Distributed, Signal Strength-Based Indoor Localization Algorithm for Use in Healthcare Environments

In current healthcare environments, a trend towards mobile and personalized interactions between people and nurse call systems is strongly noticeable. Therefore it should be possible to locate patients at all times and in all places throughout the care facility. The present article aims at describing a method by which a mobile node can locate itself indoors, based on signal strength measurements and a minimal amount of yes/no decisions. The algorithm has been developed specifically for use in a health care environment. With extensive testing and statistical support, we prove our algorithm can be used in a healthcare setting with an envisioned level of localization accuracy up to room revel (or region level in a corridor), while avoiding heavy investments since the hardware of an existing nurse call network can be reused. The approach opted for leads to very high scalability, since thousands of mobile nodes can locate themselves. Network timing issues and localization update delays are avoided, which ensures a patient can receive the needed care in a time and resources efficient w ay. existing systems. The proposed algorithm describes a method in which a mobile node can locate itself based on signal strengths between RF beacons. The envisioned localization accuracy is finetuned up to room level (or region level if the mobile node is inside a corridor). Since all mobile nodes are able to locate themselves, scalability issues are avoid ed. The research is supported by a statistical analysis (Suppor t Vector Machines), and is presented as follows. Section II gives an outline of existing systems for indoor localizatio n in general. In Section III, an overview of the developed indoor localization technique is given, followed by Section IV in which the performance of the proposed localization technique under laboratory conditions is given and analysed. Section V elaborates on the theoretical support for the developed ind oor localization algorithm, after which a general conclusion a bout the performed work is presented in Section VI.