Catálogo de publicaciones - libros

In this paper, we introduce new types of Telematics services for a convergence of Telematics and USN technology and explain several requirements needed for those services. Then, we propose a Telematics application framework that can satisfy those requirements of a real-time service, a reliable data acquisition, and an efficient query processing. The framework is composed of Telematics sensor nodes, Telematics service station, and Telematics vehicle that can provide users with reliable and real-time traffic safety services. Also, we present important issues and solutions that can be applied to an implementation of the framework; In-network spatial query processing, vehicle location determination, and real-time and reliable routing protocol. It is expected that this framework can be helpful for the future Telematics services as a standard model when ubiquitous computing society is pervasively activated.

In this paper we examine the benefit of reports about resources in mobile ad-hoc networks. Each disseminated report represents information about a spatio-temporal event, such as the availability of a parking slot or a cab request. Reports are disseminated by a peer-to-peer broadcast paradigm, in which an object periodically broadcasts the reports it carries to encountered objects. We evaluate the value of resource information in terms of how much time is saved when using the information to discover resources, compared to the case when the information is not used.

Traditional GIS tools are well suited for desktop workstations, but need to be adapted in order to satisfy the requirements of mobility. We propose a concept for sketch-based spatial querying in mobile GIS environments. This concept combines newest techniques for spatial querying and mobile technologies. Such a combination is beneficial because it allows formulating queries by drawing the desired spatial configuration on touch-sensitive screens, thus avoiding typing complex statements in some SQL-like query language. Client-server architectures in mobile environments are characterized by low and fluctuating bandwidth, and by frequent disconnections. We discuss client-server strategies in mobile environments and suggest an adaptive client-server architecture for geo-mobile querying. It is shown that adaptation to the mobile environment is necessary in order to ensure efficiency of geo-mobile queries.

Finding the fastest route in dynamic transportation networks aids navigation service considerably. Existing approaches are either too complex or incapable of handling complex circumstances wherein both the location of a mobile user and the traffic conditions change incessantly over time. In this paper, we propose an incremental search approach based on a variation of A*- Lifelong Planning A* (LPA*) to derive a dynamic fastest path, which continually adapts to the real-time traffic condition while making use of the previous search result. Our experimental results reveal that the proposed approach is a significant improvement over a conventional approach also using the A* algorithm.

In this paper we address the problem and propose the method for continuous range query processing for mobile objects moving on known network paths. The method assumes that the objects know their destination in advance and move along the best/shortest path to it. The method is based on an available 2D indexing scheme (e.g. R* Tree) for indexing transportation network data. The network R* tree is extended to provide matching of queries and objects according to their locations on the network for stationary objects/queries or their network routes for mobile objects/queries and performing the filter step of the continuous query. The refinement step of the query processing methodology generates main memory data structures that represent temporal query result and support periodic, incremental evaluation to produce result updates.

The well known OGC Styled Layer Descriptor (SLD) specification allows to specify the design of a map. On the other hand in LBS and UbiGIS maps need to be generated dynamically taking a lot of factors into account which describe the current user, situation and context. We present how to transform such user and context models with a base map represented as SLD resulting in an “adapted” SLD. Further we discuss how to apply these in order to generate SVG-based mobile maps. In order to generate base maps represented as SLD we developed a ArcMap2SLD-generator. This tool allows designing a map using ESRI ArcMap and automatically converting it into a valid SLD-file. This acts as a base for modifications using the mentioned user and context models. Using this SLD as parameter within WMS-requests results in an “adapted map”. We explain this approach and discuss potentials and weaknesses.

When attempting to locate specific spatial information online users face the burden of having to differentiate between relevant and extraneous spatial content. This problem is more evident in the mobile environment where users are impeded by several device limitations. One way of overcoming this is to automatically profile users’ spatial content preferences by recording all interactions users have with maps and monitoring users’ movements in the field as they interact with maps. We describe a multimodal mobile GIS that implicitly records all user movements, as well as interactions between users and maps, to dynamically recommend information and to infer persistent spatial information preferences. A search engine, prefetching context-aware information, is incorporated to enhance the users’ experiences. Modeling preferences in this manner allows us to recommend personalized context-aware spatial content to users whenever they request maps. A specific case study has been developed around subjects working on surveying tasks where spatial information is required in the field.

In the context of Web personalization, Markov chains have been recently proposed to model user’s navigational trails, in order to infer user preference and predict future visits through computation of transitional probabilities. Based on these principles, the research introduced in this paper develops a hybrid Web personalization approach that applies k-order Markov chains towards an integration of spatial proximity and semantic similarity for the manipulation of geographical data on the Web. This framework personalizes Web navigational experiences over spatial entities embedded in Web documents. A reinforcement process is also introduced to evaluate and adapt interactions between the user and the Web on the basis of user’s relevance feedbacks. An illustrative case study applied to spatial information available on the Web exemplifies our approach.

The World Wide Web constitutes a large information space and a promising support for the development of data inference, analysis and mining mechanisms. The research presented in this paper introduces a modelling approach that derives a social network and computes some of its emerging properties, from the semantics exhibited from a domain knowledge embedded in a series of Web pages. The framework is applied to the research communities related to a series of conferences in a given domain, and the university connections materialised by the researcher trajectories over time. The properties of the social network are analysed using graph-based measures, and a novel geographical dispersion coefficient.

This paper discusses the dynamic presentation of heterogeneous spatio-temporal content along a trajectory. Applications based on this scheme provide users with the ability to view target information and its surrounding context together in an opportunistic manner. We discuss various types of triggers contained in a trajectory that induce dynamic changes in content. We describe different implementations based on this scheme.