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NannyCaps - Monitoring Child Conditions and Activity in Automotive Applications Using Capacitive Proximity Sensing

 
: Frank, Sebastian; Kuijper, Arjan

:

Stephanidis, Constantine (Ed.):
HCI International 2020 - Late Breaking Papers. 22nd HCI International Conference, HCII 2020. Proceedings : Digital Human Modeling and Ergonomics, Mobility and Intelligent Environments; Copenhagen, Denmark, July 19-24, 2020, held virtually
Cham: Springer Nature, 2020 (Lecture Notes in Computer Science 12429)
ISBN: 978-3-030-59986-7 (Print)
ISBN: 978-3-030-59987-4 (Online)
S.67-82
International Conference on Human-Computer Interaction (HCI International) <22, 2020, Online>
Englisch
Konferenzbeitrag
Fraunhofer IGD ()
capacitive proximity sensing; Lead Topic: Smart City; Research Line: Human computer interaction (HCI); capacitive proximity sensing; advanced driver assistance systems (ADAS); physical activity monitoring

Abstract
Children have to be transported safely. Securing children in a child seat is indicated. Due to structure and restraint systems, children are secured in case of an accident. Children require our attention to keep them healthy and at good mood. Nonetheless, attention must be payed to driving, too. This discrepancy leads to unattended children. Furthermore, responsible must decide to leave their children alone in the vehicle in case of emergencies. This may lead to heat strokes. Aside of limiting effects of an accident, it would be helpful to assist ambulance after an emergency and to detect injuries even without accident. Besides safety features, preserving good mood of children is an exquisite comfort feature. This can be achieved without privacy issues as they would occur using camera-based systems. The proposed solution, NannyCaps, is designed to contribute to safety and comfort. An invisible array of capacitive proximity sensors enables head position recognition, sleep state recognition, heart rate recognition and occupancy recognition. The system is included into the child seat, only. In this paper, we present the design and implementation of Nanny- Caps. By conducting ten test runs under real world conditions, more than 600km of data is collected. Using this data, NannyCaps is trained and evaluated. Reasonable results are shown in evaluation. Thus, following the development of NannyCaps will likely improve the situation for children in transportation systems.

: http://publica.fraunhofer.de/dokumente/N-608790.html