IoT based Patient monitoring is the current need of the hour. The critical care services have been a crucial part for patients, who suffer from serious health conditions and heart diseases. Increased population is one of the major reasons behind waiting for clinical health monitoring services in hospitals. The current internet era and IoT based health support systems provide medical services for individuals and hospitals to forecast or early-detect probable critical care situations. The proposed approach is a new health care support system for heart patients to monitor and report with hospitals. We have introduced a Fog assisted IoT based cardio monitoring application to help the decision support system, which also tested with the existing analogues health care applications to show its elevated performance.
We consider a continuous review (s, S) inventory system in which the arriving customers belong to any one of the two types (type-1 or type-2). When the inventory level is above s, the customers are not distinguished as to their type and their demanded items are delivered immediately to them. Once the inventory level drops to s(≥ 0), an order for Q items is placed and thereafter the demands of type-2 customers alone are satisfied. The type-1 customers are sent to a place called orbit which is of infinite size. These orbiting demands retry for their demand after a random time which is assumed to have exponential distribution. The arrivals of customers are assumed to follow a Markovian arrival process and the lead time is assumed to have phase-type distribution. The joint probability distribution of the number of customers in the orbit and the inventory level is obtained in the steady-state case. Various system performance measures in the steady state are derived and total expected cost rate is calculated.
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