Schmitz, Martin and Herbers, Martin and Dezfuli, Niloofar and Günther, Sebastian and Mühlhäuser, Max (2018):
Off-Line Sensing: Memorizing Interactions in Passive 3D-Printed Objects.
In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, ACM, In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Montréal, Canada, In: CHI '18, ISBN 978-1-4503-5620-6,
DOI: 10.1145/3173574.3173756,
[Online-Edition: https://doi.org/10.1145/3173574.3173756],
[Conference or Workshop Item]

Abstract

Embedding sensors into objects allow them to recognize various interactions.However, sensing usually requires active electronics that are often costly, need time to be assembled, and constantly draw power. Thus, we propose off-line sensing: passive 3D-printed sensors that detect one-time interactions, such as accelerating or flipping, but neither require active electronics nor power at the time of the interaction. They memorize a pre-defined interaction via an embedded structure filled with a conductive medium (e.g., a liquid). Whether a sensor was exposed to the interaction can be read-out via a capacitive touchscreen. Sensors are printed in a single pass on a consumer-level 3D printer. Through a series of experiments, we show the feasibility of off-line sensing.

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