Delivering Reliability of Data Sources in IoT Healthcare Ecosystems

Contributing authors


Nowadays, the use of Internet of Things (IoT) in various different fields has made significant progress, especially in the field of healthcare, where a myriad of heterogeneous medical data sources are in use. This fact has reinforced the vision of developing new communication technologies and finding new ways to synchronize and successfully manage all these data sources. However, this vision is accompanied by several related challenges. One of these challenges refers to the fact that since all the existing IoT medical data sources are usually characterized by a high degree of heterogeneity, they are expected to be recognized as reliable at different stages, thus providing data of different levels of reliability. To effectively tackle this challenge, the present paper proposes a mechanism for capturing the reliability levels of different IoT medical data sources, so as to automatically decide whether these will be considered as reliable or not, and thus their data will be kept for further analysis. In this context, in this mechanism three (3) discrete stages are implemented, facilitating both the data reliability and the availability estimation of these data sources, making finally feasible the manipulation of these sources and the estimation of their overall reliability levels. The prototype associated with this paper provides an example of this mechanism, demonstrating in detail each discrete stage.