Catálogo de publicaciones - libros

The development of the European Satellite Navigation System, Galileo, the modernisation of GPS, and the recent advances in High Sensitivity GNSS technology have opened up new horizons, leading to new location and context based applications. Nevertheless, these satellite based technologies may not always deliver the necessary navigation and positioning information in a number of difficult environments, as well as when there is accidental or intentional interference with the satellite signals.

Underground car parks and railway tunnels are two examples of difficult environments, where the reception of satellite signals is affected. Similarly, the malicious jamming of satellite signals near landing sites at airports, or the intentional or unintentional uploading of incorrect orbit predictions will render the satellite derived navigation and positioning information unusable. The risk of such interference may be low, but difficult environments are always present in a number of safety-critical transport applications, as well as in a variety of commercial location-based-services, involving the continuous tracking of goods or individuals.

This is when there is a requirement to combine satellite derived navigation and positioning data with other positioning technologies, such as inertial navigation, cellular telephone networks, such as GSM/GPRS, and Wireless Local Area Networks (WLAN). Clearly, the specific combination of a hybrid system will depend on the required accuracy, integrity and extent of geographical coverage of the corresponding application.

The wide variety of tracking applications, involving persons, vehicles, devices or merchandise, for safety, convenience, security, marketing and other purposes, presents multiple challenges, not only with respect to technology development and service provision, but also in terms of what is legally and ethically acceptable. Many of the proposed commercial applications would create few problems regarding general public acceptance. These include the tracking of motor vehicles for congestion monitoring, taxation and insurance purposes, and the tracking of vulnerable individuals, such as the very young or individuals suffering from a debilitating infirmity such as Alzheimer.

Some of these technologies could also be exploited not only by governments for national and internal security purposes, but also by criminals. Clearly, there is a fine boundary between what is ethically acceptable and what is not. Therefore, there is a need for raising public awareness of these issues and starting a debate involving the public at large as well the relevant government, legal and political institutions.

Services in pervasive computing systems must evolve so that they become minimally intrusive and exhibit inherent proactiveness and dynamic adaptability to the current conditions, user preferences and environment. Con-text awareness has the potential to greatly reduce the human attention and interaction bottlenecks, to give the user the impression that services fade into the background, and to support intelligent personalization and adaptability features. To establish this functionality, an infrastructure is required to collect, manage, maintain, synchronize, infer and disseminate context information towards applications and users. This paper presents a context model and ambient context management system that have been integrated into a pervasive service platform. This research is being carried out in the DAIDALOS IST Integrated Project for pervasive environments. The final goal is to integrate the platform developed with a heterogeneous all-IP network, in order to provide intelligent pervasive services to mobile and non-mobile users based on a robust context-aware environment.

Service-centric systems are highly dynamic and often complex systems, with different services running on a distributed network. For the design of context-aware service-centric systems, paradigms have to be developed that deal with the distributed and dynamic nature of these systems, and with the unreliability and unavailability problems of providing information on their context. This paper presents a context architecture for the development of context-aware service-centric systems that provides the context information and deals with these challenges.

Context-aware systems are systems that use context information to adapt their behavior or to customize the content they provide. Prior work in the area of context-aware systems focused on applications where context sources, Context-Aware Services (CASs), and users are in each other’s spatial proximity. In such systems no scalability problem exists. However, other relevant CASs are subject to strong scalability problems due to the number of users, the geographical distribution of the context sources, the users, and the CAS as well as the number of organizations that participate in the provision of the context-aware system.

In this paper, we classify CASs according to their scalability needs and review context provision and service provision infrastructures with regard to their scalability. For building large-scale context-aware systems it is not sufficient to Zuse large-scale service provision and context provision infrastructures. Additionally an integration layer is needed that makes the heterogeneous access interfaces of the context provision infrastructures transparent for the CASs. We outline our proposal for such an integration layer and describe how it can be combined with an infrastructure that allows handhelds themselves to gather context information in their immediate vicinity via wireless technologies.

Navigation for and tracking of humans within a building usually implies significant infrastructure investment and devices are usually too high in weight and volume to be integrated into garments.

We propose a system that relies on existing infrastructure (so requires little infrastructure investment) and is based on a sensor that is low cost, low weight, low volume and can be manufactured to have similar characteristics to everyday clothing (flexible, range of colours).

This proposed solution is based on solar modules. This paper investigates their theoretical and practical characteristics in a simplified scenario. Two models based on theory and on experimental results (empirical model) are developed and validated.

First distance estimations indicate that an empirical model for a particular scenario achieves an accuracy of 18cm with a confidence of 83%.

This paper discusses a three step procedure to perform high definition positioning by the use of low cost Bluetooth devices. The three steps are: Sampling, Deployment, and Real Time Positioning. A genetic algorithm is discussed for deployment optimization and a neural network for real time positioning. A case study, along with experiments and results, are finally discussed dealing with a castle in Sicily where many trials were carried out to the end of arranging a positioning system for context aware service provision to visitors.

In this paper, we present a robust, decentralized approach to RF-based location tracking. Our system, called MoteTrack, is based on low-power radio transceivers coupled with a modest amount of computation and storage capabilities. MoteTrack does not rely upon any back-end server or network infrastructure: the location of each mobile node is computed using a received radio signal strength signature from numerous beacon nodes to a database of signatures that is replicated across the beacon nodes themselves. This design allows the system to function despite significant failures of the radio beacon infrastructure. In our deployment of MoteTrack, consisting of 20 beacon nodes distributed across our Computer Science building, we achieve a 50 percentile and 80 percentile location-tracking accuracy of 2 meters and 3 meters respectively. In addition, MoteTrack can tolerate the failure of up to 60% of the beacon nodes without severely degrading accuracy, making the system suitable for deployment in highly volatile conditions. We present a detailed analysis of MoteTrack’s performance under a wide range of conditions, including variance in the number of obstructions, beacon node failure, radio signature perturbations, receiver sensitivity, and beacon node density.

We present a series of techniques that we have been using to process GPS readings to increase their accuracy. In a study of urban pollution, we have deployed a number of tracked mobile pollution monitors comprising a PDA, GPS sensor and carbon monoxide (CO) sensor. These pollution monitors are carried by pedestrians and cyclists. Because we are operating in an urban environment where the sky is often occluded, the resulting GPS logs will show periods of low availability of fix and a wide variety of error conditions. From the raw GPS and CO logs we are able to make maps of pollution at a 50m scale. However, because we know the behaviour of the carriers of the devices, and we can relate the GPS behaviour and known effects of CO in the environment, we can correct the GPS logs semi-automatically. This allows us to achieve a roughly 5m scale in our maps, which enables us to observe a new class of expected environmental effects. In this paper we present the techniques we have developed and give a general overview of how other knowledge might be integrated by system integrators to correct their own log files.

Location-based services like reminders, electronic graffiti, and tourist guides normally require a custom, location-sensitive database that must be custom-tailored for the application at hand. This deployment cost reduces the initial appeal of such services. However, there is much location-tagged data already available on the Web which can be easily used to create compelling location-aware applications with almost no deployment cost. Such tagged data can be used directly in applications as well as to provide evidence in models of activity. We describe three applications that take advantage of existing Web data combined with location measurements from a GPS receiver. The first application, “Pinpoint Search”, finds web pages of nearby places based on GPS coordinates, queries from a Web mapping service, and general Web searches. The second application, “XRay”, uses the mapping service to find businesses in a building by pointing a GPS-equipped electronic compass at the building. The third application is called “Travelogue”, and it builds a map and clickable points of interest to help automatically annotate a trip based on GPS coordinates. Finally, we discuss the use of Web-based data as rich sources of evidence for probabilistic models of a user’s activity, including a means for interpreting the explanation for the loss of Web signals as users enter structures.

The aim of (short for mon ositioning rchitecture for everal ensors) is to realize a location infrastructure which can make use of a multitude of different sensors and combine their output in a meaningful way to produce a so called that describes the location of a user or device as coordinates and corresponding location probabilities. Furthermore, COMPASS includes a so called translator service, i.e. a build-in component that translates PDFs (or coordinates) to meaningful location identifiers like building names and/or room numbers. This paper gives a short overview on the goals and abilities of COMPASS.