Activity Recognition by Using LoRaWAN Sensor

Tahera Hossain, Tahia Tazin, Md Atiqur Rahman Ahad, Sozo Inoue,
ACM Int'l Conf. Pervasive and Ubiquitous Computing (Ubicomp) Poster
(Not Available)
(Not Available)
Low Power Wide Area (LPWA) technologies are
monumental for the IoT sector. Among the LPWA
technologies, long range (LoRa) and narrowband (NB)-
IoT are two promising technologies. In this paper, we
explore LoRaWAN (LoRa Wide Area Network) sensor for
human activity recognition. To support the ageing

population in the world, assisted living and sensor-
based human activity recognition are important

research areas. In this research, we propose an activity
recognition framework by exploiting LoRaWAN sensor
and its accelerometer data. In our framework, we
explore Arduino Uno, Arduino Lucky Shield having a
number of different sensors, and LoRaWAN to build one
compact system. By exploring a LoRaWAN Gateway, we
transfer the sensor data to SORACOM cloud platform
successfully. Then from the cloud data, a few statistical
features are computed to classify three activities such
as walk, stay and run. We aggregate the time series
data into different action labels that summarize the
user activity over a time interval. After, we train data
to induce a predictive model for activity recognition. We
explore the K-Nearest Neighbor (KNN) and Linear
Discriminant Analysis (LDA) for classification. We
achieve recognition accuracy 80% by KNN and 73.3%
by LDA. The result provides promising prospect for
LoRaWAN sensor for improving healthcare monitoring

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