TY - GEN
T1 - Sensor Fusion and Device Collaboration based Smart Plug Hub Architecture for Precise Identification of ADL in Real-Time
AU - Kang, Homin
AU - Kang, Soon Ju
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In this paper, we propose a Smart Plug Hub Architecture for real-time measurement of Activities of Daily Living (ADL), a medical index indicating daily living performance. Currently, ADL is evaluated through patient interviews, behavioral videos, or behavioral tracking through wearable devices. However, the above methods have problems such as low accuracy and privacy violation. SPH overcomes the above problems through sensor fusion and device collaboration. SPH predicts the situation by detecting environmental changes according to human behavior through various environmental sensors. In order to analyze continuous environmental data effectively, a technique of analyzing data divided by each part is used by receiving a segmentation triggering a signal that allows data to be analyzed by region from surrounding IoT devices. By visualizing the collected data, SPH was able to predict in real-time specific human behavior in various environments.
AB - In this paper, we propose a Smart Plug Hub Architecture for real-time measurement of Activities of Daily Living (ADL), a medical index indicating daily living performance. Currently, ADL is evaluated through patient interviews, behavioral videos, or behavioral tracking through wearable devices. However, the above methods have problems such as low accuracy and privacy violation. SPH overcomes the above problems through sensor fusion and device collaboration. SPH predicts the situation by detecting environmental changes according to human behavior through various environmental sensors. In order to analyze continuous environmental data effectively, a technique of analyzing data divided by each part is used by receiving a segmentation triggering a signal that allows data to be analyzed by region from surrounding IoT devices. By visualizing the collected data, SPH was able to predict in real-time specific human behavior in various environments.
KW - Activities of Daily Living
KW - Device Collaboration
KW - Edge Computing
KW - Sensor Fusion
KW - Signal Processing
UR - http://www.scopus.com/inward/record.url?scp=85141132795&partnerID=8YFLogxK
U2 - 10.1109/ISCC55528.2022.9913055
DO - 10.1109/ISCC55528.2022.9913055
M3 - Conference contribution
AN - SCOPUS:85141132795
T3 - Proceedings - IEEE Symposium on Computers and Communications
BT - 2022 IEEE Symposium on Computers and Communications, ISCC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 27th IEEE Symposium on Computers and Communications, ISCC 2022
Y2 - 30 June 2022 through 3 July 2022
ER -