The rapid development of modern Information and Communication Technologies (ICTs) in recent years and their introduction into people’s daily lives worldwide, has led to new circumstances at all levels of the social environment. In health care in particular, sensors and data links offer potential for constant monitoring of patient’s symptoms and needs, in real time, enabling physicians to diagnose and monitor health problems wherever the patient is, either at home or outdoors. However, the use of Internet of Things concepts in the health domain does not come without extra data and therefore a data transfer cost overheads. To deal with these overheads, novel metrics, and methods are introduced in an attempt to maximize the capabilities and widen acceptance/usage provided by the Internet of Things. Without losing its generality, the method discussed is experimentally evaluated in the paradigm of the Health domain. The focus is on the need for an overview of available data formats and transmission methods and selection of the optimal combination, which can result to reduction/minimization of costs. An analytic methodology is presented backed with theoretical metrics and evaluated experimentally.
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