A multi-level simulation-based optimization framework for IoT-enabled elderly care systems

A multi-level framework that combines a simulation and optimization approach is proposed to evaluate the performance of complex systems triggered by real-time IoT-fed "service requests". The idea behind the conceptual framework is centered on the use of simulation to mimic system organization, rules and behavior, whereas optimization is used to search for the allocation of both personnel and equipment to pursue optimality with respect to resource availability. Focusing on a healthcare assistance network for the elder, the framework is tailored to determine the staff requirements for home assistance of local elderly populations based on different priorities of service requests and geographical areas covered by the service. The framework is verified by using NEMSIS (National Emergency Medical Services Information System) data, i.e. the national database that is used to store emergency medical services data from the U.S. States and Territories. Ad hoc scenarios are analyzed and evaluated in an illustrative use case. Numerical results show how, upon the arrival flow of non-deterministic patient calls, the framework allows to verify the goodness of strategic, tactical and operational decisions of healthy living for the elder.