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Moving sensors refers to an emerging class of data intensive applications that impacts disciplines such as communication, health-care, scientific applications, etc. These applications consist of a fixed number of sensors that move and produce streams of data as a function of time. They may require the system to match these streams against stored streams to retrieve relevant data (patterns). With communication, for example, a speaking impaired individual might utilize a haptic glove that translates hand signs into written (spoken) words. The glove consists of sensors for dierent nger joints. These sensors report their location and values as a function of time, producing streams of data. These streams are matched against a repository of spatio-temporal streams to retrieve the corresponding English character or word. The contributions of this study are two folds. First, it introduces a framework to store and retrieve "moving sensors" data. The framework advocates physical data independence and software-reuse. Second, we investigate alternative representations for storage and retrieval of data in support of query processing. We quantify the tradeoff associated with these alternatives using empirical data from RoboCup soccer matches.

. In recent years, spatio-temporal data are increasingly recorded in database-enabled information systems. To share the benefit, often, a public data access is provided utilizing WWW-based visual interfaces. If spatio-temporal data are queried, data visualization and exploration in a spatial and temporal context is needed to better present and analyze spatio-temporal behaviours and relationships. In existing WWW-based interfaces of temporal geographical information or scientific data visualization systems, only videos, static visualizations (images) or, recently, VRML-worlds (Virtual Reality Modeling Language) are applied which support neither 3D- nor temporal navigation, respectively. Additionally, these interfaces offer only small support for further exploratory tools according to the temporal domain and to conceptual database entities which users are often aware of. In this paper, we propose an extension to VRML which supports the description of spatio-temporal (temporal 3D- )graphi...

INTRODUCTION Time is probably one of the most essential and paradoxical concepts that human beings face. Time is always present in our everyday life from the perception of events to the development of human thinking behaviours. However, time is still a difficult concept to describe and formalise as it has no obvious physical characteristics and properties. We can only establish a temporal statement from the observation or prevision of changes. The relationship between time and space is a consequence of the observation of changes as the perception of spatial alterations denotes the existence of time. The representation of time within Geographical Information Systems (GIS) is still an important and expected development to make these systems more suited to the temporal analysis of real-world phenomena. Over the past years, the representation of spatiotemporal data has been extensively discussed by different research communities such as the Artificial Intelligence domain that pro

For some spatiotemporal applications, it can be assumed that the modeled world is precise and bounded, and that also our record of it is precise. While these simplifying assumptions are sufficient in applications like a land information system, they are unnecessarily crude for many other applications that manage data with spatial and/or temporal extents, such as navigational applications. This work explores fuzziness and uncertainty, subsumed under the term indeterminacy, in the spatiotemporal context. To better illustrate the basic spatiotemporal concepts of change or evolution, it is shown how the fundamental modeling concepts of spatial objects, attributes, and relationships and time points and periods are influenced by indeterminacy and how they can be combined. In particular, the focus is on the change of spatial objects and their geometries across time. Four change scenarios are outlined, which concern discrete versus continuous change and asynchronous versus synchronous measurement, and it is shown how to model indeterminacy for each. A case study illustrates the applicability of the paper’s general proposal by describing the uncertainty related to the management of the movements of point objects, such as the management of vehicle positions in a fleet management system.

Although GIS has been applied to many application areas, there is still a need for successful integration of the temporal dimension in current spatial data models in order to deal with the complexity of urban and environmental systems. In particular, there are a few spatio-temporal data models for representing gradual changes. The objective of this paper is to design, at the conceptual level, a spatio-temporal data model that represents and reasons over gradual changes. Our modeling approach considers entities, changes, evolution, events, and processes as modeling primitives in the spatial, temporal and thematic dimensions. Gradual changes are represented at different levels of abstraction while spatio-temporal predicates manipulate the modeling primitives identified. The potential of our modeling approach is illustrated by a case study oriented to the study of "dynamic field" changes in air temperatures in a region of North-East China.

The study of spatial relationships has been one of the most active areas in GIS research over the past twenty years. Many formal models have been proposed for the definition of topological or cardinal relationships. However, these approaches often consider space as a static continuum which does not integrate the temporal dimension. Recent progress in spatio-temporal GIS research attempts to extend the representation of spatial relationships to the integration of the life and motion of spatial entities or in other words, the study of the evolution of spatial entities. However, these models generally consider the evolution of spatial entities, that is, entities constrained by a filiation tree. This paper proposes an alternative view of relationships in space and time, that is, we consider independent entities in space and time. The temporal and spatial dimensions are modelled using a hierarchical approach that allows the description of relationships at different levels of abstraction. We show that hierarchical reasoning in time and space supports the identification of modular relationships, generally not identified in existing temporal GIS models, and suggest that their use has promising potential for many GIS applications.

Incremental updating of a Spatio-Temporal Data Base (STDB) means that master spatial data set is updated when any change (geometric or thematic) occurs, the changes can be recorded, updated and provided successively to users. During this process, a set of editing operations is needed to add, delete or amend spatial objects. As traditional manual operations are labor-intensive and even error–prone, it is necessary to develop a method to automate or semi- automate these editing operations. This requires the automatic

With the development of distributed object technologies and the overwhelming advent of the Web, an object-oriented data model for GIS/LIS is proposed, possessing significantly increasing importance and application, when moving from a static position to a distributed and heterogeneous view. The conceptual model of land information hinges on a complex spatio-temporal object model for defining not only collections of land parcel objects but also distributions of them within a four domain framework.

This paper presents a conceptual modeling language for spatiotemporal applications that offers built-in support for capturing geo-referenced, time-varying information. More specifically, the well-known object-oriented Unified Modeling Language (UML) is extended to capture the semantics of space and time as they appear in spatiotemporal applications. Language clarity and simplicity is maintained in the new language, the Extended Spatiotemporal UML, which introduces a small base set of modeling constructs, namely, the spatial, temporal and thematic constructs, which can then be combined and applied at different levels (i.e., attribute, association, object class) in the object-oriented model. An example is used to illustrate the simplicity and flexibility of this approach, and a formal functional specification of the semantic constructs and their symbolic combinations is given.