iPhone Independent Real Time Localization System Research and Its Healthcare Application

Abstract

This project studied several popular localization algorithms on iPhone and, according to the demands, specifically designed it to improve healthcare IT system in hospitals. The challenge of this project was to realize the different localization systems on iPhone and to make balance between its response time and localization accuracy. We implemented three popular localization algorithms, namely nearest neighbor (NN), K-nearest neighbor (KNN), and probability phase, and we compared their performance on iPhone. Furthermore, we also implemented a real-time localization system using the ZigBee technology on iPhone. Thus, the whole system could realize not only self-localization but also others-localization. To fulfill the healthcare needs, we developed an application, which can be used to improve the hospital IT, system. The whole project included three phases. The first phase was to localize iPhone's position using the received WiFi signal by iPhone, compare and optimize their performances. During the second phase, we implemented a ZigBee RFID localization system and combined it with the WiFi system. Finally, we combined new features of the system with a healthcare IT system. We believe that this application on iPhone can be a useful and advanced application in hospitals.

Fuzzy decision trees embedded with evolutionary fuzzy clustering for locating users using wireless signal strength in an indoor environment

“…Research on recognizing the people's complex behaviour based on their movements at indoor was proposed by Salazar et al 47 To support home rehabilitation, Nguyen et al 48 proposed approaches to recognize the traumatic brain injured patient movements at indoor. Iphone users provided with health services is another interesting IOT application developed by Lu et al 49 which locates users and provides health services accordingly. In this study, machine learning approaches like K‐nearest neighbour (KNN), neural networks (NN), and probability phase were used for locating users with their smart device.…”