NXP Semiconductors had nine patents in big data during Q1 2024. NXP Semiconductors NV has developed a layered architecture for managing the health of electronic systems by utilizing predictive data analytics to determine and improve the health condition. They have also patented a data processing system for cryptographic operations in lattice-based cryptography and a method for protecting machine learning models from side channel attacks by computing weighted sums with randomized negations. GlobalData’s report on NXP Semiconductors gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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NXP Semiconductors grant share with big data as a theme is 33% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Layered architecture for managing health of an electronic system and methods for layered health management (Patent ID: US20240020186A1)
The patent filed by NXP Semiconductors NV describes a layered architecture for managing the health of an electronic system. This architecture includes multiple health subsystems that receive health information from health monitors connected to various components of the system. The health subsystems then use predictive data analytics to determine the system's health condition and update health policies to enhance the prediction of the system's health condition. The method involves sending health information through different layers of the system, determining the health condition based on received information, and updating health policies accordingly.
Furthermore, the system described in the patent includes health monitors, first and second layer health subsystems, a third layer health subsystem, and a fourth layer health subsystem on a cloud compute. Each layer is responsible for receiving, analyzing, and transmitting health information to the next layer. The third layer health subsystem determines the system's health condition based on predictive data analytics and the received health information, while the fourth layer health subsystem updates the health policy based on the information received from the third layer. The system also involves broadcasting health policies, storing health information in non-volatile memory, receiving operational requests based on the health condition, and implementing various actions such as powering off components or changing the system's mode based on the determined health condition.
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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.
