Intelligent Optimized Controlled Health Care System Using Brute Force and Heuristic Algorithms

Recently, the health care system has gained increased attention due to the required increase in population in societies and the need for fast action urgent cases of health. New development of technologies, internet, and IoT make further progress in the establishment of a health care system to the extent that it considered as a measure of the progress in a country. The quality of the healthcare system depends on the comfort of patients during the treatment time and monitoring. In order to achieve these goals, scientists created a remote real-time monitoring system. In this research, the data taken from simulated healthcare sensors are used in an explicit functional model called Quality of inference (QoINF), which will be optimized within either by the intelligent Brute force or heuristic algorithms. The required task is to find the best set of sensors with high accuracy and the lowest cost. Moreover, based on the value of context, the deduced best set of sensors would be examined by Fuzzy Logic Controller (FLC) to make a proper decision for the nurse or doctor that supervise the patients or elderly people.