Following a peer-review process, Sensors MDPI Journal has accepted to publish a scientific manuscript, co-authored by UBITECH’s Konstantinos Perakis and Stamatis Pitsios, entitled “IoT in Healthcare: Achieving Interoperability of High-Quality Data Acquired by IoT Medical Devices”. Konstantinos Perakis, Stamatis Pitsios and their co-editors from UPRC present a mechanism for effectively implementing a holistic approach for successfully achieving data interoperability between high-quality data that derive from heterogeneous devices. Through this mechanism, initially, the collection of the different devices’ datasets occurs, followed by the cleaning of them. In sequel, the produced cleaning results are used in order to capture the levels of the overall data quality of each dataset, in combination with the measurements of the availability of each device that produced each dataset, and the reliability of it. Consequently, only the high-quality data is kept and translated into a common format, being able to be used for further utilization. The proposed mechanism is evaluated through a specific scenario, producing reliable results, achieving data interoperability of 100% accuracy, and data quality of more than 90% accuracy.
In particular, the proposed mechanism gathers heterogeneous IoT medical devices’ data, automatically extracting the data that is of high-quality and making it interoperable. Based on this mechanism, initially all the available heterogeneous IoT medical devices are discovered and connected into the mechanism, which is responsible for collecting their data. Once these devices are connected and their data is successfully gathered, the cleaning of it takes place, from which the results of each device’s dataset cleaning derive. The latter are combined with the corresponding overall data quality measurements that are captured from each different device in combination with its derived data, so as to decide whether the connected devices’ derived data will be considered as reliable or not. Consequently, only the reliable data is kept and translated into an interoperable format, and thus are kept to be used for further analysis. The proposed mechanism is evaluated through a specific use case, by gathering data from heterogeneous IoT medical devices, in order to clean it and capture its quality levels, and finally make interoperable only the cleaned data that are of high-quality.