Cyril Ray

Semantic management of moving objects

We review the state-of-the-art in the semantic representation of moving objects.We present the key research challenges for the semantic management of moving objects.We propose a scalable framework for the semantic management of moving objects.The framework supports a distributed storage and analysis of semantic mobility data. This position paper presents our vision for the semantic management of moving objects. We argue that exploiting semantic techniques in mobility data management can bring valuable benefits to many domains characterized by the mobility of users and moving objects in general, such as traffic management, urban dynamics analysis, ambient assisted living, emergency management, m-health, etc. We present the state-of-the-art in the domain of management of semantic locations and trajectories, and outline research challenges that need to be investigated to enable a full-fledged and intelligent semantic management of moving objects and location-based services that support smarter mobility. We propose a distributed framework for the semantic enrichment and management of mobility data and analyze the potential deployment and exploitation of such a framework.

Real-Time 3D Monitoring of Marine Navigation

Maritime transportation has a huge impact on the world economy and our everyday lives. Nowadays, the vast majority of world goods are carried by sea by huge container carriers. The disasters and damages caused in the event of major sea collisions can pose serious threats to the environment. This stresses the urgent need for the development of maritime navigation systems whose objective should be to contribute to a safer sea. Among many technical and methodological issues, there is still a need for distributed computing architectures that will favour real-time monitoring of mobile objects at sea, and generation of computer and visual-based environments. The research presented in this chapter introduces a three-dimensional (3D) GIS applied to maritime navigation. The three-dimensional component facilitates the understanding of maritime behaviours and patterns at sea, thus favouring better decisions for either sailors at sea or maritime authorities in charge of traffic monitoring.

Design principles of a stream-based framework for mobility analysis

Trajectory analysis is of crucial importance in several fields as social analysis, zoology, climatology or traffic monitoring. Over the last decade, the number of mobile systems and devices recording their positions has grown significantly generating a deluge of spatial and temporal data to analyze. This increasing volume of data raises numerous issues in terms of storage, processing and extraction of information. Previous works considering movement analysis have been mainly oriented towards either archived data processing and mining or continuous handling of incoming streams. The research developed in this pa- per introduces the design principles of a holistic approach combining real-time processing and archived data analysis to process mobility data “on the fly”. This solution aims to provide better results comparing to both purely offline and online approaches. This research considers distributed data and processing to be more efficient. The design principles are applied to maritime traffic analysis and a few representative examples are introduced to demonstrate the relevance of our approach.

Visual exploration of movement and event data with interactive time masks

We introduce the concept of time mask, which is a type of temporal filter suitable for selection of multiple disjoint time intervals in which some query conditions fulfil. Such a filter can be applied to time-referenced objects, such as events and trajectories, for selecting those objects or segments of trajectories that fit in one of the selected time intervals. The selected subsets of objects or segments are dynamically summarized in various ways, and the summaries are represented visually on maps and/or other displays to enable exploration. The time mask filtering can be especially helpful in analysis of disparate data (e.g., event records, positions of moving objects, and time series of measurements), which may come from different sources. To detect relationships between such data, the analyst may set query conditions on the basis of one dataset and investigate the subsets of objects and values in the other datasets that co-occurred in time with these conditions. We describe the desired features of an interactive tool for time mask filtering and present a possible implementation of such a tool. By example of analysing two real world data collections related to aviation and maritime traffic, we show the way of using time masks in combination with other types of filters and demonstrate the utility of the time mask filtering.

A hybrid approach combining real-time and archived data for mobility analysis

Mobility analysis is involved in many areas such as urban planning, traffic monitoring, climatology, study of social and animal phenomena to mention a few examples. The emergence and proliferation of mobile and sensor-based systems generate a significant increase of spatial and temporal data in terms of volume and frequency of update. In particular, the storage, management and analysis of the large data sets generated become a non straightforward task. Current works related to the manipulation of mobility data have been directed towards either mining archived historical data or continuous processing of incoming data streams. Our research introduces a hybrid approach whose objective is to provide a combined processing of real-time data streams and archived data. The principles of our approach is to promote the distributed and parallelized processing of mobility data. The whole framework is currently applied to the real-time monitoring of maritime traffic.

Amplitude-based dominant component analysis for underwater mines extraction in side scans sonar

For the first time, the application of the amplitude dominant component analysis (ADCA) to the segmentation of sonar images is explored. We exploit the saliency of the objects in side scans sonar images for underwater mines recognition. Due to the textural and multicomponent nature of the sonar image, a set of bandpass filters is used to decompose the image into narrowband components which lends itself more easily to analysis. The filters bank used is a set of Gabor filters, favored due to their optimal joint spatial and spectral localization. The ADCA-based segmentation is illustrated on real high-resolution sonar images, yielding very promising results showing the interest to exploit the saliency of sonar images.

Seafloor characterization by bathymetric image segmentation

The aim of this work is the characterization of seafloor using bathymetric images segmentation. The bathy-metric image is considered as set of oriented wave profiles generated, in general, by unidirectional currents (water flows constantly in one direction) where each profile can be viewed as the superposition of fast oscillations (ripples) and slow oscillations (sand waves). Due to the texture and multicomponent aspects of the bathymetric image, the characterization is performed using an adaptive mutliresolution decomposition based on the multivariate empirical mode decomposition (MEMD) technique. The MEMD a data driven technique, well dedicated for non-stationary and multicomponent data analysis, is applied to multivariate bathymetric profiles to generate 2D intrinsic empirical functions (IMFs) or empirical images each one associated to a bedform such as ripple, sand wave or dune (migaripple). Preliminary results on real bathymetric images shows the interest of the MEMD as a feasible decomposition tool to identify main bedforms.

A Distributed Computing Approach for Transportation Modelling and Simulation: Application to an Airport System

The paper presents a research that explores and validates the interest of distributed systems for the modeling and simulation of transportation data flows. Introduced is a hierarchical and graph based modeling approach that represents a first step towards the development of a computing architecture flexible enough to be applied to different application areas. The approach relies on distributed simulation principles and includes several features particularly adapted for the simulation of transportation system from the modeling, distribution and simulation of data flows. The computational implementation includes several functional levels from the logical representation of data structures and properties at different levels of granularity, to the control, monitoring and analysis of data flows within the represented transportation system. A user oriented interface supports the parameterization, execution, control, monitoring and visualization of the simulations.