Study of LoRaWAN Technology for Activity Recognition

Reviewed
Tahera Hossain, Yusuke Doi, Tahia Tazin, Md Atiqur Rahman Ahad, Sozo Inoue,
Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA)
(Not Available)
(Not Available)
5 pages
2018-10-12
Singapore
http://hasca2018.hasc.jp/
In this paper, we explore LoRaWAN (Long Range Wide
Area Network) sensor for human activity recognition. In
this research, we want to verify activity recognition by
using LoRaWAN devices. We want to explore relation
between packet loss and activity recognition accuracy
from LoRaWAN sensor data. Afterwards, we study
LoRaWAN sensors data transfer ability in a real
caregiving center. We want to estimate the packet loss
amount from realistic sensors. In LoRaWAN technology,
the amount of sensor nodes connected with a single
gateway have an impact on the performance of sensors
ultimate data sending capability in terms of packet loss.
By exploring a single gateway, we transfer the
LoRaWAN sensor data to the cloud platform
successfully. We evaluate LoRaWAN accelerometer
sensors data for human activity recognition. We explore
the Linear Discriminant Analysis (LDA), Random Forest
(RnF) and K-Nearest Neighbor (KNN) for classification.
We achieve recognition accuracy of 94.44% by LDA,
84.72% by RnF and 98.61% by KNN. Then we simulate
the packet loss environment in our dataset to explore
the relation between packet loss and accuracy. In real
caregiving center, we did experiment with 42 LoRaWAN
sensors node connectivity and data transfer ability to
evaluate the packet received and packet loss
performance with LoRaWAN sensors.

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