Ford Motor has patented a system for removing personally identifiable information (PII) from sensor data captured by a vehicle. The system uses object detection and semantic labeling to classify regions as public or private based on location, ensuring data privacy compliance. GlobalData’s report on Ford Motor 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 Ford Motor, Hydrogen fuel cells was a key innovation area identified from patents. Ford Motor's grant share as of April 2024 was 62%. Grant share is based on the ratio of number of grants to total number of patents.

System for removing personally identifiable information from vehicle sensor data

Source: United States Patent and Trademark Office (USPTO). Credit: Ford Motor Co

A recently granted patent (Publication Number: US11972015B2) discloses a system and method for the removal of personally identifiable information (PII) using sensors and controllers. The system involves capturing sensor data, performing object detection, creating a 3D depth mapping, and fusing this data with high definition maps to classify regions as public or private based on a PII filter. The system can obfuscate private regions and request customer attestation for further privacy protection.

The patent also covers a method for PII removal in vehicles, where sensor data is processed to identify objects, map the surroundings, and classify regions as public or private. The method includes obfuscating private regions and requesting customer attestation for additional privacy measures. Additionally, a non-transitory computer-readable medium with instructions for PII removal in vehicles is detailed, allowing for the execution of processes like object detection, data fusion, and classification based on a PII filter. The medium also enables the obfuscation of private regions and the downloading of PII filters via a transceiver for enhanced data protection.

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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.