FDRF: Fault Detection and Recovery Framework for Seamless Data Transmission in Remote Health Monitoring Using WBAN

Health monitoring systems based on Sensors, IoT and Cloud server have gained popularity in recent time. In this work patient either wear small sensors or they are placed inside their body through the surgical means. They will sense health vitals and transmit them to central server for processing and storage. Doctors can remotely access the data at his convenience. Such sensor based monitoring system should be reliable and fault-free since it involves health data. However, it may be affected by several factors at different places and levels, like hardware failure, software problems, as well as errors during transmission. Health monitoring system should be fault preventive so that it can function properly and ensure seamless data transmission even in the presence of some faulty sensor nodes. In the present context we have designed a Fault Detection and Recovery Framework for sensor based remote health monitoring system which can detect faulty sensor nodes and can accordingly select alternative set of nodes to continue with the data transmission. Faulty nodes are restrained from taking part in data sensing and transmission till they behave properly or are replaced by other nodes. We have used Libelium MySignals HW (eHealth Medical Development Shield used in Arduino) v2 sensors, patient vitals are collected through three different sensors such as ECG, SpO2 and temperature sensor. Additionally arduino board Model UNO R3 is used as microcontroller device. Acquired sensor data are analyzed using proposed algorithm and simulated using MATLAB to detect node level faults and our proposed framework ensures reliable, seamless, accurate and timely data transmission.