Scalable optimal planning of sensor networks for hospital assets tracking

Abstract

An optimization framework is proposed to plan a sensor network in hospital environments aimed at tracking medical assets. The framework is based on three modules: the first module defines the critical levels of the hospital locations based on the assets movements and criticality; the second module models the coverage characteristics of the sensors; the third module, based on the outputs of the previous ones, determines the optimal sensor placements. The modular optimization framework can be used for heterogeneous network technologies. The paper is based on the work in [1], which is substantially improved in terms of scalability to render the framework suitable for real applications. Simulation results are presented, considering a case-study based on the plan of the cardiology department of the "San Camillo" hospital in Rome and on interviews with the personnel.