Context aware healthcare system For modern life through fogging And deep learning

Abstract

Remote Patient Monitoring (RPM) is accounted as the digital health service and is developed to provide care assistance to people. With the help of RPM, people can manage their own health comfortably. Further the medical professionals are able to track the state of the patient in a regular basis. The pandemic situation realized in recent year also raised the well effective design of RPM in place. There exists a lot of cost effective RPM, the advancements in sensor and communication technology reduces the cost of implementation. Apart from affordability, the other interesting factors that improve the efficiency of RPM are context awareness, proactiveness, security and speedy service. newlineThe first module produces the simple design of smart pulse oximeter with influencing environmental factors into account and it provides the error rate in the range of 4 BPM and ensures the overall accuracy as 95% as compared with the commercial product. Further this module enriches the knowledge on designing a physiological monitor through incorporating the dependency realized among the vital signs. newlineThe second module describes the algorithm to perform context aware computation in fog layer. With fog server, the current state of the patient is assessed and real time responses are triggered. Context aware based access control mechanism is designed to protect patient data. The efficiency of fog computing and effective routing protocol is simulated using the network simulator NS-2 with throughput, delay and packet delivery ratio (PDR) as evaluation parameters. The integration of fog in RPM design increases the transmission speed as 24.7% and computation service of the application as faster as 3.46% on average against traditional cloud setting newline