Requirements for enhancing trust, security and integrity of GNSS location services

The paper describes a number of requirements for enhancing the trust of location acquisition from Satellite Navigation Systems, particularly for those applications where the location is monitored through a remote GNSS receiver. We discuss how the trust of a location acquisition could be propagated to an application through the use of a proposed tamper-­resistant GNSS receiver which quantifies the trust of a location solution from the signaling used (ie. P(Y) code, Galileo SOL, PRS, CS) and provides a cryptographic proof of this to a remote application. The tamper­-resistance state of the receiver is also included in this cryptographic proof.

Enhancing the trust of location acquisition systems for critical applications and location-based security services

This paper identifies a number of critical infrastructure applications that are reliant on location services from cooperative location technologies such as GPS and GSM. We show that these location technologies can be represented in a general location model, such that the model components can be used for vulnerability analysis. We perform a vulnerability analysis on these components of GSM and GPS location systems as well as a number of augmentations to these systems.

Mixed spatial and nonspatial problems in location based services

With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.

Mixed Spatial and Nonspatial Problems in Location Based Services

With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.

Locant: A nature inspired location service for ad hoc networks

An efficient location service is a prerequisite to any robust, effective and precise location information aided Mobile Ad Hoc Network (MANET) routing protocol. Locant, presented in this paper is a nature inspired location service which derives inspiration from the insect colony framework, and it is designed to work with a host of location information aided MANET routing protocols. Using an extensive set of simulation experiments, we have compared the performance of Locant with RLS, SLS and DLS, and found that it has comparable or better performance compared to the above three location services on most metrics and has the least overhead in terms of number of bytes transmitted per location query answered.

A Modified inverse integer Cholesky decorrelation method and the performance on ambiguity resolution

One of the research focuses in the integer least squares problem is the decorrelation technique to reduce the number of integer parameter search candidates and improve the efficiency of the integer parameter search method. It remains as a challenging issue for determining carrier phase ambiguities and plays a critical role in the future of GNSS high precise positioning area. Currently, there are three main decorrelation techniques being employed: the integer Gaussian decorrelation, the Lenstra–Lenstra–Lovász (LLL) algorithm and the inverse integer Cholesky decorrelation (IICD) method. Although the performance of these three state-of-the-art methods have been proved and demonstrated, there is still a potential for further improvements. To measure the performance of decorrelation techniques, the condition number is usually used as the criterion. Additionally, the number of grid points in the search space can be directly utilized as a performance measure as it denotes the size of search space. However, a smaller initial volume of the search ellipsoid does not always represent a smaller number of candidates. This research has proposed a modified inverse integer Cholesky decorrelation (MIICD) method which improves the decorrelation performance over the other three techniques. The decorrelation performance of these methods was evaluated based on the condition number of the decorrelation matrix, the number of search candidates and the initial volume of search space. Additionally, the success rate of decorrelated ambiguities was calculated for all different methods to investigate the performance of ambiguity validation. The performance of different decorrelation methods was tested and compared using both simulation and real data. The simulation experiment scenarios employ the isotropic probabilistic model using a predetermined eigenvalue and without any geometry or weighting system constraints. MIICD method outperformed other three methods with conditioning improvements over LAMBDA method by 78.33% and 81.67% without and with eigenvalue constraint respectively. The real data experiment scenarios involve both the single constellation system case and dual constellations system case. Experimental results demonstrate that by comparing with LAMBDA, MIICD method can significantly improve the efficiency of reducing the condition number by 78.65% and 97.78% in the case of single constellation and dual constellations respectively. It also shows improvements in the number of search candidate points by 98.92% and 100% in single constellation case and dual constellations case.

Cooperative positioning for heterogeneous wireless systems

Future emerging market trends head towards positioning based services placing a new perspective on the way we obtain and exploit positioning information. On one hand, innovations in information technology and wireless communication systems enabled the development of numerous location based applications such as vehicle navigation and tracking, sensor networks applications, home automation, asset management, security and context aware location services. On the other hand, wireless networks themselves may bene t from localization information to improve the performances of di erent network layers. Location based routing, synchronization, interference cancellation are prime examples of applications where location information can be useful. Typical positioning solutions rely on measurements and exploitation of distance dependent signal metrics, such as the received signal strength, time of arrival or angle of arrival. They are cheaper and easier to implement than the dedicated positioning systems based on ngerprinting, but at the cost of accuracy. Therefore intelligent localization algorithms and signal processing techniques have to be applied to mitigate the lack of accuracy in distance estimates. Cooperation between nodes is used in cases where conventional positioning techniques do not perform well due to lack of existing infrastructure, or obstructed indoor environment. The objective is to concentrate on hybrid architecture where some nodes have points of attachment to an infrastructure, and simultaneously are interconnected via short-range ad hoc links. The availability of more capable handsets enables more innovative scenarios that take advantage of multiple radio access networks as well as peer-to-peer links for positioning. Link selection is used to optimize the tradeo between the power consumption of participating nodes and the quality of target localization. The Geometric Dilution of Precision and the Cramer-Rao Lower Bound can be used as criteria for choosing the appropriate set of anchor nodes and corresponding measurements before attempting location estimation itself. This work analyzes the existing solutions for node selection in order to improve localization performance, and proposes a novel method based on utility functions. The proposed method is then extended to mobile and heterogeneous environments. Simulations have been carried out, as well as evaluation with real measurement data. In addition, some speci c cases have been considered, such as localization in ill-conditioned scenarios and the use of negative information. The proposed approaches have shown to enhance estimation accuracy, whilst signi cantly reducing complexity, power consumption and signalling overhead.

A business model for an entertainment solution to the in-vehicle infotainment industry

The evolution of mobile technologies that make its presence something ubiquitous and the idea of internet connectivity in every device, often called as the Internet of Things, are pushing a disruption in other industry: the in-vehicle infotainment (IVI). Many companies are trying to enter this new industry that comprises information (weather, news, location services) and entertainment solutions in just one. For that purpose, company X developed a new entertainment solution and intends to bring it to market. This Work Project focuses on creating a business model and an entry mode for the company.

Indoor positioning using Android Platform

In recent years, there has been a great increase in the development of wireless technologies and location services. For this reason, numerous projects in the location field, have arisen. In addition, with the appearance of the open Android operating system, wireless technologies are being developed faster than ever. This Project approaches the design and development of a system that combines the technologies of wireless, location and Android with the implementation of an indoor positioning system. As a result, an Android application has been obtained, which detects the position of a phone in a simple and useful way. The application is based on the WIFI manager API of Android. It combines the data stored in a SQL database with the wifi data received at any given time. Afterwards the position of the user is determined with the algorithm that has been implemented. This application is able to obtain the position of any person who is inside a building with Wi-Fi coverage, and display it on the screen of any device with the Android operating system. Besides the estimation of the position, this system displays a map that helps you see in which quadrant of the room are positioned in real time. This system has been designed with a simple interface to allow people without technology knowledge. Finally, several tests and simulations of the system have been carried out to see its operation and accuracy. The performance of the system has been verified in two different places and changes have been made in the Java code to improve its precision and effectiveness. As a result of the several tests, it has been noticed that the placement of the access point (AP) and the configuration of the Wireless network is an important point that should be taken into account to avoid interferences and errors as much as possible, in the estimation of the position. RESUMEN. En los últimos años, se ha producido un incremento en el desarrollo de tecnologías inalámbricas y en servicios de localización y posicionamiento. Por esta razón, han surgido numerosos proyectos relacionados con estas tecnologías. Por otra parte, un punto importante en el desarrollo de estas tecnologías ha sido la aparición del lenguaje Android que ha hecho que estas nuevas tecnologías se implementaran con una mayor rapidez. Este proyecto, se acerca al diseño y desarrollo de un sistema que combina tecnologías inalámbricas, de ubicación y uso de lenguaje Android para el desarrollo de una aplicación de un sistema de posicionamiento en interiores. Como consecuencia de esto se ha obtenido una aplicación Android que detecta la posición de un dispositivo móvil de una manera sencilla e intuititva. La aplicación se basa en la API WIFI de Android, que combina los datos almacenados en una base de datos SQL con los datos recibidos vía Wi-Fi en cualquier momento. A continuación, la posición del usuario se determina con el algoritmo que se ha implementado a lo largo de todo el proyecto utilizando código Android. Esta aplicación es capaz de obtener la posición de cualquier persona que se encuentra dentro de un edificio con cobertura Wi-Fi, mostrando por pantalla la ubicación del usuario en cualquier dispositivo que disponga de sistema operativo Android. Además de la estimación de la posición, este sistema muestra un mapa que le ayuda a ver en qué cuadrante de la sala está situado el usuario. Este sistema ha sido diseñado con una interfaz sencilla para permitir que usuarios sin conocimiento tecnológico o no acostumbrados al uso de los nuevos dispositivos de hoy en día puedan usarlo de una manera sencilla y de forma intuitiva. Por último, se han llevado a cabo varias pruebas y simulaciones del sistema para verificar su funcionamiento y precisión. El rendimiento del sistema se ha comprobado en dos puntos diferentes de la sala (lugar donde se han hecho todas las pruebas y desarrollado la aplicación) realizando cambios en el código Java para mejorar aún más la precisión y eficacia del posicionamiento. Como resultado de todo esto, se ha comprobado que la ubicación del punto de acceso (AP) y la configuración de la red inalámbrica es importante, y por ello se debe de tener en cuenta para evitar interferencias y tantos errores como sea posible en la estimación de la posición.

Contribución a la localización en interiores basada en comunicaciones inalámbricas

Determinar con buena precisión la posición en la que se encuentra un terminal móvil, cuando éste se halla inmerso en un entorno de interior (centros comerciales, edificios de oficinas, aeropuertos, estaciones, túneles, etc), es el pilar básico sobre el que se sustentan un gran número de aplicaciones y servicios. Muchos de esos servicios se encuentran ya disponibles en entornos de exterior, aunque los entornos de interior se prestan a otros servicios específicos para ellos. Ese número, sin embargo, podría ser significativamente mayor de lo que actualmente es, si no fuera necesaria una costosa infraestructura para llevar a cabo el posicionamiento con la precisión adecuada a cada uno de los hipotéticos servicios. O, igualmente, si la citada infraestructura pudiera tener otros usos distintos, además del relacionado con el posicionamiento. La usabilidad de la misma infraestructura para otros fines distintos ofrecería la oportunidad de que la misma estuviera ya presente en las diferentes localizaciones, porque ha sido previamente desplegada para esos otros usos; o bien facilitaría su despliegue, porque el coste de esa operación ofreciera un mayor retorno de usabilidad para quien lo realiza. Las tecnologías inalámbricas de comunicaciones basadas en radiofrecuencia, ya en uso para las comunicaciones de voz y datos (móviles, WLAN, etc), cumplen el requisito anteriormente indicado y, por tanto, facilitarían el crecimiento de las aplicaciones y servicios basados en el posicionamiento, en el caso de poderse emplear para ello. Sin embargo, determinar la posición con el nivel de precisión adecuado mediante el uso de estas tecnologías, es un importante reto hoy en día. El presente trabajo pretende aportar avances significativos en este campo. A lo largo del mismo se llevará a cabo, en primer lugar, un estudio de los principales algoritmos y técnicas auxiliares de posicionamiento aplicables en entornos de interior. La revisión se centrará en aquellos que sean aptos tanto para tecnologías móviles de última generación como para entornos WLAN. Con ello, se pretende poner de relieve las ventajas e inconvenientes de cada uno de estos algoritmos, teniendo como motivación final su aplicabilidad tanto al mundo de las redes móviles 3G y 4G (en especial a las femtoceldas y small-cells LTE) como al indicado entorno WLAN; y teniendo siempre presente que el objetivo último es que vayan a ser usados en interiores. La principal conclusión de esa revisión es que las técnicas de triangulación, comúnmente empleadas para realizar la localización en entornos de exterior, se muestran inútiles en los entornos de interior, debido a efectos adversos propios de este tipo de entornos como la pérdida de visión directa o los caminos múltiples en el recorrido de la señal. Los métodos de huella radioeléctrica, más conocidos bajo el término inglés “fingerprinting”, que se basan en la comparación de los valores de potencia de señal que se están recibiendo en el momento de llevar a cabo el posicionamiento por un terminal móvil, frente a los valores registrados en un mapa radio de potencias, elaborado durante una fase inicial de calibración, aparecen como los mejores de entre los posibles para los escenarios de interior. Sin embargo, estos sistemas se ven también afectados por otros problemas, como por ejemplo los importantes trabajos a realizar para ponerlos en marcha, y la variabilidad del canal. Frente a ellos, en el presente trabajo se presentan dos contribuciones originales para mejorar los sistemas basados en los métodos fingerprinting. La primera de esas contribuciones describe un método para determinar, de manera sencilla, las características básicas del sistema a nivel del número de muestras necesarias para crear el mapa radio de la huella radioeléctrica de referencia, junto al número mínimo de emisores de radiofrecuencia que habrá que desplegar; todo ello, a partir de unos requerimientos iniciales relacionados con el error y la precisión buscados en el posicionamiento a realizar, a los que uniremos los datos correspondientes a las dimensiones y realidad física del entorno. De esa forma, se establecen unas pautas iniciales a la hora de dimensionar el sistema, y se combaten los efectos negativos que, sobre el coste o el rendimiento del sistema en su conjunto, son debidos a un despliegue ineficiente de los emisores de radiofrecuencia y de los puntos de captura de su huella. La segunda contribución incrementa la precisión resultante del sistema en tiempo real, gracias a una técnica de recalibración automática del mapa radio de potencias. Esta técnica tiene en cuenta las medidas reportadas continuamente por unos pocos puntos de referencia estáticos, estratégicamente distribuidos en el entorno, para recalcular y actualizar las potencias registradas en el mapa radio. Un beneficio adicional a nivel operativo de la citada técnica, es la prolongación del tiempo de usabilidad fiable del sistema, bajando la frecuencia en la que se requiere volver a capturar el mapa radio de potencias completo. Las mejoras anteriormente citadas serán de aplicación directa en la mejora de los mecanismos de posicionamiento en interiores basados en la infraestructura inalámbrica de comunicaciones de voz y datos. A partir de ahí, esa mejora será extensible y de aplicabilidad sobre los servicios de localización (conocimiento personal del lugar donde uno mismo se encuentra), monitorización (conocimiento por terceros del citado lugar) y seguimiento (monitorización prolongada en el tiempo), ya que todos ellas toman como base un correcto posicionamiento para un adecuado desempeño. ABSTRACT To find the position where a mobile is located with good accuracy, when it is immersed in an indoor environment (shopping centers, office buildings, airports, stations, tunnels, etc.), is the cornerstone on which a large number of applications and services are supported. Many of these services are already available in outdoor environments, although the indoor environments are suitable for other services that are specific for it. That number, however, could be significantly higher than now, if an expensive infrastructure were not required to perform the positioning service with adequate precision, for each one of the hypothetical services. Or, equally, whether that infrastructure may have other different uses beyond the ones associated with positioning. The usability of the same infrastructure for purposes other than positioning could give the opportunity of having it already available in the different locations, because it was previously deployed for these other uses; or facilitate its deployment, because the cost of that operation would offer a higher return on usability for the deployer. Wireless technologies based on radio communications, already in use for voice and data communications (mobile, WLAN, etc), meet the requirement of additional usability and, therefore, could facilitate the growth of applications and services based on positioning, in the case of being able to use it. However, determining the position with the appropriate degree of accuracy using these technologies is a major challenge today. This paper provides significant advances in this field. Along this work, a study about the main algorithms and auxiliar techniques related with indoor positioning will be initially carried out. The review will be focused in those that are suitable to be used with both last generation mobile technologies and WLAN environments. By doing this, it is tried to highlight the advantages and disadvantages of each one of these algorithms, having as final motivation their applicability both in the world of 3G and 4G mobile networks (especially in femtocells and small-cells of LTE) and in the WLAN world; and having always in mind that the final aim is to use it in indoor environments. The main conclusion of that review is that triangulation techniques, commonly used for localization in outdoor environments, are useless in indoor environments due to adverse effects of such environments as loss of sight or multipaths. Triangulation techniques used for external locations are useless due to adverse effects like the lack of line of sight or multipath. Fingerprinting methods, based on the comparison of Received Signal Strength values measured by the mobile phone with a radio map of RSSI Recorded during the calibration phase, arise as the best methods for indoor scenarios. However, these systems are also affected by other problems, for example the important load of tasks to be done to have the system ready to work, and the variability of the channel. In front of them, in this paper we present two original contributions to improve the fingerprinting methods based systems. The first one of these contributions describes a method for find, in a simple way, the basic characteristics of the system at the level of the number of samples needed to create the radio map inside the referenced fingerprint, and also by the minimum number of radio frequency emitters that are needed to be deployed; and both of them coming from some initial requirements for the system related to the error and accuracy in positioning wanted to have, which it will be joined the data corresponding to the dimensions and physical reality of the environment. Thus, some initial guidelines when dimensioning the system will be in place, and the negative effects into the cost or into the performance of the whole system, due to an inefficient deployment of the radio frequency emitters and of the radio map capture points, will be minimized. The second contribution increases the resulting accuracy of the system when working in real time, thanks to a technique of automatic recalibration of the power measurements stored in the radio map. This technique takes into account the continuous measures reported by a few static reference points, strategically distributed in the environment, to recalculate and update the measurements stored into the map radio. An additional benefit at operational level of such technique, is the extension of the reliable time of the system, decreasing the periodicity required to recapture the radio map within full measurements. The above mentioned improvements are directly applicable to improve indoor positioning mechanisms based on voice and data wireless communications infrastructure. From there, that improvement will be also extensible and applicable to location services (personal knowledge of the location where oneself is), monitoring (knowledge by other people of your location) and monitoring (prolonged monitoring over time) as all of them are based in a correct positioning for proper performance.

Normalização automática de descrições de hotéis

As descrições de produtos turísticos na área da hotelaria, aviação, rent-a-car e pacotes de férias baseiam-se sobretudo em descrições textuais em língua natural muito heterogénea com estilos, apresentações e conteúdos muito diferentes entre si. Uma vez que o sector do turismo é bastante dinâmico e que os seus produtos e ofertas estão constantemente em alteração, o tratamento manual de normalização de toda essa informação não é possível. Neste trabalho construiu-se um protótipo que permite a classificação e extracção automática de informação a partir de descrições de produtos de turismo. Inicialmente a informação é classificada quanto ao tipo. Seguidamente são extraídos os elementos relevantes de cada tipo e gerados objectos facilmente computáveis. Sobre os objectos extraídos, o protótipo com recurso a modelos de textos e imagens gera automaticamente descrições normalizadas e orientadas a um determinado mercado. Esta versatilidade permite um novo conjunto de serviços na promoção e venda dos produtos que seria impossível implementar com a informação original. Este protótipo, embora possa ser aplicado a outros domínios, foi avaliado na normalização da descrição de hotéis. As frases descritivas do hotel são classificadas consoante o seu tipo (Local, Serviços e/ou Equipamento) através de um algoritmo de aprendizagem automática que obtém valores médios de cobertura de 96% e precisão de 72%. A cobertura foi considerada a medida mais importante uma vez que a sua maximização permite que não se percam frases para processamentos posteriores. Este trabalho permitiu também a construção e população de uma base de dados de hotéis que possibilita a pesquisa de hotéis pelas suas características. Esta funcionalidade não seria possível utilizando os conteúdos originais. ABSTRACT: The description of tourism products, like hotel, aviation, rent-a-car and holiday packages, is strongly supported on natural language expressions. Due to the extent of tourism offers and considering the high dynamics in the tourism sector, manual data management is not a reliable or scalable solution. Offer descriptions - in the order of thousands - are structured in different ways, possibly comprising different languages, complementing and/or overlap one another. This work aims at creating a prototype for the automatic classification and extraction of relevant knowledge from tourism-related text expressions. Captured knowledge is represented in a normalized/standard format to enable new services based on this information in order to promote and sale tourism products that would be impossible to implement with the raw information. Although it could be applied to other areas, this prototype was evaluated in the normalization of hotel descriptions. Hotels descriptive sentences are classified according their type (Location, Services and/or Equipment) using a machine learning algorithm. The built setting obtained an average recall of 96% and precision of 72%. Recall considered the most important measure of performance since its maximization allows that sentences were not lost in further processes. As a side product a database of hotels was built and populated with search facilities on its characteristics. This ability would not be possible using the original contents.

Multi-agent system for personalization of location-based services

The current ubiquitous network access and increase in network bandwidth are driving the sales of mobile location-aware user devices and, consequently, the development of context-aware applications, namely location-based services. The goal of this project is to provide consumers of location-based services with a richer end-user experience by means of service composition, personalization, device adaptation and continuity of service. Our approach relies on a multi-agent system composed of proxy agents that act as mediators and providers of personalization meta-services, device adaptation and continuity of service for consumers of pre-existing location-based services. These proxy agents, which have Web services interfaces to ensure a high level of interoperability, perform service composition and take in consideration the preferences of the users, the limitations of the user devices, making the usage of different types of devices seamless for the end-user. To validate and evaluate the performance of this approach, use cases were defined, tests were conducted and results gathered which demonstrated that the initial goals were successfully fulfilled.

Privacy-friendly Business Models for Location-Based Mobile Services

This paper presents a theoretical model to analyze the privacy issues around location based mobile business models. We report the results of an exploratory field experiment in Switzerland that assessed the factors driving user payoff in mobile business. We found that (1) the personal data disclosed has a negative effect on user payoff; (2) the amount of personalization available has a direct and positive effect, as well as a moderating effect on user payoff; (3) the amount of control over user's personal data has a direct and positive effect, as well as a moderating effect on user payoff. The results suggest that privacy protection could be the main value proposition in the B2C mobile market. From our theoretical model we derive a set of guidelines to design a privacy-friendly business model pattern for third-party services. We discuss four examples to show the mobile platform can play a key role in the implementation of these new business models.