Title: Identifying risky environments for COPD patients using smartphones and internet of things objects
Authors: Ioannis Kouris; Dimitris Koutsouris
Addresses: National Technical University of Athens, 9, Her?on Polytechniou str., 15773 Zografou, Athens, Greece ' National Technical University of Athens, 9, Her?on Polytechniou str., 15773 Zografou, Athens, Greece
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.
Keywords: smartphones; activity recognition; internet of things; IoT objects; pattern recognition; emerging patterns; risky environments; chronic obtrusive pulmonary disease; COPD patients; healthcare technology; short-term complications; personalised decision making; e-healthcare; electronic healthcare; embedded sensors; smartphone sensors; wearable computing; wireless BANs; body area networks; risk identification; cloud computing; mobile devices.
International Journal of Computational Intelligence Studies, 2014 Vol.3 No.1, pp.1 - 17
Received: 01 Jun 2012
Accepted: 25 Jul 2012
Published online: 13 Jan 2014 *