Smartwatches as IoT Edge Devices: A Framework and Survey

Abstract

Smartwatches have finally come of age and represent a unique platform for building IoT applications involving people. Today, smartwatches are used in various IoT scenarios including healthcare and fitness. Since the current smartwatches are equipped with a variety of sensors and heterogenous wireless protocols, they can be used to enact a variety of people-based Social Internet of Things (SIoT). Such applications involve sending sensor data from millions of watches through the IoT cloud. Processors on current watches are powerful enough to run even deep learning algorithms and may support peak download data rates of more than 50 Mbits/second. However, battery life remains a limiting factor. Most smartwatch applications capture and process context. This paper provides a survey and framework based on context computation, edge analytics, and computation off-loading as applied to IoT applications using smartwatches. This framework can be a basis of meaningful discussion of various solutions to address various technical problems like short battery life of smartwatches when used in IoT applications.