Streaming Pressure Sensor Data for Cloud Processing

Abstract

The smart home that contains ambient and worn sensors to allow the assessment of older adult well-being has been the focus of many research projects and has the promise to enable increased independence for older adults and delay their need for institution-based care. Many of these projects have focused on the sensor technologies and have been performed in small scale pilots or tests with local data capture and storage. For wide scale deployment to large populations, a solution is required to allow these systems to be deployed that is low cost while also providing effective streaming of the data into the cloud for processing. In this paper, the performance of a Raspberry PI embedded computer being used with pressure sensitive mats and direct streaming to the IBM Cloud IoT service is presented. The paper shows this single sensor application consumes up to 30% of a single CPU core capacity of the platform for the task of flowing the data. The data also shows the variance in the capacity demands frequently drives core utilization to between 60 and 100%. The result is that a single core must be dedicated to the real-time data flow task as the data flow application (Node-Red) must run within a single core. The result indicates that the low cost Raspberry PI platform can meet the performance needs and the CPU capacity of other cores could allow additional processing of the data prior to transmission.