Activity Recognition by Using LoRaWAN Sensor

Low Power Wide Area (LPWA) technologies are monumental for the IoT sector. In this paper, we explore LoRaWAN (LoRa Wide Area Network) sensor for human activity recognition. 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 service.