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露天挖机、矿用卡车的协同调度方法、装置及可读存储介质

Resumen de: CN121745538A

本申请提供了露天挖机、矿用卡车的协同调度方法、装置及可读存储介质，属于矿用车辆协同调度领域；挖机与卡车之间采用4G/5G专网与小型局域网的双网络自适应切换机制实现协同调度，方法包括以下步骤：通过卡车调度平台配置编组计划，生成动态调度指令，并同步向处于待机状态的挖机和处于空运状态的卡车下发协同调度指令；挖机和卡车接收到调度指令后分别行驶至装载区域，并判断车辆是否进入装载区域；确定车辆进入装载区域后，再判断是否存在排队车辆；然后选择排队卡车，更新卡车状态并判断是否装载完成后进入卸载区域，更新状态后直至卸载完成最终完成卸载和状态更新；可以极大的避免挖机与卡车之间频繁出现通信中断或数据传输延迟的情况。

一种模块化手术室专用耗材智能管理装置

Resumen de: CN121730999A

本发明公开了一种模块化手术室专用耗材智能管理装置，涉及耗材管理领域；该模块化手术室专用耗材智能管理装置，通过拼接盒、底部模块和顶部模块拼接组成耗材管理装置，装置的嵌入式系统接入库存系统对存储盒内部的耗材进行统一管理；在耗材出库到剩余耗材归库过程中，可以选择部分拼接盒与底部模块和顶部模块组装，将待使用的手术耗材经由摄像头和嵌入式系统记录后放置在存储盒中，在术前术后通过摄像头和嵌入式系统拍摄记录手术耗材使用情况，便于医护人员在术前术后快速清点手术耗材的消耗情况，在剩余耗材归库时，嵌入式系统与库存系统对接，实现剩余耗材的快速录入，将耗材专门管理延伸到术前术后的各个时间段。

一种数字孪生驱动的智慧港口装卸流程优化方法及系统

Resumen de: CN121745369A

本发明公开了一种数字孪生驱动的智慧港口装卸流程优化方法及系统，应用于包含岸桥、场桥、水平运输设备与堆场作业单元的港口装卸场景。通过采集港口装卸流程的实时状态数据与作业约束数据，构建并更新与物理港口对应的数字孪生状态，在数字孪生状态下生成装卸流程的候选控制动作集，并针对各候选控制动作执行反事实干预仿真，计算对应的流程演化结果及边际因果影响指标，进一步生成可机器校验的动作安全‑收益证书，仅选择满足预设证书门槛的控制动作下发执行，并通过执行反馈持续更新数字孪生状态，从而实现港口装卸流程的安全、稳定与高效优化。

一种基于智能体的企业项目服务管理系统

Resumen de: CN121745844A

本发明涉及大数据分析技术领域，具体为一种基于智能体的企业项目服务管理系统；接入企业的业务凭证数据流、项目合同文档及资金流转记录作为私域运营数据，同步接入区域关联数据中的物流运输时空轨迹及工业能源消耗数据；验证智能体组基于企业私域运营数据，调用区域关联数据中的物流与能耗数据，进行多维物理时空及逻辑一致性匹配，生成包含置信度权重的可信交互特征；分析智能体组接收可信交互特征，将微观交互关系映射至区域宏观维度，构建包含企业节点与加权服务流转边的区域产业链拓扑网络；基于区域产业链拓扑网络，动态计算企业节点间的服务供需耦合指数，识别阻碍项目流转的产业链断点，生成优化资源配置的补链路径规划。

一种物流业务的确定方法及装置

Resumen de: CN121745786A

本申请公开了一种物流业务的确定方法及装置，属于物流技术领域，该方法充分结合了发货需求与报价信息进行决策，能够从各个物流服务中精准筛选出符合实际发货需求的目标物流服务，有效解决了传统人工对比或单一维度筛选导致的效率低、匹配度差的问题，显著提升了物流业务确定的效率与精准度，保障了物流业务的高效开展。

物流场地车辆智能调度方法、装置、设备及存储介质

Resumen de: CN121745605A

本申请涉及物流仓储与智能调度技术领域，具体公开了一种物流场地车辆智能调度方法、装置、设备及存储介质，方法包括：获取多源数据；根据可反映货物需求、车辆特性和物流场地状态在内的影响因素，对当前全部待调度车辆进行调度优先级排序；根据各待调度车辆的调度优先级，从高到低依次从调度资源池中筛选出所有符合分配约束的可行的资源调度方案，并进行自由组合；基于调度资源排队时长和调度资源综合利用率构建的资源调度评价公式，对自由组合形成的若干候选资源整体调度方案进行评分，确定出最优资源整体调度方案。本申请提供的方案，可以实现人员、车辆、货物、场地的高效匹配与协同，提高了资源调配效率及资源调度方案可信度，降低了沟通成本。

作業計画支援装置、作業計画支援方法、及び、作業計画支援プログラム

Resumen de: JP2026054195A

【課題】倉庫内の物品による保管コスト又は管理コストを考慮して、オペレーションの効率化を考慮しつつ、倉庫内における物品の保管場所移動の効率化を向上させる。【解決手段】物流倉庫における作業計画支援装置は、倉庫内の移動候補在庫それぞれについて、現在の在庫位置データと、移動先の位置データと、作業コストに関する評価指標と、保管コストに関する評価指標とを取得し、作業コストに関する評価指標を使って、現在位置と移動先それぞれの作業コストとそれらの差分である作業コスト評価値とを算出し、保管コストに関する評価指標を使って、現在位置と移動先それぞれの保管コストとそれらの差分である保管コスト評価値とを算出し、作業コスト評価値と前記保管コスト評価値とを使って、倉庫内の移動候補在庫から作業計画に含める移動作業候補を選択し、移動作業候補を表示部に出力する。【選択図】図１

METHOD FOR DETERMINING A CONFIGURATION FOR PLACING AT LEAST ONE ITEM WITHIN A CONTAINER

Resumen de: WO2026061795A1

The invention relates to a method for determining a configuration for placing at least one item (ART) within a container (CNT), the method being implemented by an electronic device during order preparation, at an order-preparation station, for items to be placed within the container (CNT), the method comprising at least one iteration of the following steps: - capturing (S01) a datum representative of an available volume (VD) within the container (CNT); - obtaining (S04) a list (L1) of items to be placed within the container (CNT); - determining (S05) a volume (V1) of the items to be placed according to the list (L1) of the items to be placed; - depending on the volume (V1) of the items and on the datum representative of an available volume (VD) within the container (CNT), calculating (S06) the configuration (confP) for placing the items of the list (L1) of the items.

Deep Causal Learning for Continuous Testing, Diagnosis, and Optimization

Resumen de: US20260086514A1

A system and methods for multivariant learning and optimization repeatedly generate self-organized experimental units (SOEUs) based on the one or more assumptions for a randomized multivariate comparison of process decisions to be provided to users of a system. The SOEUs are injected into the system to generate quantified inferences about the process decisions. Responsive to injecting the SOEUs, at least one confidence interval is identified within the quantified inferences, and the SOEUs are iteratively modified based on the at least one confidence interval to identify at least one causal interaction of the process decisions within the system. The causal interaction can be used for testing, diagnosis, and optimization of the system performance.

SELF-POSITIONING OF ELECTRONIC SHELF LABEL (ESL) DEVICES THROUGH INTER-ESL LINKS

Resumen de: US20260086186A1

This disclosure provides systems, methods, and devices for Electronic Shelf Label (ESL) systems that support positioning of ESL devices. In a first aspect, a method includes: determining known positions of a first subset of ESL devices; receiving positioning measurements for each ESL device in a second subset of ESL devices; estimating a first position of each ESL device in the second subset based on the positioning measurements received for that ESL device and the known positions of the first subset; determining a positioning error associated with the first position of each ESL device in the second subset; and estimating a second position of each ESL device in the second subset based on the positioning error and additional positioning measurements received for that ESL device. Other aspects and features are also claimed and described.

情報処理システム、情報処理方法及びプログラム

Resumen de: WO2024161705A1

Problem To provide an information processing system, for example, that can reduce the number of batteries managed as stock. Solution One aspect of the present invention provides an information processing system. The information processing system comprises at least one processor capable of executing a program so as to carry out each of the following steps. In an acquisition step, use information of each of first batteries, which are those of batteries that are mounted on a plurality of mobility devices and used, is acquired. The batteries further include at least one second battery that is managed as stock, and the second battery is charged in a charging center and is delivered to a yard after being charged. The mobility devices are configured such that the first battery can be replaced with the second battery in the yard. In a delivery control step, determination of a specific yard that is a yard to which the second battery is delivered from the charging center is controlled according to the use information.

運搬車両管理方法

Resumen de: JP2026054210A

【課題】対策地域内廃棄物または放射性物質によって汚染された産業廃棄物を運搬する運搬車両を効率的に管理する方法を提供する。【解決手段】対策地域内廃棄物または放射性物質によって汚染された産業廃棄物を運搬し位置情報測定システムを搭載する運搬車両の集中管理を行うセンターが、運搬車両とセンターとの通信回線を介して、運搬車両の位置、運搬経路、および、チェックポイント通過時間を含む運搬情報を受信し、運搬情報をセンターの管理モニターに随時表示する、運搬車両管理方法。【選択図】図１

SYSTEM AND METHODS FOR ASSET TRACKING, ASSET GROUPING, AND ERROR RECOVERY

Resumen de: US20260089469A1

A method includes, generating a schedule for an asset tag group, the schedule defining: a multicast trigger time for transmission of a multicast trigger to the asset tag group; and for each asset tag in the asset tag group, a transmit time succeeding receipt of the multicast trigger and unique to the asset tag, and a wake window intersecting the transmit time and the receipt of the multiact trigger. The method also includes, at the node network: broadcasting the multicast trigger; and, at an asset tag in the asset tag group, entering a wake mode; receiving the multicast trigger; transmitting a ranging signal; and entering the sleep mode. The method further includes, at the node network: receiving ranging signals from the asset tag group; and deriving locations of the asset tags in the asset tag group based on the ranging signals received by the node network.

USING A MACHINE-LEARNING MODEL TO GENERATE SUBSEQUENT ORDERS FOR PREVIOUSLY UNOBTAINED ITEMS

Resumen de: US20260087534A1

An online system generates subsequent orders for users following failed attempts to purchase items. The online system receives a request to fulfill an order from a user device. The online system determines that an item from the order is unable to be fulfilled and generates a failed fulfillment signal for the item associated with the user. At a later time, the online system automatically generates a set of items for a subsequent order for the user, the set of items including at least one item substantially similar to the item that was unable to be fulfilled and predicted by a machine-learned model to be available. The online system transmits a notification to the user that the set of items is available for fulfillment.

SERVER DEVICE, PROVISION METHOD, AND RECORDING MEDIUM

Resumen de: US20260087450A1

In a server device, an intermittent appender intermittently appends to a report file for a store, at predetermined time intervals, log information of a record newly generated or updated in a database. Upon receiving a request for download of the report file from a store terminal, a supplementary appender appends to the report file the log information after the previous appending by the intermittent appender. Upon start of appending by the supplementary appender, a provider causes the intermittent appender to hold appending, and upon completion of the appending by the supplementary appender, provides the store terminal with the report file. Upon completion of providing the report file by the provider, a resumer initializes the report file, and then cancels holding of the intermittent appender to cause the intermittent appender to resume the appending.

OPTIMIZING TRUCK LOADING OF PALLETS

Resumen de: US20260087446A1

This specification generally discloses technology for optimizing the loading of pallets on trucks and other sorts of vehicles. A pallet loading technique includes receiving pallet information for a shipment, the pallet information describing pallets to be included in the shipment, receiving vehicle constraint information for a vehicle, the vehicle constraint information describing rules for loading pallets on the vehicle, and determining candidate solutions for loading the pallets on the vehicle, each candidate solution (i) satisfying the rules for loading pallets on the vehicle, and (ii) defining, for each pallet to be included in the shipment, a respective position and orientation of the pallet on the vehicle. At least some of the candidate solutions are evaluated, one of the candidate solutions is selected, and the vehicle is loaded according to the selected candidate solution.

ARTIFICIAL INTELLIGENCE AGENT USING LANGUAGE MODEL AND REINFORCEMENT LEARNING MODEL TO GUIDE PICKING PROCESS

Resumen de: WO2026064129A1

An artificial intelligence (Al) agent is disclosed that assists an entity to complete a task. The entity is assigned to complete a task. The Al agent monitors events to detect an occurrence of an event associated with the task. A machine learning model of the Al agent is prompted to generate a set of candidate actions based in part on the detected event and data about the entity. A reinforcement learning model of the Al agent scores each candidate action from the set to tailor the candidate actions to the entity. A scored action is selected as a recommended response to the event and is communicated to a client device of the entity which causes the entity to perform the selected action.

DETECTING ERRORS BASED ON INTERACTIONS OF USERS OF AN ONLINE SYSTEM WITH PHYSICAL DEVICES

Resumen de: WO2026064025A1

An online system uses a trained machine-learning model to detect errors in catalog data based on interactions of users of the online system with physical carts. Upon receiving an interaction signal indicating an interaction by the user with a device in a location of a source or an action signal indicating an action in the location of the source, the online system applies the trained model to the interaction signal and/or the action signal to generate an error score for an item that indicates a likelihood of an error in relation to the item. Responsive to the error score being above a threshold score, the online system generates an error checking signal for confirming that the error is present. Responsive to the confirmation of the error, the online system generates a user interface that alerts about the error and requests an action to correct the error.

ARTIFICIAL INTELLIGENCE (AI) AGENTS BASED DATA PROCESSING IN ENTERPRISE APPLICATIONS DEVELOPED BY CODELESS PLATFORM

Resumen de: US20260087447A1

The present invention provides a system and method for multi AI agent driven data processing in enterprise application developed by codeless platform. The invention includes one or more AI agents configured for processing one or more input received on conversational assistant interface. The invention includes triggering contextual processing of received input by orchestration agent interacting with multi-AI agents for executing a task identified from the received input.

DEEP LEARNING SYSTEM FOR DYNAMIC PREDICTION OF ORDER PREPARATION TIMES

Resumen de: US20260087306A1

A system and method are provided for dynamically updating a digital menu using deep-learning-based preparation-time prediction. A first deep learning neural network generates item-level embeddings for menu items based on historical preparation time records. Actual and estimated item-level preparation time vectors are generated using cosine-similarity weighting across subsets of the historical data. A second deep learning neural network is trained using the item-level vectors, ground-truth preparation times, and normalized non-categorical metadata processed through dense vector layers and concatenation. The trained network is executed to generate predicted item-level preparation times for menu items currently available for ordering. An updated digital menu including the predicted item-level preparation times is generated and transmitted to a client device, and the digital menu is automatically updated in real time on the client device in response to changes in the predicted preparation times.

SYSTEMS AND METHODS FOR PERFORMING VENDOR-AGANOSTIC CTO/QTO (CONFIGURE TO ORDER/QUOTE TO ORDER)

Resumen de: AU2025226868A1

- 1 - Computerized systems and methods are described for managing vendor-agnostic configure-to-order (CTO) and quote-to-order (QTO) processes. A Real-Time Data Mesh (RTDM) is provided for aggregating, standardizing, and normalizing real-time data from various sources. A Single Pane of Glass User Interface (SPoG UI) facilitates dynamic interaction and visibility into vendor performance. An Advanced Analytics and Machine- Learning (AAML) Module analyzes product compatibility, optimizes pricing strategies, and predicts market trends. A Vendor-Agnostic CTO/QTO Integration Module (VACIM) includes a Process Standardization Engine and a Vendor Data Transformation Gateway to ensure uniformity across vendors. Methodologies within the invention automate data processing, integrate transformation gateways for data consistency, and employ rule engines driven by machine learning for decision-making, thereby streamlining vendor processes, enhancing scalability, and optimizing pricing strategies in a scalable, adaptable framework. Computerized systems and methods are described for managing vendor-agnostic configure-to-order (CTO) and quote-to-order (QTO) processes. A Real-Time Data Mesh (RTDM) is provided for aggregating, standardizing, and normalizing real-time data from various sources. A Single Pane of Glass User Interface (SPoG UI) facilitates dynamic interaction and visibility into vendor performance. An Advanced Analytics and Machine- Learning (AAML) Module analyzes product compatibili

PROBABILISTIC EVENT TRIGGERING USING LOCATION DATA

Resumen de: US20260087445A1

Techniques for determining an estimated time of arrival at a pickup location are discussed herein. For example, techniques may include receiving first location data from a user computing device approaching a pickup location, receiving data indicating when the device entered a virtual boundary associated with the pickup location, determining a location of the device when it was a particular time period away from entering the virtual boundary, associating the location with a discretized location of a map, applying a blurring function to generate a probability field indicating probability of entering the virtual boundary within the time period, using the probability field to determine probability of arriving at the pickup location within the particular time period, and triggering an action based on the probability meeting a threshold.

AUTOMATED DEVICE FOR CROSS-BORDER E-COMMERCE AND METHOD FOR CONTROLLING SAME

Resumen de: WO2026063564A1

An automated device for cross-border e-commerce and a method for controlling same are disclosed. The automated device according to one embodiment of the present invention comprises: a database that stores data; and a processor that controls the automated device, wherein the processor may, when a preset word representing a popular search term is identified while scraping a web page, extract keywords searched at a preset frequency or higher and store the keywords in the database, search a shopping platform using the extracted and stored keywords, store a shopping mall URL address searched on the shopping platform in the database, and store product data of the shopping mall in the database using the stored shopping mall URL address.

SYSTEM AND METHOD FOR SECURE PRODUCT TRACKING AND AUTHENTICATING USING GEO-TAGGING AND MACHINE-READABLE CODE INTEGRATION

Resumen de: WO2026062473A1

A system for secure product tracking and authentication using geo-tagging and machine-readable code integration is disclosed. The system includes a first computing device comprises a geo-tag and code generation module that creates a unique geo-tag for each product, embedding authorized data such as licenses, permissions, and trademark registrations. This geo-tag is paired with a machine-readable code containing product-specific details and a time-stamp, which is then embedded onto the product's packaging by a connected packing machine. A second computing device allows users to track the product across the supply chain, displaying real-time information on the product's location, status, and authenticity. A server manages and analyzes this data in real-time, ensuring regulatory compliance and detecting potential tampering. A scanning device reads the machine-readable code at various checkpoints, updating the product's status and transmitting data to the server, where alerts and notifications are generated based on analyzed data.

Wearable device for analytics data collection

Nº publicación: AU2025230708A1 26/03/2026

Solicitante:

AUGMODO INC
Augmodo Inc

Resumen de: AU2025230708A1

A wearable device has a body with one or more connectors for coupling the body to a lanyard. A camera assembly is mounted on the body. The camera assembly includes a pair of cameras configured to capture images of an environment surrounding the wearable device. The wearable device also includes a network adapter to transmit data derived from the captured images to a processing system. ep w e a r a b l e d e v i c e h a s a b o d y w i t h o n e o r m o r e c o n n e c t o r s f o r c o u p l i n g t h e b o d y t o a e p l a n y a r d c a m e r a a s s e m b l y i s m o u n t e d o n t h e b o d y h e c a m e r a a s s e m b l y i n c l u d e s a p a i r o f c a m e r a s c o n f i g u r e d t o c a p t u r e i m a g e s o f a n e n v i r o n m e n t s u r r o u n d i n g t h e w e a r a b l e d e v i c e h e w e a r a b l e d e v i c e a l s o i n c l u d e s a n e t w o r k a d a p t e r t o t r a n s m i t d a t a d e r i v e d f r o m t h e c a p t u r e d i m a g e s t o a p r o c e s s i n g s y s t e m Local Network Wearable Device Wearable Device Base Station Wearable Device Wide Area Network Server Charging Dock Server Wide Area Network Base Station Charging Dock Local Network Wearable Wearable Device Device 110A Wearable 110N Device ep e p e r v e r i d e r e a a s e t a t i o n e a r a b l e e a r a b l e e a r a b l e