein.

Abstract: An out-of-stock indicator is received that indicates a product is out-of-stock or believed to be out-of-stock. Information about the features of the products and store are obtained or determined. The features are applied to a first machine learning model, which yields a probability that the item is out-of-stock. The obtained probability is compared to a threshold, and if the probability value is above a threshold, then the PI value is adjusted. If not above the threshold, then scans are monitored for out-of-stock conditions, and some time later the features will be applied to a different model, and the above-process repeated. In aspects, this process occurs over a certain time period or until the PI is adjusted.

Abstract: A system for storing one or more unmanned aerial vehicles is described herein. The system includes one or more shelves attached to a holding structure, the one or more shelves being configured to support one or more unmanned aerial vehicles (UAVs), the one or more shelves defining one or more shelf areas configured to receive the one or more unmanned aerial vehicles. The system also includes an electrical charging station configured to charge electrical batteries of the one or more unmanned aerial vehicles supported by the one or more shelves; and a data transfer and storage system configured to transfer and store data that is previously stored in a data storage device of the one or more unmanned aerial vehicles in a data storage unit.

Abstract: The embodiments described herein are directed to a cart and related methods. The cart includes a base, a plurality of wheels connected to the base, a lower platform mounted to the base, a back panel mounted to the base, a set of lateral panels, an opening side of the cart, and a linking mechanism. The set of lateral panels defines an interior space of the cart. At least one of the set of lateral panels includes a shelf. The shelf is pivotally mounted to a rectangular frame of the at least one of the set of lateral panels. The opening side of the cart is open to provide access to the interior space of the cart. The linking mechanism is configured and arranged to connect the cart to another cart.

Abstract: A system can include one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations comprising: receiving, at a search engine, a user search query submitted by a user; generating, using a recall personalization model, a simulated query that supplements the user search query with a feature vector reflecting personalization preferences of the user; and generating, using the search engine, search results for the user search query based, at least in part, on the simulated query that accounts for the personalization preferences of the user. Other embodiments are disclosed herein.

Abstract: A system can include one or more processors and one or more non-transitory computer-readable media storing computing instructions, that when executed on the one or more processors, cause the one or more processors to perform operations including: automatically customizing, based on a first state of a user, first content for a graphical user interface on an electronic device of the user; monitoring second activities of the user over a time period; identifying a second probability that the user has transitioned from the first state into a second state during the time period; determining when the second probability is above a second probability predefined threshold; and after determining the second probability to be above the second probability predefined threshold, automatically customizing, based on the second state of the user, second content for the graphical user interface on the electronic device of the user. Other embodiments are disclosed herein.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations including: reducing, using a multilayer perceptron, a dimension of feature embeddings for an item to generate a representation vector; extracting, using a recurrent neural network, sequential data from traffic features for the item; inputting the representation vector and the sequential data into a multilayer neural network, wherein the first scoring layer outputs one or more first performance metrics based on offline learning; and re-purposing the output of the second ReLU activation function of the multilayer neural network by feeding the output of the second ReLU activation function into a second scoring layer to output one or more second performance metrics based on online learning. Other embodiments are disclosed.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to verify accuracy of a shipment. In some embodiments, items loaded to and/or unloaded from a delivery vehicle are scanned and compared to a delivery schedule, and a unique identifier is provided to confirm proper loading/unloading at a subsequent scheduled stop of the vehicle.

Abstract: An automated container cutting system for cutting a container includes a cutting platform and a cutting tool held by the cutting platform. The cutting tool is configured to cut the container. The automated container cutting system includes a force feedback sensor operatively connected to the cutting tool such that the force feedback sensor is configured to measure resistive force exerted on the cutting tool. The automated container cutting system includes at least one processor communicatively coupled to the force feedback sensor. The processor is configured to receive resistive force data from the force feedback sensor. The resistive force data represents resistive force exerted on the cutting tool as the cutting tool pierces a wall of the container. The at least one processor is configured to determine whether the cutting tool has penetrated through the wall of the container using the received resistive force data.

Abstract: In some embodiments, systems and methods provide distributed item authentication. In some embodiments systems comprise: a housing; a set of sensor systems; a transceiver; and an authentication control circuit configured to: obtain first sensor data of an item being authenticated, obtain an initial identification of the item; access an item authentication block specific to the item; obtain a first set of authentication instructions; control one or more sensor systems in accordance with the first set of authentication instructions; compare multiple current authentication sensor data to the set of multiple historic authentication sensor data; confirm that each of a threshold number of the multiple current authentication sensor data is consistent within a threshold variation of a corresponding one of the set of multiple historic authentication sensor data; and cause the item authentication block to be updated to include the confirmation of authentication of the item.

Abstract: Systems and methods including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform functions comprising: determining at least one fleet delivery route for delivery of one or more items of one or more orders to one or more locations using a vehicle fleet; dynamically shuffling the at least one fleet delivery route by at least evaluating a cost differential; when the cost differential satisfies a threshold: removing the first order from the source route; inserting the first order into the first other delivery route; and communicating the first order to a first other deliverer associated with the first other delivery route. Additional embodiments are disclosed herein.

Abstract: Described in detail herein is a forecasting system. In one embodiment, the system can generate forecast data for the amount of labor and physical objects needed at various facilities.

Abstract: Systems, apparatuses, and methods are provided herein for user access to smart locks at a retail shopping facility. In one embodiment, a system for user access to smart locks at a retail shopping facility includes an access member, a smart lock securing the access member, and a control circuit. The control circuit configured to receive authentication data from the user interface device; determine whether the authentication data matches within a threshold of stored authentication data associated with a profile stored in a database; determine that the user is a trusted user based on the determination that the authentication data matches with the stored authentication data within the threshold; and provide an optical key to the user interface device, wherein the smart lock is configured to unlock the access member in response to receiving the optical key from the user interface device.

Abstract: A system can include one or more processing modules and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processing modules and perform receiving, from an electronic device, a search query from a user of a plurality of users; processing first data; and facilitating displaying a set of items. Processing the first data can comprise determining one or more keywords by capturing the one or more keywords during a time window; creating a feature set of second data associated with at least a portion of the plurality of users; determining a set of items of the item set as being based at least in part on an item vector representation and a keyword vector representation; determining a respective purchase probability associated with each item of the set of items of the item set; ranking the set of items.