scholarly journals BIM in People2People and Things2People Interactive Process

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2982
Author(s):  
Bruno Mataloto ◽  
João C. Ferreira ◽  
Ricardo Resende ◽  
Rita Moura ◽  
Sílvia Luís
Keyword(s):  
User Behavior ◽  
3D Visualization ◽  
Research Work ◽  
Data Representation ◽  
Sensor Data ◽  
University Campus ◽  
Shared Spaces ◽  
Interactive 3D ◽  
Interaction Approach ◽  
Real Time Information

In this research work, we present an IoT solution to environment variables using a LoRa transmission technology to give real-time information to users in a Things2People process and achieve savings by promoting behavior changes in a People2People process. These data are stored and later processed to identify patterns and integrate with visualization tools, which allow us to develop an environmental perception while using the system. In this project, we implemented a different approach based on the development of a 3D visualization tool that presents the system collected data, warnings, and other users’ perception in an interactive 3D model of the building. This data representation introduces a new People2People interaction approach to achieve savings in shared spaces like public buildings by combining sensor data with the users’ individual and collective perception. This approach was validated at the ISCTE-IUL University Campus, where this 3D IoT data representation was presented in mobile devices, and from this, influenced user behavior toward meeting campus sustainability goals.

scholarly journals Interactive 3D Exploration of RDF Graphs through Semantic Planes

2018 ◽  
Vol 10 (8) ◽  
pp. 81 ◽  
Author(s):  
Fabio Viola ◽  
Luca Roffia ◽  
Francesco Antoniazzi ◽  
Alfredo D’Elia ◽  
Cristiano Aguzzi ◽  
...  
Keyword(s):  
Semantic Web ◽  
3D Visualization ◽  
Data Representation ◽  
Knowledge Bases ◽  
Rdf Graph ◽  
Common Concept ◽  
Interactive 3D ◽  
3D Scene ◽  
Rdf Graphs ◽  
3D Exploration

This article presents Tarsier, a tool for the interactive 3D visualization of RDF graphs. Tarsier is mainly intended to support teachers introducing students to Semantic Web data representation formalisms and developers in the debugging of applications based on Semantic Web knowledge bases. The tool proposes the metaphor of semantic planes as a way to visualize an RDF graph. A semantic plane contains all the RDF terms sharing a common concept; it can be created, and further split into several planes, through a set of UI controls or through SPARQL 1.1 queries, with the full support of OWL and RDFS. Thanks to the 3D visualization, links between semantic planes can be highlighted and the user can navigate within the 3D scene to find the better perspective to analyze data. Data can be gathered from generic SPARQL 1.1 protocol services. We believe that Tarsier will enhance the human friendliness of semantic technologies by: (1) helping newcomers assimilate new data representation formats; and (2) increasing the capabilities of inspection to detect relevant situations even in complex RDF graphs.

Interactive 3D Visualization with Dual Leap Motions

2018 ◽  
Vol 30 (7) ◽  
pp. 1268 ◽  
Author(s):  
Guodao Sun ◽  
Puyong Huang ◽  
Yipeng Liu ◽  
Ronghua Liang
Keyword(s):  
3D Visualization ◽  
Interactive 3D

scholarly journals Outlier Detection Transilience-Probabilistic Model for Wind Tunnels Based on Sensor Data

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2532
Author(s):  
Encarna Quesada ◽  
Juan J. Cuadrado-Gallego ◽  
Miguel Ángel Patricio ◽  
Luis Usero
Keyword(s):  
Anomaly Detection ◽  
Outlier Detection ◽  
Research Work ◽  
Industrial Sector ◽  
Sensor Data ◽  
Correct Selection ◽  
Wind Tunnels ◽  
Data Set ◽  
First Case ◽  
Anomaly Analysis

Anomaly Detection research is focused on the development and application of methods that allow for the identification of data that are different enough—compared with the rest of the data set that is being analyzed—and considered anomalies (or, as they are more commonly called, outliers). These values mainly originate from two sources: they may be errors introduced during the collection or handling of the data, or they can be correct, but very different from the rest of the values. It is essential to correctly identify each type as, in the first case, they must be removed from the data set but, in the second case, they must be carefully analyzed and taken into account. The correct selection and use of the model to be applied to a specific problem is fundamental for the success of the anomaly detection study and, in many cases, the use of only one model cannot provide sufficient results, which can be only reached by using a mixture model resulting from the integration of existing and/or ad hoc-developed models. This is the kind of model that is developed and applied to solve the problem presented in this paper. This study deals with the definition and application of an anomaly detection model that combines statistical models and a new method defined by the authors, the Local Transilience Outlier Identification Method, in order to improve the identification of outliers in the sensor-obtained values of variables that affect the operations of wind tunnels. The correct detection of outliers for the variables involved in wind tunnel operations is very important for the industrial ventilation systems industry, especially for vertical wind tunnels, which are used as training facilities for indoor skydiving, as the incorrect performance of such devices may put human lives at risk. In consequence, the use of the presented model for outlier detection may have a high impact in this industrial sector. In this research work, a proof-of-concept is carried out using data from a real installation, in order to test the proposed anomaly analysis method and its application to control the correct performance of wind tunnels.

scholarly journals A Novel Building Temperature Simulation Approach Driven by Expanding Semantic Segmentation Training Datasets with Synthetic Aerial Thermal Images

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 353
Author(s):  
Yu Hou ◽  
Rebekka Volk ◽  
Lucio Soibelman
Keyword(s):  
Semantic Segmentation ◽  
Sensor Data ◽  
University Campus ◽  
City Center ◽  
Thermal Images ◽  
Complex Envelope ◽  
Virtual Camera ◽  
Image Translation ◽  
Rgb Images ◽  
Synthetic Datasets

Multi-sensor imagery data has been used by researchers for the image semantic segmentation of buildings and outdoor scenes. Due to multi-sensor data hunger, researchers have implemented many simulation approaches to create synthetic datasets, and they have also synthesized thermal images because such thermal information can potentially improve segmentation accuracy. However, current approaches are mostly based on the laws of physics and are limited to geometric models’ level of detail (LOD), which describes the overall planning or modeling state. Another issue in current physics-based approaches is that thermal images cannot be aligned to RGB images because the configurations of a virtual camera used for rendering thermal images are difficult to synchronize with the configurations of a real camera used for capturing RGB images, which is important for segmentation. In this study, we propose an image translation approach to directly convert RGB images to simulated thermal images for expanding segmentation datasets. We aim to investigate the benefits of using an image translation approach for generating synthetic aerial thermal images and compare those approaches with physics-based approaches. Our datasets for generating thermal images are from a city center and a university campus in Karlsruhe, Germany. We found that using the generating model established by the city center to generate thermal images for campus datasets performed better than using the latter to generate thermal images for the former. We also found that using a generating model established by one building style to generate thermal images for datasets with the same building styles performed well. Therefore, we suggest using training datasets with richer and more diverse building architectural information, more complex envelope structures, and similar building styles to testing datasets for an image translation approach.

scholarly journals Interactive 3D visualization for theoretical virtual observatories

2018 ◽  
Vol 477 (2) ◽  
pp. 1495-1507 ◽  
Author(s):  
T Dykes ◽  
A Hassan ◽  
C Gheller ◽  
D Croton ◽  
M Krokos
Keyword(s):  
3D Visualization ◽  
Interactive 3D ◽  
Virtual Observatories

A service-oriented context-awareness reasoning framework and its implementation

2018 ◽  
Vol 36 (6) ◽  
pp. 1114-1134 ◽  
Author(s):  
Xiufeng Cheng ◽  
Jinqing Yang ◽  
Lixin Xia
Keyword(s):  
Context Awareness ◽  
Service Providers ◽  
User Behavior ◽  
Contextual Information ◽  
Sensor Data ◽  
Context Information ◽  
Content Type ◽  
Low Level ◽  
Service Oriented ◽  
High Level

PurposeThis paper aims to propose an extensible, service-oriented framework for context-aware data acquisition, description, interpretation and reasoning, which facilitates the development of mobile applications that provide a context-awareness service.Design/methodology/approachFirst, the authors propose the context data reasoning framework (CDRFM) for generating service-oriented contextual information. Then they used this framework to composite mobile sensor data into low-level contextual information. Finally, the authors exploited some high-level contextual information that can be inferred from the formatted low-level contextual information using particular inference rules.FindingsThe authors take “user behavior patterns” as an exemplary context information generation schema in their experimental study. The results reveal that the optimization of service can be guided by the implicit, high-level context information inside user behavior logs. They also prove the validity of the authors’ framework.Research limitations/implicationsFurther research will add more variety of sensor data. Furthermore, to validate the effectiveness of our framework, more reasoning rules need to be performed. Therefore, the authors may implement more algorithms in the framework to acquire more comprehensive context information.Practical implicationsCDRFM expands the context-awareness framework of previous research and unifies the procedures of acquiring, describing, modeling, reasoning and discovering implicit context information for mobile service providers.Social implicationsSupport the service-oriented context-awareness function in application design and related development in commercial mobile software industry.Originality/valueExtant researches on context awareness rarely considered the generation contextual information for service providers. The CDRFM can be used to generate valuable contextual information by implementing more reasoning rules.

KG3D: An Interactive 3D Visualization Tool for Knowledge Graphs

2019 ◽  
pp. 886-889
Author(s):  
Dawei Xu ◽  
Lin Wang ◽  
Xin Wang ◽  
Dianquan Li ◽  
Jianpeng Duan ◽  
...  
Keyword(s):  
3D Visualization ◽  
Visualization Tool ◽  
Knowledge Graphs ◽  
Interactive 3D

scholarly journals 3D visualization in otosurgery

2020 ◽  
Vol 19 (6) ◽  
pp. 38-49
Author(s):  
D. M. Kuz’min ◽  
◽  
A. A. Fedotova ◽  
Keyword(s):  
Middle Ear ◽  
3D Visualization ◽  
Research Work ◽  
Three Dimensional ◽  
Middle Ear Surgery ◽  
Ear Surgery ◽  
Task Load ◽  
Additional Information ◽  
Surgical Field ◽  
Nasa Task Load Index

The main priority of middle ear surgery is to create a safe and optimal view of the surgical field, as well as the most accurate visualization of anatomical structures, which is a driving factor in the evolution of otosurgery. The additional information provided by three-dimensional (3D) images has been proven to improve understanding of the temporal bone anatomy and improve the operator’s ability to assess associated diseases, thereby optimizing surgical management. In the presented experimental research work, a new technique for visualizing the surgical field is described, which improves the quality of the operator’s work and expands the possibilities of middle ear surgery. On the basis of the Chair of Otorhinolaryngology of the Mechnikov North-Western State Medical University a remote adapter for an endoscopic tube was created, which allows you to broadcast the video image received from its distal end to virtual reality glasses. For a detailed understanding of the principle of information transmission in a new three-dimensional reality, we used concepts such as disparity and stereopsis. All research results were evaluated according to the NASA Task Load Index scale. Analyzing the results of the experiment, in the conditions of three-dimensional visualization of the surgical field, a lower level of subjective workload was revealed, which was regarded as a positive effect of the realization of the phenomenon of stereopsis, when performing manipulations on the middle ear.

scholarly journals The Design and Testing of 3DmoveR: an Experimental Tool for Usability Studies of Interactive 3D Maps

2018 ◽  
pp. 31-63 ◽  
Author(s):  
Lukáš Herman ◽  
Tomáš Řezník ◽  
Zdeněk Stachoň ◽  
Jan Russnák
Keyword(s):  
Spatial Data ◽  
Response Times ◽  
3D Visualization ◽  
User Interaction ◽  
Google Earth ◽  
Web Based ◽  
3D Environments ◽  
Camera Position ◽  
Interactive 3D ◽  
3D Scene

Various widely available applications such as Google Earth have made interactive 3D visualizations of spatial data popular. While several studies have focused on how users perform when interacting with these with 3D visualizations, it has not been common to record their virtual movements in 3D environments or interactions with 3D maps. We therefore created and tested a new web-based research tool: a 3D Movement and Interaction Recorder (3DmoveR). Its design incorporates findings from the latest 3D visualization research, and is built upon an iterative requirements analysis. It is implemented using open web technologies such as PHP, JavaScript, and the X3DOM library. The main goal of the tool is to record camera position and orientation during a user’s movement within a virtual 3D scene, together with other aspects of their interaction. After building the tool, we performed an experiment to demonstrate its capabilities. This experiment revealed differences between laypersons and experts (cartographers) when working with interactive 3D maps. For example, experts achieved higher numbers of correct answers in some tasks, had shorter response times, followed shorter virtual trajectories, and moved through the environment more smoothly. Interaction-based clustering as well as other ways of visualizing and qualitatively analyzing user interaction were explored.

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