A fusion component for location management in mobile

When indoors, several positioning technologies and systems may coexist (e.g. WiFi, Bluetooth, ZigBee, HF-RFID or bidi codes serving as beacons, cellular networks, etc.); each of them delivering its location estimates with a given accuracy at a given computational cost. In this paper, we describe a Mobile Fusion Component (MFC) -prepared to run in a mobile device- which aims at optimizing the selection of the available positioning systems by handling Quality-of-Location (QoL). The objective of the MFC is to offer the (best) location <JK@D8K@FE N?@:? =LC=@CCJ K?< :FEJLD<I 8GGC@:8K@FEJj +F& E<<;J 8K K?< J8D< K@D< K?8K minimizes resource consumption in the mobile device. Additionally, the MFC will provide seamless hand-off among location technologies and allow the user to establish his own privacy level for location data sharing. The MFC is part of a service-oriented mobile =I8D<NFIB N?@:? F==<IJ iContext Acquisition Services anD Reasoning Algorithmsj (CASanDRA Mobile) to accelerate the development of context-aware applications

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

Wifi bluetooth based combined positioning algorithm

Nowadays positioning have become very important for many services (Localization based services) and positioning have become more accurate, despite, there are some territories that basic positioning systems like GPS or even hybrid ones like GPS-WiFi or GPS-WiFi-gsm can’t cover, specially indoor enviroments. In this paper we propose a positioning method merging WLAN and Bluetooth technologies based on trilateration technique. Simulated sceneario demostrate accuracy gains, even when we use a high signal attenuation parameter. A simulated sceneario taken from a real home with the real WLAN and Bluetooth stations validates our WLAN-Bluetooth method. Firstly we calculate each equation from each available station, then we decide how to overdetermine the generated equation system in a reason of 4 to 1 (4 equations for one unknown) and finally solve the system using mathematical methods. This work is a step more to better position in indoor enviroments and localization based service

Using contex-awarenes to foster active lifestyles

This paper describes a context-aware mobile application which aims at adaptively motivating its users to assume active lifestyles. The application is built on a model which combines ‘motion patterns’ with ‘activity profiles’, in order to evaluate the user’s real level of activity and decide which actions to take to give advice or provide feedback. In particular, a ‘move-to-uncover’ wallpaper puzzle interface is employed as motivating interface; at the same time, context-aware notifications are triggered when low activity levels are detected. In order to accelerate the application’s design and development cycle, a mobile service oriented framework – CASanDRA Mobile - has been used and improved. CASanDRA Mobile provides standard features to facilitate context acquisition, fusion and reasoning in mobile devices, making easier access to sensors and context-aware applications cohabitatio

Using bluetooth to implement a pervasive indoor positioning system with minimal requirements at the application level

Proyecto CCG10-UC3M/TIC-4992 de la Comunidad Autónoma de Madrid y la Universidad Carlos III de MadridPublicad

Bluetooth-WiFi based combined positioning algorithm, implementation and experimental evaluation

Positioning an individual with high accuracy is important since many location-based services rely on the position of the user to provide them with ubiquitous services. Despite the need for accuracy, no perfect solution has been proposed for the problem of accurately positioning an individual. A number of attempts to improve the accuracy has been made achieving an accuracy of about 2 meters using sophisticated techniques and the advances made in the mobile industry. In this paper we explain the methodology to get a propagation model suitable for Bluetooth in order to get a more accurate distance measurement, and also the algorithm to combine it with WiFi to position a user in an indoor environment. Firstly, we get measurements of distance related to a RSSI value obtained from the Bluetooth to get a propagation model, we compute a distance using the known propagation model from WiFi, and finally an algorithm to obtain the location of the receiver combinig Bluetooth and WiFi is presente

Design and Development of Google Glass-Based Campus Navigation System

This paper investigates the feasibility of a Google Glass-based campus navigation system for both indoor and outdoor areas. The Indoor Positioning System (IPS) of the proposed system utilizes the magnetic positioning technology of IndoorAtlas Maps™ API which depends on structure's magnetic field fluctuations or geomagnetic fingerprints. The outdoor navigation mechanism simply consists of a map displayed within the Google Glass app with an augmented routing path leading to the set destination, while the indoor navigation interface displays a blue dot indicator of the current position on top of the augmented map with minimum spanning tree route. Furthermore, a data logging feature is incorporated for logging the movements of the user through the use of QR coded checkpoints for outdoor location monitoring and indoorto-outdoor navigation transitions. The proposed system was tested in De La Salle University (DLSU) - Manila Campus, where 30 participants (15 DLSU and 15 Non-DLSU) were invited to utilize the proposed system navigating from an entry point to a set destination. The proposed Google Glass-based navigation system was found to have an average error of 1.77 meters (indoor) and around 77% of the users who utilized the application responded with a positive feedback. However, Google glass’ limited battery life and high cost are among the barriers to adaptation. These results could provide empirical evidence supporting the feasibility of Google glass-based navigation deployment in other public areas, e.g. malls, government buildings, hospitals, etc

Contribución al desarrollo de sistemas automáticos de planificación eficiente de rutas

[SPA] El objetivo de esta tesis doctoral es el desarrollo de un sistema de detección de dispositivos móviles y su aplicación en los sistemas de planificación eficiente de rutas. Para ello, se lleva a cabo la implementación piloto de un prototipo de sistema global automático para la estimación de información origen-destino (OD) en los medios públicos de transporte. Esta herramienta TIC de medición está basada en los resultados del análisis de la demanda y el flujo de pasajeros en las líneas urbanas de transporte, sus tasas de ocupación y las matrices origen-destino. Esto se logra mediante la detección de dispositivos electrónicos personales a bordo (etiquetas Bluetooth o WiFi), el procesamiento de esa información y su transmisión. Las muestras detectadas, tras ser tratadas por un procesador estadístico de decisión para determinar cuáles de ellas son representativas y cuáles no, permiten la creación de patrones de comportamiento atendiendo a las matrices de probabilidades OD resultantes. La capacidad de este prototipo para la obtención de grandes volúmenes de muestras, ha permitido garantizar la viabilidad de predicción del sistema con porcentajes de error despreciables. Este trabajo de tesis permite la mejora del servicio prestado por las empresas de transporte público de pasajeros a sus clientes directos, el consorcio de transportes de las ciudades en las que operan, así como los usuarios finales, los pasajeros, lo que facilita una movilidad más inteligente y sostenible. [ENG] The aim of this thesis is to develop a detection system of mobile devices and their application in efficient route planning. To this end, a pilot is carried out with an automated system prototype for estimating overall information origindestination (OD) in public transport services. This ICT measurement tool is based on the results of the analysis of demand and passenger flow in urban transport lines, occupancy rates and origin-destination matrices. This is accomplished by detecting personal electronic devices on board (Bluetooth or WiFi labels), processing and transmitting such information. The samples detected, after being treated by a statistical decision processor to determine which of these are representative and which are not, allow the creation of patterns of behavior in response to the OD resulting probability matrices. The capacity of this prototype for the production of large volumes of samples, has ensured the system viability for prediction with negligible percentages error. This thesis can improve the service provided by public transport companies of passengers to their direct customers, the transport consortium of cities in which they operate, as well as end users, the passengers, facilitating a smarter mobility and sustainable.Escuela Internacional de DoctoradoUniversidad Politécnica de CartagenaDoctor en Programa Oficial de Posgrado en Tecnologías de la Información y Comunicacione

Signal modelling based scalable hybrid Wi-Fi indoor positioning system

Location based services (LBS) such as advertising, navigation and social media require a mobile device to be aware of its location anywhere. Global Positioning System (GPS) is accurate outdoors. However, in case of indoor environments, GPS fails to provide a location due to non-line of sight. Even in cases where GPS does manage to get a position fix indoors, it is largely inaccurate due to interference of indoor environment. Wi-Fi based indoor positioning offers best solution indoors, due to wide usage of Wi-Fi for internet access. Wi-Fi based indoor positioning systems are widely based on two techniques, first Lateration which uses distances estimated based on signal properties such as RSS (Received Signal Strength) and second, Fingerprint matching of data collected in offline phase. The accuracy of estimated position using Lateration techniques is lower compared to fingerprinting techniques. However, Fingerprinting techniques require storing a large amount of data and are also computationally intensive. Another drawback of systems based on fingerprinting techniques is that they are not scalable. As the system is scaled up, the database required to be maintained for fingerprinting techniques increases significantly. Lateration techniques also have challenges with coordinate system used in a scaled-up system. This thesis proposes a new scalable positioning system which combines the two techniques and reduces the amount of data to be stored, but also provides accuracy close to fingerprinting techniques. Data collected during the offline/calibration phase is processed by dividing the test area into blocks and then stored for use during online/positioning phase. During positioning phase, processed data is used to identify the block first and then lateration techniques are used to refine the estimated location. The current system reduces the data to be stored by a factor of 20. And the 50th percentile accuracy with this novel system is 4.8m, while fingerprint system accuracy was 2.8m using same data. The significant reduction in database size and lower computational intensity benefits some of the applications like location-based search engines even with slightly lower performance in terms of accuracy