Abstract
Low-Power Wide Area Networks have contributed in several parts of the Internet of Things ecosystem during the last years by enabling long range, robust and low power communication. Machine Learning for embedded systems has also assisted the advancement of the Internet of Things by identifying patterns and increasing the accuracy of predicting events and behaviours. At the same time, wearable and mobile systems are less obtrusive, consuming less energy and have more computing resources. In this paper we combine these three components and propose a low cost wearable system based on a regular shoe and off-the-shelf electronics which is able to recognize foot gestures and transmit messages over long range, in cases of emergency. The evaluation considers an application scenario where the user performs specific foot gestures to trigger the transmission of an emergency message, during other activities (e.g., walking). The proposed wearable system would benefit a user who is in danger and attempts to notify her/his emergency contacts in a discreet manner. Results show that the proposed system is able to identify the intended foot gestures with 98% accuracy.
Original language | English |
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Title of host publication | Proceedings of the 5th IEEE PerCom Workshop on Pervasive Health Technologies |
Number of pages | 6 |
Publisher | IEEE |
Publication date | 2021 |
ISBN (Print) | 978-1-7281-4716-1 |
Publication status | Published - 2021 |
Event | 6th IEEE PerCom Workshop on Pervasive Health Technologies - Virtual event, Kassel, Germany Duration: 22 Mar 2020 → 26 Mar 2020 |
Workshop
Workshop | 6th IEEE PerCom Workshop on Pervasive Health Technologies |
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Location | Virtual event |
Country/Territory | Germany |
City | Kassel |
Period | 22/03/2020 → 26/03/2020 |
Keywords
- IoT
- LPWAN
- Pervasive Health
- Wearable
- Foot Gesture