Coma is a prolonged state of unconsciousness for an extended period of time. Patients in coma are unable to move and communicate and therefore require continuous monitoring for their well-being and safety. Traditional monitoring techniques are labour-intensive, time-consuming, and require round-the-clock human observation. There is need for more automated and efficient approach for surveillance of coma patients. In this research manuscript, we propose a fog-based intelligent healthcare framework for monitoring the body movements of coma patient using smart cameras. The proposed system’s effectiveness is evaluated using ifogsim toolkit. The results obtained demonstrate that fog computing exhibits a more efficient reduction in latency, network usage, and energy consumption compared to cloud computing, thereby establishing fog computing as a superior QoS framework.

Capital Budgeting, Investment, Case Study Method