Siemens had 103 patents in digitalization during Q2 2024. Siemens AG filed patents in Q2 2024 for methods and devices related to calibrating digital twins of complex systems, optimizing recycling processes for electronic components, assessing datasets using machine learning algorithms, providing information from medical record databases, and automatically tuning digital twins of physical systems using adaptive filtering. These inventions aim to improve accuracy, efficiency, and effectiveness in various technological applications. GlobalData’s report on Siemens gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Siemens had no grants in digitalization as a theme in Q2 2024.
Recent Patents
Application: Real-time calibration for detailed digital twins (Patent ID: US20240210933A1)
The patent filed by Siemens AG describes a method for calibrating a digital twin of a physical complex system by receiving sensor data, calculating an error between the digital twin and the physical system, generating candidate parameters based on a gradient optimization, applying these parameters to the digital twin, and recalculating the error until it meets a user-defined tolerance. The process involves iterative steps to continuously refine the digital twin's parameters based on the sensor data and the system's state, ensuring accurate representation and calibration.
Furthermore, the system described in the patent includes a computer processor and memory storing instructions to create a digital twin, receive sensor data, calculate errors, determine gradients, generate candidate parameters, update the digital twin's output, and recalibrate the error value iteratively. The digital twin is based on a parametric differentiable model that combines physics-based models and sensor data, with the calibration process involving gradient optimization and machine learning techniques. The system is designed for space-rich 3D systems like building control systems, enabling real-time calibration and scenario analysis for improved performance and energy efficiency based on sensor data.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
