Inference of Personal Sensors in the Internet of Things

  • James Jin Won Kang Deakin University
  • Henry Larkin Deakin University

Abstract

Smartphone technology has become more popular and innovative over the last few years, and technology companies are now introducing wearable devices into the market. By emerging and converging with technologies such as Cloud, Internet of Things (IoT) and Virtualization, requirements to personal sensor devices are immense and essential to support existing networks, e.g. mobile health (mHealth) as well as IoT users. Traditional physiological and biological medical sensors in mHealth provide health data either periodically or on-demand. Both of these situations can cause rapid battery consumption, consume significant bandwidth, and raise privacy issues, because these sensors do not consider or understand sensor status when converged together. The aim of this research is to provide a novel approach and solution to managing and controlling personal sensors that can be used in various areas such as the health, military, aged care, IoT and sport. This paper presents an inference system to transfer health data collected by personal sensors efficiently and effectively to other networks in a secure and effective manner without burdening workload on sensor devices.

Author Biography

James Jin Won Kang, Deakin University

James Kang is currently a Ph.D. candidate  at the School of Information Technology in Deakin University, Australia with interests in mHealth networks, IoT, big data and Health Informatics. He has worked in the ICT industry for over 20 years in roles such as solutions design, testing, deployment, operation and technical support. He has specialised in Intelligent Networks for wired and mobile networks during the earlier stages of his career, and later worked on IP, IMS, NGN and VoIP technologies. James has experience with major solutions and service providers such as LG, Telecom NZ, Vodafone, Siemens, Telstra, Alcatel-Lucent and NBN Co. He has recently went to Africa as a volunteer IT advisor sponsored by the Australian government (DFAT) to help NGOs.

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Published
2016-01-26
How to Cite
KANG, James Jin Won; LARKIN, Henry. Inference of Personal Sensors in the Internet of Things. International Journal of Information, Communication Technology and Applications, [S.l.], v. 2, n. 1, p. 1-23, jan. 2016. ISSN 2205-0930. Available at: <https://www.ijicta.org/index.php/ijicta/article/view/25>. Date accessed: 23 aug. 2017. doi: https://doi.org/10.17972/ijicta20162125.
Section
Articles

Keywords

Inference; Data Mining; mHealth; Personal Sensor Devices; WBAN; Sensor Networks; IoT; Big Data; Cloud Computing