Identifying risky environments for COPD patients using smartphones and internet of things objects

Abstract

This paper overviews the capabilities offered by the smartphones as advanced computing devices for healthcare applications, focusing on the prevention of short-term complications of chronic obtrusive pulmonary disease COPD patients, using personalised decision making. Data provided by the embedded smartphone sensors, wearable wireless body area networks and internet of things objects are incorporated in a framework that evaluates and alerts the COPD patient for potentially risky environmental conditions in the proximal area. Data processing schemas are presented, distributing the execution of the calculations between the smartphone and a cloud-hosted service, achieving the ideal equilibrium between processing speed, system scalability and battery life of the mobile devices.