Smart healthcare model with fog-cloud network architecture

In this paper, the performance of an internet of things (IoT) based, real-time, smart ECG signal compression and transmission protocol is investigated through both simulation and hardware implementation. The protocol, consisting of a combination of fog and cloud computing architecture, has a four layered structure with first layer comprising of wearable ECG sensor and noise filter embedded in the device. Second layer is an encoder which consists of an algorithm subdivided into two schemes namely, geometry-based method (GBM) and wavelet-based iterative thresholding (WTIT). The algorithm is based on the fact that ECG signals can be approximated by the linear combination of a few coefficients obtained from a wavelet basis. The third layer consists of wireless transmission medium from the wearable to a private cloud, accessed by the hospital servers. The data is obtained in the receiver, the final layer, where signal reconstruction is performed using inverse transforms.