Improving Remote Patient Monitoring Systems Using a Fog-Based IoT Platform With Speech Recognition
Marc Jayson Baucas, Petros Spachos
Abstract
Due to the recent shortage of resources in the healthcare industry, remote patient monitoring (RPM) systems arose to establish a convenient alternative for accessing healthcare services remotely. However, as the usage of this system grows with the increase of patients and sensing devices, data and network management becomes an issue. As a result, wireless architecture challenges in patient privacy, data flow, and service interactability surface that need addressing. We propose a fog-based Internet of Things (IoT) platform to address these issues and reinforce the existing RPM system. The introduced platform can allocate resources to alleviate server overloading and provide an interactive means of monitoring patients through speech recognition. We designed a testbed to simulate and test the platform in terms of accuracy, latency, and throughput. The results show the platform’s potential as a viable RPM system for sound-based healthcare services.