Performance Evaluation of Mobile U-Navigation based on GPS/WLAN Hybridization

This paper present our mobile u-navigation system. This approach utilizes hybridization of wireless local area network and Global Positioning System internal sensor which to receive signal strength from access point and the same time retrieve Global Navigation System Satellite signal. This positioning information will be switched based on type of environment in order to ensure the ubiquity of positioning system. Finally we present our results to illustrate the performance of the localization system for an indoor/ outdoor environment set-up.Comment: Journal of Convergence Information Technology(JCIT

Mobile Indoor Augmented Reality. Exploring applications in hospitality environments.

Augmented reality (AR) is been increasingly used in mobile devices. Most of the available applications are set to work outdoors, mainly due to the availability of a reliable positioning system. Nevertheless, indoor (smart) spaces offer a lot of opportunities of creating new service concepts. In particular, in this paper we explore the applicability of mobile AR to hospitality environments (hotels and similar establishments). From the state-of-the-art of technologies and applications, a portfolio of services has been identified and a prototype using off-the-shelf technologies has been designed. Our objective is to identify the next technological challenges to overcome in order to have suitable underlying infrastructures and innovative services which enhance the traveller?s experience

Design and analysis of collision reduction algorithms for LED-based indoor positioning with simulation and experimental validation

In this paper, we develop a low complexity indoor positioning system (IPS) and design a lightweight, low-cost, and wearable receiver for it. The accuracy of proximity-based LED IPS has been improved using overlap between LED beams but LED packets in the overlap region are subject to collisions. In this paper, we design collision handling algorithms for the IPS that considers building and lighting infrastructures. Mathematical analyses of the proposed algorithms are done and models for the probability of collisions are developed. The models, which are verified using simulations, are used to calculate the time required for position update called positioning time. Analysis of the positioning time is done for single and multiple receivers systems and validated with experimental measurements. Results show positioning error as low as 56 cm with a positioning time of about 300 ms for slotted unsynchronized systems and 500 ms for unslotted unsynchronized systems which makes the developed system pragmatic and appropriate for human positioning

Data Analysis and Memory Methods for RSS Bluetooth Low Energy Indoor Positioning

The thesis aims at finding a feasible solution to Bluetooth low energy indoor positioning (BLE-IP) including comprehensive data analysis of the received signal strength indication (RSSI) values. The data analysis of RSSI values was done to understand different factors influencing the RSSI values so as to gain better understanding of data generating process and to improve the data model. The positioning task is accomplished using a methodology called \textit{fingerprinting}. The fingerprinting based positioning involves two phases namely \textit{calibration phase} and \textit{localization phase}. The localization phase utilises the memory methods for positioning. In this thesis, we have used \textit{Gaussian process} for generation of radio maps and for localization we focus on memory methods: \textit{particle filters} and \textit{unscented Kalman filters}. The Gaussian process radio map is used as the measurement model in the Bayesian filtering context. The optimal fingerprinting phase parameters were determined and the filtering methods were evaluated in terms root mean square error

Evaluation of an indoor localization system for a mobile robot

Although indoor localization has been a wide researched topic, obtained results may not fit the requirements that some domains need. Most approaches are not able to precisely localize a fast moving object even with a complex installation, which makes their implementation in the automated driving domain complicated. In this publication, common technologies were analyzed and a commercial product, called Marvelmind Indoor GPS, was chosen for our use case in which both ultrasound and radio frequency communications are used. The evaluation is given in a first moment on small indoor scenarios with static and moving objects. Further tests were done on wider areas, where the system is integrated within our Robotics Operating System (ROS)-based self-developed 'Smart PhysIcal Demonstration and evaluation Robot (SPIDER)' and the results of these outdoor tests are compared with the obtained localization by the installed GPS on the robot. Finally, the next steps to improve the results in further developments are discussed