A Study of Basic 3D Visualization Architecture for Network Operation and Management Tools

Recently, network operation tools using 3D visualization technologies have become more and more important. Generally, 3D visualized network operation tools are useful for computer network management or operation. However, a development of 3D visualized network operation tools requires advanced technical skills and highly cost. On the other hand, 3D computer graphics technologies become more familiar in recent years because of that computer hardwares and softwares are rapidly growing and obtain high performance. In this research, we have developed basic architecture of 3D visualization system for network operation and management tools, by using an open source 3DCG software ``Blender'' and a programming language ``Python``. In this paper, we explain details, results of evaluation and efficiency of the proposed architecture

Wireless Network Visualization in 3D Virtual Environment Framework

Simulating a signal propagation of wireless cognitive network has been widely accepted by researchers in order to come out with three-dimensional (3D) representation data display. Instead of using primitive way to understand the behavior of signal propagation, 3D visualization of wireless networking could also help researchers to study the limitation and exploration of wireless cognitive network deeply. In this paper, we would like to address the requirement and the potential of using 3D representation to visualize properly the wireless cognitive network. We also performed preliminary test of our 3D visualization system using OpenGL graphic library to visualize the propagation of signal travelling in specific room with several medium. The test has been conducted in order to understand the requirement of wireless cognitive network in 3D visualization before the actual system is built

Interactive Visual Analysis of Networked Systems: Workflows for Two Industrial Domains

We report on a first study of interactive visual analysis of networked systems. Working with ABB Corporate Research and Ericsson Research, we have created workflows which demonstrate the potential of visualization in the domains of industrial automation and telecommunications. By a workflow in this context, we mean a sequence of visualizations and the actions for generating them. Visualizations can be any images that represent properties of the data sets analyzed, and actions typically either change the selection of data visualized or change the visualization by choice of technique or change of parameters

Clustering Trajectories by Relevant Parts for Air Traffic Analysis

Clustering of trajectories of moving objects by similarity is an important technique in movement analysis. Existing distance functions assess the similarity between trajectories based on properties of the trajectory points or segments. The properties may include the spatial positions, times, and thematic attributes. There may be a need to focus the analysis on certain parts of trajectories, i.e., points and segments that have particular properties. According to the analysis focus, the analyst may need to cluster trajectories by similarity of their relevant parts only. Throughout the analysis process, the focus may change, and different parts of trajectories may become relevant. We propose an analytical workflow in which interactive filtering tools are used to attach relevance flags to elements of trajectories, clustering is done using a distance function that ignores irrelevant elements, and the resulting clusters are summarized for further analysis. We demonstrate how this workflow can be useful for different analysis tasks in three case studies with real data from the domain of air traffic. We propose a suite of generic techniques and visualization guidelines to support movement data analysis by means of relevance-aware trajectory clustering

Hybrid-Dimensional Visualization and Interaction - Integrating 2D and 3D Visualization with Semi-Immersive Navigation Techniques

The integration of 2D visualization and navigation techniques has reached a state where the potential for improvements is relatively low. With 3D-stereoscopy-compatible technology now commonplace not only in research but also in many households, the need for better 3D visualization and navigation techniques has increased. Nevertheless, for the representation of many abstract data such as networks, 2D visualization remains the primary choice. But often such abstract data is associated with spatial data, thereby increasing the need for combining both 2D and 3D visualization and navigation techniques. Here, we discuss a new hybrid-dimensional approach integrating 2D and 3D (stereoscopic) visualization as well as navigation into a semi-immersive virtual environment. This approach is compared to classical 6DOF navigation techniques. Three scientific as well as educational applications are presented: an educational car model, a plant simulation data exploration, and a cellular model with network exploration, each of these combining spatial with associated abstract data. The software is available at: http://Cm4.CELLmicrocosmos.org

Visual analytics of flight trajectories for uncovering decision making strategies

In air traffic management and control, movement data describing actual and planned flights are used for planning, monitoring and post-operation analysis purposes with the goal of increased efficient utilization of air space capacities (in terms of delay reduction or flight efficiency), without compromising the safety of passengers and cargo, nor timeliness of flights. From flight data, it is possible to extract valuable information concerning preferences and decision making of airlines (e.g. route choice) and air traffic managers and controllers (e.g. flight rerouting or optimizing flight times), features whose understanding is intended as a key driver for bringing operational performance benefits. In this paper, we propose a suite of visual analytics techniques for supporting assessment of flight data quality and data analysis workflows centred on revealing decision making preferences

Knowledge visualization: From theory to practice

Visualizations have been known as efficient tools that can help users analyze com- plex data. However, understanding the displayed data and finding underlying knowl- edge is still difficult. In this work, a new approach is proposed based on understanding the definition of knowledge. Although there are many definitions used in different ar- eas, this work focuses on representing knowledge as a part of a visualization and showing the benefit of adopting knowledge representation. Specifically, this work be- gins with understanding interaction and reasoning in visual analytics systems, then a new definition of knowledge visualization and its underlying knowledge conversion processes are proposed. The definition of knowledge is differentiated as either explicit or tacit knowledge. Instead of directly representing data, the value of the explicit knowledge associated with the data is determined based on a cost/benefit analysis. In accordance to its importance, the knowledge is displayed to help the user under- stand the complex data through visual analytical reasoning and discovery

Inspection and maintenance KPIs to support decision making integrated into Digital Twin tool

In the H2020 European project ASHVIN “Assistants for Healthy, Safe, and Productive Virtual Construction Design, Operation & Maintenance using a Digital Twin”, a set of Key Performance Indicators (KPIs) and Performance Indicators (PIs) to plan and control productive, resource efficient, and safe maintenance are being developed for transport infrastructure. This paper is presenting PIs and KPIs for the assessment and monitoring of the following aspects: Productivity, Resource Efficiency, Cost, Health & Safety during the operational life cycle stage, which is mainly focusing on the inspection and maintenance planning. Quantifiable and measurable PIs and KPIs are proposed and applied on two demonstration projects, highway bridge in Spain and airport runway in Croatia, as part of transportation infrastructure. Proposed PIs and KPIs are integrated into digital twins of the analyzed assets and into decision making tools for risk based maintenance planning. This paper presents the overview of the proposed digital PIs and KPIs applied on two demonstration projects and the integration into decision support tools for efficient and sustainable maintenance planning.Postprint (published version

Inspection and maintenance KPIs to support decision making integrated into Digital Twin tool

In the H2020 European project ASHVIN “Assistants for Healthy, Safe, and Productive Virtual Construction Design, Operation & Maintenance using a Digital Twin”, a set of Key Performance Indicators (KPIs) and Performance Indicators (PIs) to plan and control productive, resource efficient, and safe maintenance are being developed for transport infrastructure. This paper is presenting PIs and KPIs for the assessment and monitoring of the following aspects: Productivity, Resource Efficiency, Cost, Health & Safety during the operational life cycle stage, which is mainly focusing on the inspection and maintenance planning. Quantifiable and measurable PIs and KPIs are proposed and applied on two demonstration projects, highway bridge in Spain and airport runway in Croatia, as part of transportation infrastructure. Proposed PIs and KPIs are integrated into digital twins of the analyzed assets and into decision making tools for risk based maintenance planning. This paper presents the overview of the proposed digital PIs and KPIs applied on two demonstration projects and the integration into decision support tools for efficient and sustainable maintenance planning