Internet of Things (IoT) is gaining more attention from last few decades. Nowadays, people are moving towards the IoT based systems for living their life luxuriously. Adoption of IoT in the field of healthcare sector is noticeable. Real time monitoring of patient is possible in better way using this technique. Due to integration of IoT, the quality of services in healthcare field is surpasses. Most of the time due to improper monitoring of patient's body parameters causes hazardous effects on patient's health. In this paper, we discuss the IoT based remote monitoring of patient. The aim here is to get proper and timely treatment to the patient, when any of the health parameters crosses its set limits. The abnormal condition of patient is informed to his physician, care taker and family members by sending message about abnormal health parameter. So that patient can be treated well in time.

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The aim of this work is to study the influence of pressure loss parameters from a district heating system on the distribution of fluid flow rates. The research was finalized by improving the mathematical model of a district heating network, which comprises an algebraic non-linear system that synthesizes flow balance equations of a stationary flow. This enhanced model indicates the influence of every consumer’s heat demand supplied from a district heating network on the fluid flow rates distribution based on the means of the implicit function theorem. The originality of the method consists of considering the network a sensitive system that responds to the variations of input parameters (pressure loss parameters) by variations of output parameter (fluid flow rates). The main advantage is that the engineer in charge with exploitation of the heating system may understand what happens with the flow allocations when pressure loss parameters of the network are different from the nominal ones, without making any measurements on the field or computations using new scenarios. The method presented in this paper facilitates the choice of the best decision concerning balancing and practical management of radial heating networks.