Efficient information distribution in the Internet of Medical Things (IoMT)

Abstract

Towards the world of Internet of Things, people utilize knowledge from sensor streams in various kinds of smart applications including, but not limited to smart medical information systems. The number of sensed devices is rapidly increasing along with the amount of sensing data. Consequently, the bottleneck problem at the local gateway has become a huge concern given the critical loss and delay intolerant nature of medical data. Orthogonally to the existing solutions, we propose sensor data prioritization mechanism to enhance the information quality while utilizing resources using Value of Information (VoI) at the application level. Our approach adopts signal processing techniques and information theory related concepts to assess the VoI. We introduce basic yet convenient ways to enhance the efficiency of medical information systems, not only when considering the resource consumption, but also when performing updates, by selecting appropriate delay for wearable sensors to send data at optimal VoI. Our analysis shows some interesting results about the correlation and dependency of different sensor signals, that we use for the value assesment. This preliminary analysis could be an initiative for further investigation of VoI in medical data transmission using more advanced methods.Towards the world of Internet of Things, people utilize knowledge from sensor streams in various kinds of smart applications including, but not limited to smart medical information systems. The number of sensed devices is rapidly increasing along with the amount of sensing data. Consequently, the bottleneck problem at the local gateway has become a huge concern given the critical loss and delay intolerant nature of medical data. Orthogonally to the existing solutions, we propose sensor data prioritization mechanism to enhance the information quality while utilizing resources using Value of Information (VoI) at the application level. Our approach adopts signal processing techniques and information theory related concepts to assess the VoI. We introduce basic yet convenient ways to enhance the efficiency of medical information systems, not only when considering the resource consumption, but also when performing updates, by selecting appropriate delay for wearable sensors to send data at optimal VoI. Our analysis shows some interesting results about the correlation and dependency of different sensor signals, that we use for the value assesment. This preliminary analysis could be an initiative for further investigation of VoI in medical data transmission using more advanced methods