Indoor Positioning and Fall Detection System Without Wearables

<redacted>

Bachelor thesis (2023)

Authors

G.W. Mulder Electrical Engineering, Mathematics and Computer Science
K.N. Hernández Salvador Electrical Engineering, Mathematics and Computer Science
M.T. Baroud Electrical Engineering, Mathematics and Computer Science

Contributors

P.J. French Bio-Electronics - EEMCS (mentor)
K. Rassels Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering (mentor)
İlke Ercan Electrical Engineering Education - EEMCS (coach)
Tiago Costa Bio-Electronics - EEMCS (coach)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2023 Gerben Mulder, Kim Hernández Salvador, Mounzir Baroud
More Info
expand_more

Published Date

27-06-2023

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

This thesis report, one of a set of two reports, describes a novel way to detect incidents that could occur in the daily life of the elderly. Unlike most systems already implemented in this field, this system does not use any wearable (positioning) sensors and works off an Single Board Computer (SBC).Independent of both of these systems is a system for reassurance to alleviate distress.