A sensor-based architecture for telemedical and environmental air pollution monitoring system using 5G and blockchain

Abstract

Within the recent advancements in technology, there is a tremendous growth in digital healthcare technologies for refining and transmuting healthcare which takes the account of plummeting human miscalculations, enlightening clinical consequences, facilitating care coordination, and humanizing practice efficiencies, with the help of integrated approaches. To create a more effective and safer health care environment in the places where there is no medical health care facility, Internet of Medical Things (IoMT) can provide a Tele medical room with a 5G infrastructure. The Tele medical room contains a smart chair facility, wherein the data of patient denotes heart rate of the patient, electrocardiography, blood pressure of the patient, and body temperature of the patients that can be monitored remotely and the assistance can be provided by the doctors through remote conferencing. The 5G-enabled communication environment is created to withstand higher data transmission in the remote correspondence interface.During the recent decade, we have seen an incredible improvement concerning miniaturized electronic devices, in order to facilitate their integration in handheld equipment. This invention demonstrates the estimation of blood glucose level by designing a substrate-based flexible antenna. The change in the concentration of raw material provides moderate dielectric constant that is attained in the flexible antenna. Synthesized nickel particle-based flexible nickel aluminate (NiAl2O4) is utilized as a substrate material for microwave applications. The substrate was made with 42% of nickel, with a dielectric constant of 4.979 and a thickness of 1 mm. Design and performance analyses were investigated based on the reflection coefficient in normal and bent conditions. Dielectric properties of human blood over a broad frequency range were measured with and without adding the glucose content for different types of blood groups. These results were manipulated as a data set required for machine learning approaches.The optimized Ensemble algorithm which provides feature reduction, hyper parameter optimization, along with asymmetrical cost assignment can be used to segregate the normal and abnormal heart beat signal. The receiver unit comprises a headphone jack which can be inbuilt with a Wi-Fi modem in order to clearly hear the pulmonary, cardiac, or digestive noises being monitored. The Internet of Things (IoT) sensor information is created from different heterogeneous gadgets, correspondence conventions, and information organizes that are gigantic in nature. This gigantic measure of information is not incorporated and examined physically. This is a huge issue for IoT application designers to make the mix of IoT sensor information. Semantic explanation of IoT information is the establishment of IoT semantics. Bunching is one way of settling the combination and investigation of IoT sensor information. Semantics and learning approaches are the keys to resolve the issue of sensor information combination and investigation in IoT.