8 results about "Scalable design" patented technology

Methods, systems, and devices for wireless communications are described. A forwarding device (e.g., a reconfigurable intelligent surface (RIS)) may transmit a capability message indicating one or more timing parameters associated with a time duration for the forwarding device to switch a set of forwarding elements from forwarding in a first direction to forwarding in a second direction. The forwarding device may receive, based on the indicated one or more timing parameters, one or more control messages that instructs the forwarding device to forward signal energy in the first direction during a first symbol period and to forward signal energy in the second direction during a second symbol period. The first symbol period may be different from the second symbol period. The forwarding device may include a primary array including a first set of forwarding elements and a secondary array including a second set of forwarding elements.

An autonomous and adaptable AI-powered robotic workstation system is designed for diverse real-world applications. This includes a configurable workstation seamlessly integrating a dynamic robotic hand, endowed with real-time decision-making capabilities. The workstation features an automatic calibration and self-configuration mechanism utilizing six-axis motion for task execution, ensuring alignment and auto-positioning via cameras. A dynamic and no-code onboarding process with auto-calibration captures and stores product onboarding, optimization of object categorization and prioritizing captures using vision AI. The system also includes a vision-based operations module with AI-driven functionality, integrated hardware, scalable design, calibration capabilities, and unification of specified operations within the same workstation system.

Systems and methods for resource management using a scalable resource management database are provided. A resource management tool accesses a resource management database. The resource management tool determines a size of an attribute value corresponding to an attribute of a resource instance satisfies a predetermined size threshold. The resource management tool determines a query frequency associated with the attribute value satisfies a predetermined frequency threshold. The resource management tool creates a value index table based on a value table, the value index table excluding the attribute value satisfying the predetermined size threshold and the predetermined frequency threshold.

Systems and methods for resource management using a scalable resource management database are provided. A resource management tool accesses a resource management database. The resource management tool determines an attribute value corresponding to an attribute of a resource instance comprises an object array. The object array includes a plurality of array features. The resource management tool converts the plurality of array features to a plurality of converted attributes. The resource management tool updates an attribute table by replacing the attribute of the resource instance with the plurality of converted attributes for the resource instance. The resource management tool updates a value table by adding one or more group identifications for grouping a plurality of attribute values corresponding to the plurality of converted attributes for the resource instance.

The invention relates to a method for the scalable design of an electric drive unit.The inventive method for the scalable design of an electric drive unit using a computer-aided system comprises the input of scaling or parameterizing input values ​​for geometric and performance-related characteristics of the electric drive unit, the processing of the input values ​​by a pre-trained AI surrogate model based on a training database of empirical benchmark data and / or simulation-based data, and the output of predicted electromagnetic, thermal, and / or cost-related output values, wherein, after the output, a confidence assessment of the predicted output values ​​is carried out and, if a predetermined confidence criterion is not met, a physical simulation is automatically triggered, the simulation results of which are fed back to the training database for the extension of the AI ​​surrogate model.

Systems and methods for resource management using a scalable resource management database are provided. A resource management tool accesses a resource management database. The resource management tool determines an attribute value corresponding to an attribute of a resource instance comprises an object array. The object array includes a plurality of array features. The resource management tool converts the plurality of array features to a plurality of converted attributes. The resource management tool updates an attribute table by replacing the attribute of the resource instance with the plurality of converted attributes for the resource instance. The resource management tool updates a value table by adding one or more group identifications for grouping a plurality of attribute values corresponding to the plurality of converted attributes for the resource instance.

Disclosed herein are system, method, and device embodiments for deploying a highly reliable, consensus-based agentic AI system that processes natural language requests to provide deterministic, consistent, and verifiably accurate responses. The agentic AI system may prioritize reliability, transparency, trustworthiness, and deterministic behavior using structured communication, consensus mechanisms, and a scalable design. The capability to provide deterministic behavior and consistent outcomes may make the consensus-driven genetic AI tool especially suitable for applications requiring high levels of accuracy and trust.

The present invention relates to a remote AI monitoring and control unit designed for industrial automation. This unit integrates multiple communication protocols, advanced artificial intelligence (AI) capabilities, and enhanced security features to autonomously or semi-autonomously monitor and control industrial processes. The unit supports a wide range of communication protocols, including MQTT, USART, CAN bus, I2C, SPI, Modbus, Profibus, DeviceNet, EtherNet / IP, CANopen, PROFINET, BACnet, DNP3, and HART, ensuring seamless interoperability with various industrial devices. It features adaptive communication, predictive maintenance, anomaly detection, and edge AI processing. Enhanced security is achieved through blockchain integration, AI-based threat detection, and multi-layered encryption. The unit also incorporates energy-efficient operation with energy harvesting and AI-optimized power management. An augmented reality (AR) interface provides real-time data visualization and remote assistance. The modular and scalable design allows for easy customization and expansion, while a user-friendly software interface offers customizable dashboards and AI-driven insights.