Modern trends in distributed medical diagnostics automationbased on the Internet-of-Things

The paper deals with the problem of development of a distributed automated system for medical diagnostics based on the modern concept of the Internet of Things. In the process of analysis and classification of diagnostic hardware and software there was derived a new class of medical devices related to mobile integrated active medical diagnostic systems with open interfaces. The distinctive feature of this system is the ability to achieve a combination of energy efficiency, reliability and timeliness of solutions for medical diagnostics tasks. To implement the Internet of Things concept for medical distributed diagnostics we propose to build a self-mediator sensor network concept, which makes it possible to increase the autonomy of each sensor through the implementation of specialized software functionality. This functionality includes pre-processing of information on the transmitter side and implementation of P2P interaction between the sensors in the process of data transfer. In the process of such interaction, the diagnostic devices implement not only their direct purpose, but also participate in data transfer between third party devices. In general, the proposed mediator pattern contains three cooperating subsystems: the network node, the agent and the dispatcher. One of the main differences of this architecture is implementation of pre-processing by computing capabilities of smart sensors. Data interaction interface between the sensors that is required for the implementation of complex information processing within the measurement subsystem. The proposed architecture allows implementing data collection and processing functionality, which provides initial diagnostics on the system level in real time. The approach provides a reduction in the total energy consumption of autonomous devices to perform diagnosis, reduces the delivery time of network messages and the number of detected exceptions, thereby increasing the overall efficiency of a distributed medical diagnostics.