Low-Cost, Edge-Cloud, End-to-End System Architecture for Human Activity Data Collection

Abstract

Research in the Internet of Things (IoT) have paved the way to a new generation of applications and services that collect huge quantities of data from the field and do a significant part of the processing on the edge. This requires availability of efficient and effective methodologies and tools for a workflow spanning from the edge to the cloud. This paper presents a generic, complete workflow and relevant system architecture for field data collection and analysis with a focus on the human physical activities. The data source is given by a low-cost embedded system that can be placed on the user body to collect heterogeneous data on the performed movements. The system features a 9 DoF IMU sensor, to ensure a high level of configurability, connected to a custom board equipped with a rechargeable battery for wireless data collection. Data are transmitted via Bluetooth Low Energy (BLE) to a smartphone/tablet app, which manages the data transfer to Measurify, a cloud-based open-source framework designed for building measurement-oriented applications. Results from a preliminary functional experiment confirm the ability of the proposed end-to-end system architecture to efficiently implement the whole targeted edge-cloud workflow.