HRIDaaY: Ballistocardiogram-Based Heart Rate Monitoring Using Fog Computing

Ambient Assisted Living (AAL) is becoming a necessity in today's world. It provides care to the elderly patients who are under observation. With the advancements in the technology, the ability of health systems to indulge in the patient's life and remote monitoring has proven useful to prevent catastrophes. Automatic sensing based on sensors and computer vision enabled devices has taken up the field of AAL a notch ahead. Motivated from the aforementioned discussion, in this paper, we propose, a fretwork named as HRIDaaY (an architecture for remote monitoring of the heart rate of a patient) by using a ballistocardiogram sensor and fog computing (FC). We further demonstrate a data compression technique at the fog layer to reduce the bandwidth utilization. Then, a comparison is drawn using alone-Cloud and as fog- cloud combination implementation. Finally, the simulation results demonstrate that HRIDaaY has better accuracy of heart rate monitoring in comparison to the state-of-art schemes.