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2020 | OriginalPaper | Chapter

Privacy by Design: Analysis of Capacitive Proximity Sensing as System of Choice for Driver Vehicle Interfaces

Authors : Sebastian Frank, Arjan Kuijper

Published in: HCI International 2020 – Late Breaking Papers: Digital Human Modeling and Ergonomics, Mobility and Intelligent Environments

Publisher: Springer International Publishing

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Abstract

Data collection is beneficial. Therefore, automotive manufacturers start including data collection services. At the same time, manufacturers install cameras for human machine interfaces in vehicles. But those systems may disclose further information than needed for gesture recognition. Thus, they may cause privacy issues.

The law (GDPR) enforces privacy by default and design. Research often states that capacitive proximity sensing is better to serve privacy by design than cameras. Furthermore, it is unclear if customers value privacy preserving features. Nonetheless, manufacturers value the customer’s voice.

Therefore, several vehicular human machine interface systems, with camera or capacitive proximity sensing, are analyzed. Especially concerning gesture recognition, capacitive proximity sensing systems provide similar features like camera-based systems. The analysis is based on the GDPR privacy definition. Due to the analysis, it is revealed that capacitive proximity sensing systems have less privacy concerns causing features. Subsequently, three hypotheses are formulated to capture the customer’s voice.

Due to analysis results, it is questionable if gesture recognition systems, which utilize cameras, are compliant with privacy by design. Especially since well-known systems like capacitive proximity sensing are available. A survey concerning the hypotheses will give further insights in future work.

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Title: Privacy by Design: Analysis of Capacitive Proximity Sensing as System of Choice for Driver Vehicle Interfaces
Authors: Sebastian Frank
Arjan Kuijper
Publisher: Springer International Publishing
Book: HCI International 2020 – Late Breaking Papers: Digital Human Modeling and Ergonomics, Mobility and Intelligent Environments
Print ISBN: 978-3-030-59986-7

Electronic ISBN: 978-3-030-59987-4

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-59987-4_5