Alerta

DIRECTIONAL GUIDANCE USING COMBINED SENSOR DATA

Absstract of: WO2026050071A1

A method in a computing device includes: obtaining an item identifier; capturing, via a camera, an image of a portion of a facility; capturing, via a radio frequency identification (RFID) reader, a tag identifier from an RFID tag associated with an item disposed in the facility; in response to determining that the tag identifier is associated with the item identifier, detecting from the image a visual feature of the item identifier; determining, based on the visual feature, a candidate position of the item and the RFID tag in the image; and controlling an output device to present the candidate position.

DEMAND MANAGEMENT OF MATERIAL REQUIREMENTS PLANNING

Absstract of: US20260065189A1

Systems and methods are directed toward managing demand, such as for manufacturing in complex supply and/or demand driven environments, including aerospace-industry products and systems, environments with a multitude of stakeholders, and other sophisticated organizations. A production request may be provided with a component identifier for a top-level module component to be produced. Data associated with the component identifier may be determined. The data may include one or more additional component identifiers for sub-components which are to be consumed to produce the top-level module component. Supply allocations for the top-level module component and the sub-components may be generated based at least in part on the data. One or more action signals may be provided to fulfill the production request for the top-level module component according to the supply allocations.

USING A LARGE LANGUAGE MODEL TO GENERATE CONTENT BASED ON IMAGES CAPTURED AT A SOURCE LOCATION

Absstract of: US20260065327A1

An online system receives an image captured at a source location, in which the image depicts one or more objects. The system generates a prompt including the image and a request to identify, from the objects, a set of items available at the source location based on a database of items available at the source location, and to extract, from the image, text describing a price or a promotion associated with each identified item. The system provides the prompt to a large language model to obtain an output, in which the model is fine-tuned based on the database of items. The system extracts, from the output, an identifier and the text associated with each item, retrieves item data for each item based on the identifier associated with the item, and generates promotional content for the source location based on the item data and the price or promotion associated with each item.

DRIVE UP INCENTIVIZATION ENGINE IN AN ORDER FULFILLMENT SYSTEM

Absstract of: US20260065313A1

The disclosed technology provides for incentivizing a user to pick up an order at an fulfillment location. A method can include receiving, at a mobile device, information for picking up an order at a fulfillment location and and incentivization information from a server system, where the incentivization information includes information for an incentive associated with picking up the order at the fulfillment location during an incentivization window. The method can include changing a display of the computing device to display information for picking up the order during the incentivization window, receiving a second communication from the computing device indicating that the computing device has arrived at the fulfillment location, and changing the display of the computing device to display a confirmation of the incentivization information based on whether the particular timepoint at which the computing device arrived at the fulfillment location is within the incentivization window.

INDEPENDENTLY PROCURABLE ITEM COMPLIANCE INFORMATION

Absstract of: US20260065341A1

Systems and methods electronically provide information regarding digital rules related to a potential relationship instance. Users often wish to know which digital rules apply to a specified item before engaging in a relationship instance with a host entity regarding the item. The system and methods described herein allow a computing facility to identify an item and receive resource information related to the item and the digital rules applicable to the item.

GENERATING A REGION- AND SOURCE-AGNOSTIC DATABASE OF ITEMS AVAILABLE IN MULTIPLE REGIONS

Absstract of: US20260065352A1

An online system retrieves item data for items available at sources in multiple regions and generates candidate nodes based on the item data, in which each candidate node represents items having at least a threshold measure of similarity to each other. The system accesses and applies a machine-learning model to predict a matching score for each combination of an item and a candidate node based on item data for the item and attributes of items represented by the candidate node. The system assigns the items to candidate nodes based on the matching scores, retrieves information describing an availability of each item in each geographical region, and identifies an average availability of items assigned to each candidate node across the geographical regions. The system selects nodes to include in a region- and source-agnostic item database, in which the average availability associated with each selected node is at least a threshold.

System and Method of Reinforced Machine-Learning Retail Allocation

Absstract of: US20260065223A1

A system and method for allocation planning comprise a server comprising a processor and memory and configured to calculate a reward for a historical allocation of a product to one or more stores associated with a retailer. Embodiments include simulating what-if scenarios for the historical allocation to identify an allocation having a greater reward than the historical allocation and allocating a quantity of a product for a current allocation to the one or more stores based, at least in part, on a distance calculation of one or more independent variables for the historical allocation and the current allocation and the identified allocation having the greater reward then the historical allocation.

Identifying Cargo

Absstract of: US20260065217A1

Systems and methods for identifying cargo on a truck include capturing a digital image of cargo on a truck using a digital camera and determining a count of items in the cargo by digitally processing the image of the cargo using a machine learning model trained to identify the items in the image. A unique identifier can be identified in the image corresponding to a type of the items in the cargo, and the type of the items in the cargo can be determined based on the unique identifier. The count of items and the type of items is compared to an expected count and an expected type.

SYSTEM AND METHOD FOR PROACTIVE AGGREGATION

Absstract of: US20260065220A1

The method includes determining, by a central server computer using a machine learning model, aggregates of items that are likely to be ordered by end users. The method also includes initiating placement of the items in the aggregates of items in one or more locations based on locations of the end users, receiving a request for an aggregate of items, and initiate the fulfillment of the request for the aggregate of items, where the items in the aggregates of items are at the one or more locations.

APPARATUSES AND METHODS FOR FACILITATING A MAPPING AGENT TO DRIVE FORECASTING AND INVENTORY MANAGEMENT

Absstract of: US20260065218A1

Aspects of the subject disclosure may include, for example, obtaining a request pertaining to a communication service, processing a file associated with the request to generate asset details, obtaining data pertaining to demand for communication services within a communication network, processing at least the data to generate a forecast of demand for the communication service, and processing the asset details and the forecast of demand to allocate capacity, acquire resources, or a combination thereof, for facilitating the communication service. Other embodiments are disclosed.

Systems and Methods of Supply Chain Intelligence Constructed on Semantic Supply Chain Model

Absstract of: US20260065222A1

A system and method are disclosed for providing supply chain intelligence based on a semantic supply chain model. The method includes building a semantic model of a supply chain, building goals and measures to construct measure graphs to represent supply chain scenarios, storing access and computation information for the measures, relating the measures to the supply chain goals, monitoring the measures associated with the supply chain goals; tuning the measures using machine learning models by tracking outcomes and user actions associated with the measures and goals to update the machine learning models based on the tracked outcomes and user actions, monitoring for abnormal patterns of the measures, triggering, based on a detection of an abnormal pattern, an alert and a resolution, and rendering an alert or a resolution in machine form to supply chain execution systems.

Directional Guidance Using Combined Sensor Data

Absstract of: US20260065216A1

A method in a computing device includes: obtaining an item identifier; capturing, via a camera, an image of a portion of a facility; capturing, via a radio frequency identification (RFID) reader, a tag identifier from an RFID tag associated with an item disposed in the facility; in response to determining that the tag identifier is associated with the item identifier, detecting from the image a visual feature of the item identifier; determining, based on the visual feature, a candidate position of the item and the RFID tag in the image; and controlling an output device to present the candidate position.

ARTIFICIAL INTELLIGENCE-BASED MANAGEMENT OF RAILROAD SUPPLY CHAIN NETWORK

Absstract of: US20260065214A1

The technology disclosed relates to predicting an estimated time of arrival for an equipment via a railroad. In particular, the technology disclosed relates to inputting to a trained machine learning model, a shipment data that includes a starting location for a particular trip and a destination location for the particular trip, and predicting, using the trained machine learning model, the estimated time of arrival of the equipment at the destination location for the particular trip when no historical trip data exists for the particular trip.

LOCAL SMALL FOUNDATION SYSTEM FOR INFERENCING

Absstract of: US20260065094A1

The disclosure is directed to a local small foundation system which leverages a generative Artificial Intelligence (AI) model to produce classification results. The local small foundation system includes less than 10 billion parameters and is located on an edge site. The local small foundation system is customized towards the edge site. The local small foundation system produces classification results based on a query by making an inference with the generative AI model. An output guardrail module determines if the classification results can be resolved to an existing class of a plurality of existing classes. The output guardrail module also provides instructions on how to implement classification results at the endpoint management system. The output guardrail module also determines if a centralized large foundation system needs to be consulted and what to send to the centralized large foundation system.

Methods and Systems for Controlling Antennas and Reader Devices

Absstract of: US20260065001A1

An inventory system comprises an antenna configured to emit interrogation signals in a first direction toward one or more tags, a reader device configured to receive data from the one or more tags, and a controller. The controller is configured to detect a trigger event occurring within an area including the antenna, cause an adjustment to at least one antenna setting of the antenna or at least one reader device setting of the reader device based on the trigger event and a policy associated with the trigger event, and instruct the antenna or the reader device to emit an interrogation signal in a direction of one or more tags and read data from the one or more tags in accordance with the adjustment to at least one antenna setting or the at least one reader device setting.

RENEWABLE MATERIAL TRACEABILITY SYSTEM AND RENEWABLE MATERIAL TRACEABILITY METHOD

Absstract of: US20260065293A1

A renewable material traceability system acquires information on a renewable material provided by a provider and information on the provider, allocates a lot of the renewable material to a product in a production process of the product, and notifies the provider of evaluation data obtained based on data associated with the provider from among a traceability data group, the evaluation data being data as an evaluation related to the provision by the provider, the traceability data group including material traceability data, which is data including a set of information on the renewable material and information on the provider, and production traceability data, which is data including information indicating a lot allocated to each product for each of one or more types of renewable materials used as materials for the product.

INFORMATION PROCESSING APPARATUS AND INFORMATION PROCESSING METHOD

Absstract of: US20260065212A1

An information processing apparatus includes: a transaction relationship score calculation unit that calculates an inter-industry transaction relationship score indicating a relevance of a transaction relationship among a plurality of industry types; a component supplier industry-type estimation unit that estimates an industry type of a factory candidate of a supplier on a basis of identification information of a component for a factory candidate of a supplier; an industry type similarity calculation unit that calculates an inter-industry transaction relationship score between an industry type of a factory candidate of a supplier and an industry type of a factory candidate of a supplier estimated by the component supplier industry-type estimation unit; and a component manufacturing factory estimation unit that selects a factory candidate of a supplier on a basis of an inter-industry transaction relationship score calculated by the industry type.

SYSTEM AND METHOD FOR MANAGING PACKAGES

Absstract of: US20260065009A1

A system to manage packages is disclosed. The system comprises an antenna configured to emit one or more beams of a variable transmission power in one or more antenna sectors and a radio frequency identification (RFID) reader communicatively coupled to the antenna to receive an RFID signal from each of one or more incoming packages. Further, the RFID reader comprising the one or more processors coupled to the memory, the one or more processors configured to retrieve the data associated with each of the one or more packages, determine a weighted density factor of each of the one or more packages, determine a load density for each of the one or more antenna sectors, and adjust the variable transmission power of the antenna for each of the one or more antenna sectors based at least on the load density.

METHOD AND SYSTEM FOR CREATING A MULTIMODAL AND MULTILINGUAL PRODUCT CATALOGUE USING A HYBRID MODEL

Absstract of: US20260064648A1

Disclosed is a method and system for creating a product catalogue using a hybrid model. A data reception module receives multimodal data related to a product from one or more data sources that may include structured, unstructured, and semi-structured data. An extraction module extracts text from the product data and is then preprocessed using a preprocessing module, which is further converted into numerical vectors. The hybrid model, an integration of a rule-based model, a Named Entity Recognition (NER) model, and a Generative-AI model, is contextually employed to extract multilingual attributes and values from the text. An attribute-value module generates one or more attribute-value pairs and maps them to the product in a structured format. Finally, a catalogue creation module creates a product catalogue using the one or more attribute-value pairs.

INFORMATIONSVERARBEITUNGSVORRICHTUNG UND INFORMATIONSVERARBEITUNGSVERFAHREN

Absstract of: DE102025119222A1

Eine Informationsverarbeitungsvorrichtung umfasst: eine Transaktionsbeziehungspunktwert-Berechnungseinheit, die einen Zwischen-Industrietransaktionsbeziehungspunktwert, der eine Relevanz einer Transaktionsbeziehung unter einer Vielzahl von Industrietypen angibt, berechnet; eine Komponentenzuliefererindustrietyp-Schätzeinheit, die einen Industrietyp eines Fabrikkandidaten eines Zulieferers auf der Grundlage einer Identifikationsinformation einer Komponente für einen Fabrikkandidaten eines Zulieferers schätzt; eine Industrietypähnlichkeit-Berechnungseinheit, die einen Zwischen-Industrietransaktionsbeziehungspunktwert zwischen einem Industrietyp eines Fabrikkandidaten eines Zulieferers und einem Industrietyp eines Fabrikkandidaten eines Zulieferers, der durch die Komponentenzuliefererindustrietyp-Schätzeinheit geschätzt wird, berechnet; und eine Komponentenherstellungsfabrik-Schätzeinheit, die einen Fabrikkandidaten eines Zulieferers auf der Grundlage eines Zwischen-Industrietransaktionsbeziehungspunktwerts, der durch die Industrietypähnlichkeit-Berechnungseinheit berechnet wird, auswählt und einen Standort des ausgewählten Zuliefererkandidaten als einen Standort einer Herstellungsfabrik einer Komponente, die durch einen Zulieferer hergestellt wird, schätzt.

Werkzeugverwaltungssystem

Absstract of: DE102025133901A1

Ein Werkzeugverwaltungssystem (S) beinhaltet eine Werkzeugverwaltungsvorrichtung (1) und eine Informationseingabe-/-ausgabeeinheit (2). In der Informationseingabe-/-ausgabeeinheit (2) kann die Werkzeugkomponente und/oder das zusammengesetzte Werkzeug (AS), die in der Werkzeuginformationsdatenbank (10) gespeichert sind, in der eindeutige Identifizierungsinformationen zugewiesen werden, zusammen mit einer Vielzahl von vorbestimmten Aktionsmustern ausgewählt werden, die tatsächliche Vorgänge darstellen, die für die Vorbereitung eines zusammengesetzten Werkzeugs (AS) erforderlich sind, das bei der Bearbeitung verwendet wird. Die Werkzeugverwaltungsvorrichtung (1) beinhaltet eine Listengenerierungseinheit (13) und eine Datenbestimmungseinheit (14). Die Listengenerierungseinheit (13) generiert automatisch eine Vorbereitungswerkzeugliste, die die ausgewählte Werkzeugkomponente und/oder das zusammengesetzte Werkzeug (AS) für jedes der Aktionsmuster beinhaltet, wenn die Werkzeugkomponente und/oder das zusammengesetzte Werkzeug (AS) zusammen mit jedem der Aktionsmuster ausgewählt wird. Die Datenbestimmungseinheit (14) bestimmt, ob die eindeutigen Identifizierungsinformationen der tatsächlichen Werkzeugkomponente und/oder des zusammengesetzten Werkzeugs (AS) mit den eindeutigen Identifizierungsinformationen übereinstimmen, die in der Vorbereitungswerkzeugliste aufgeführt sind.

Verfahren und System zur Erzeugung einer Stückliste und einer entsprechenden Arbeitsplanliste für ein Produkt

Absstract of: DE102025134565A1

Zur Erzeugung einer Stückliste und einer entsprechenden Arbeitsplanliste für ein Produkt bildet ein Modul zur Verarbeitung natürlicher Sprache (NLP-M) wenigstens ein Produkt spezifizierendes Dokument in eine latente Repräsentation (LR) ab, die eine Einbettung im latenten Raum ist. Ein Stücklistengenerator (BOM-G) empfängt die latente Repräsentation (LR) als Eingabe und erzeugt eine Stückliste (BOM-TR) für das Produkt. Eine Benutzeroberfläche (UI) erfasst Benutzerinteraktionen mit der erzeugten Stückliste (BOM-TR) und erstellt eine kuratierte Stückliste (BOM-C) in Abhängigkeit von den Benutzerinteraktionen. Ein Arbeitsplanlistengenerator (BOP-G) empfängt die latente Repräsentation (LR) und die kuratierte Stückliste (BOM-C) als Eingabe und konstruiert eine Arbeitsplanliste (BOP-DAG) für das Produkt. Das Verfahren und das System, oder wenigstens einige ihrer Ausführungsformen, sehen eine halbautomatische Erzeugung der Stückliste und der Arbeitsplanliste für ein Produkt unter Verwendung einer KI-Engine vor. Im Vergleich zur manuellen Einrichtung einer Stückliste und/oder einer Arbeitsplanliste innerhalb eines Softwaresystems kann der Ansatz, KI zur Erzeugung dieser Informationen zu verwenden, den Prozess der Berechnung von Kosten und Nachhaltigkeitswerten eines Produkts erheblich beschleunigen. Auf diese Weise kann die Zeit von der Angebotsanfrage bis zur Abgabe des tatsächlichen Angebots erheblich verkürzt werden.

TRAINING A NEURAL DATABASE FOR ENTITY MATCHING

Absstract of: US20260065188A1

Certain aspects of the disclosure provide a method of training a neural database for entity matching. In examples, a method may include: extracting, from an electronic data repository, entity data related to a first entity that provides a good or a service; transforming the entity data into structured entity data configured to be processed by a machine learning model; processing the structured entity data with the machine learning model to generate metadata associated with the structured entity data; augmenting the structured entity data with the metadata associated with the structured entity data; and training the neural database based on the augmented structured entity data to predict one or more second entities that supply materials for the first entity and associated with the good or the service.

METHODS AND SYSTEMS FOR CONTROLLING ANTENNAS AND READER DEVICES

Absstract of: WO2026049993A1

An inventory system comprises an antenna configured to emit interrogation signals in a first direction toward one or more tags, a reader device configured to receive data from the one or more tags, and a controller. The controller is configured to detect a trigger event occurring within an area including the antenna, cause an adjustment to at least one antenna setting of the antenna or at least one reader device setting of the reader device based on the trigger event and a policy associated with the trigger event, and instruct the antenna or the reader device to emit an interrogation signal in a direction of one or more tags and read data from the one or more tags in accordance with the adjustment to at least one antenna setting or the at least one reader device setting.

METHODS AND SYSTEMS ENABLING PRODUCT DATA SEARCH WITHIN DECENTRAL NETWORKS

Nº publicación: WO2026046787A1 05/03/2026

Applicant:

BASF SE [DE]
BASF SE

Absstract of: WO2026046787A1

The present disclosure relates to the field of data search within decentral systems for product data associated with product(s) produced or producible by a production. The disclosure relates to methods, apparatuses and computer-elements for generating output product data to be published in a decentral network by a data providing service configured to provide the output product data in response to a request for such output product data. The disclosure further relates to methods, apparatuses and computer-elements for generating a search index from public output product data associated with output product(s) and received via a decentral network from public output product data provider(s) and methods, services and computer-elements for returning public output product data associated with output product(s) based on such search index. The disclosure further relates to methods, apparatuses and computer-elements for controlling access to output product data associated with output product(s) via a decentral network. The disclosure further relates to a use of the output product data published according to the present disclosure and to an output product associated with output product data published according to the present disclosure.