CalAmp‘s patent involves using machine learning to detect abnormal driving behavior through vehicle telematics data. The system calculates a driver risk score and can engage safety systems based on identified anomalies. This innovation aims to enhance vehicle safety by proactively addressing risky driving behaviors. GlobalData’s report on CalAmp gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on CalAmp, Vehicle fault diagnosis automation was a key innovation area identified from patents. CalAmp's grant share as of April 2024 was 69%. Grant share is based on the ratio of number of grants to total number of patents.
Vehicle safety system based on driver risk score
The granted patent (Publication Number: US11919523B2) discloses a method for engaging a vehicle safety system based on driver risk score and data received from a vehicle telematics device. The method involves identifying safety violations, generating safety control signals, and engaging safety systems such as engine, brakes, transmission, ignition, and autonomous driving system to ensure safe operation of the vehicle. Additionally, the method includes alerting the driver of unsafe behavior through visual and/or audible alerts from display and audio devices mounted in the vehicle.
Furthermore, the patent details the process of obtaining a driver risk score by analyzing data from the vehicle telematics device, identifying anomalies through unsupervised machine learning, and calculating the risk score based on these anomalies. The safety violations are determined by comparing the data to a reference threshold value, which is influenced by the driver risk score. The method also allows for the engagement of multiple safety systems based on different safety control signals, with confirmation of their response through sensor data from the vehicle. Overall, the patent aims to enhance vehicle safety by proactively engaging safety systems based on real-time data and driver behavior analysis.
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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.
