Thermodynamics-informed neural networks for physically realistic mixed reality

The imminent impact of immersive technologies in society urges for active research in real-time and interactive physics simulation for virtual worlds to be realistic. In this context, realistic means to be compliant to the laws of physics. In this paper we present a method for computing the dynamic response of (possibly non-linear and dissipative) deformable objects induced by real-time user interactions in mixed reality using deep learning. The graph-based architecture of the method ensures the thermodynamic consistency of the predictions, whereas the visualization pipeline allows a natural and realistic user experience. Two examples of virtual solids interacting with virtual or physical solids in mixed reality scenarios are provided to prove the performance of the method

Thermodynamics-informed neural networks for physically realistic mixed reality

The imminent impact of immersive technologies in society urges for active research in real-time and interactive physics simulation for virtual worlds to be realistic. In this context, realistic means to be compliant to the laws of physics. In this paper we present a method for computing the dynamic response of (possibly non-linear and dissipative) deformable objects induced by real-time user interactions in mixed reality using deep learning. The graph-based architecture of the method ensures the thermodynamic consistency of the predictions, whereas the visualization pipeline allows a natural and realistic user experience. Two examples of virtual solids interacting with virtual or physical solids in mixed reality scenarios are provided to prove the performance of the method

A discordance analysis in manual labelling of urban mobile laser scanning data used for deep learning based semantic segmentation

Labelled point clouds are crucial to train supervised Deep Learning (DL) methods used for semantic segmentation. The objective of this research is to quantify discordances between the labels made by different people in order to assess whether such discordances can influence the success rates of a DL based semantic segmentation algorithm. An urban point cloud of 30 m road length in Santiago de Compostela (Spain) was labelled two times by ten persons. Discordances and its significance in manual labelling between individuals and rounds were calculated. In addition, a ratio test to signify discordance and concordance was proposed. Results show that most of the points were labelled accordingly with the same class by all the people. However, there were many points that were labelled with two or more classes. Class curb presented 5.9% of discordant points and 3.2 discordances for each point with concordance by all people. In addition, the percentage of significative labelling differences of the class curb was 86.7% comparing all the people in the same round and 100% comparing rounds of each person. Analysing the semantic segmentation results with a DL based algorithm, PointNet++, the percentage of concordance points are related with F-score value in R2 = 0.765, posing that manual labelling has significant impact on results of DL-based semantic segmentation methods.Xunta de Galicia | Ref. ED481B-2019-061Ministerio de Ciencia e Innovación | Ref. PID2019-105221RB-C43Ministère de l’Economie of the G. D. of Luxembourg | Ref. SOLSTICE 2019-05-030-24Universidade de Vigo/CISU

Avatar Based Multiplayer Functionalities in Next Generation Communication and Learning in Virtual Reality Social Platforms – Case MarISOT Room

Virtual Reality Social Platforms are increasingly in use in conferences, and exhibitions. COVID19 pandemic is the main reason for a rapid growth but there are reasons such as climate change to believe these technologies will be used widely once we will enter to the post pandemic era. In this paper, we will introduce our vision to combine social functioning and hands-on-training features in one package. We have participated in and organized various events using existing virtual reality social platforms. We will analyze in this paper their pros and cons plus introduce our own technology trials. As a result, we have better understanding what development tools and how much resources would be needed to be able to create the first minimal viable product combining social functioning and hands-on-training features

Metaverse, a Holistic Vision of the New Virtual Reality

Metaverse bursts into the media as a new marketing channel in September 2021, creating an explosion of reactions as brands join the race to be pioneers. Within a fully digital society and from a mature gaming industry, Metaverse is much more than an incubator of marketing and advertising ideas for brands, Metaverse is envisioned as a social disruption. This scenario raises three relevant questions to resolve over time: 1) Will the Metaverse finally take shape as a virtual society or, on the contrary, will it be integrated as one more channel of relationship within the context omnichannel? 2) how customers, brands and institutions are reacting to the Metaverse and 3) in any case, what transversal disruptive changes will be necessary in the new scenario of the Metaverse? From the deep and constant search for information in secondary sources (desk research methodology), this article seeks a holistic vision of the Metaverse, and its reading will allow defining specific areas of research on behavior patterns of people in this new virtual reality.Metaverso irrumpe en los medios como un nuevo canal de marketing en septiembre de 2021, creando una explosión de reacciones a medida que las marcas se unen en la carrera por ser pioneras. Dentro de una sociedad totalmente digital y de una industria del juego madura, Metaverso es mucho más que una incubadora de ideas de marketing y publicidad para marcas, Metaverso se concibe como una disrupción social. Este escenario plantea tres cuestiones relevantes a resolver en el tiempo: 1) ¿Metaverso se configurará finalmente como una sociedad virtual o, por el contrario, se integrará como un canal más de relación dentro del contexto omnicanal? 2) ¿cómo están reaccionando los clientes, marcas e instituciones ante Metaverso? y 3) en todo caso, ¿qué cambios disruptivos transversales serán necesarios en el nuevo escenario del Metaverso? Desde la búsqueda profunda y constante de información en fuentes secundarias (metodologia desk research), este artículo pretende una visión holística del Metaverso, y su lectura permitirá definir áreas específicas de investigación sobre patrones de comportamiento de las personas en esta nueva realidad virtual

Metaverse, a Holistic Vision of the New Virtual Reality

Metaverse bursts into the media as a new marketing channel in September 2021, creating an explosion of reactions as brands join the race to be pioneers. Within a fully digital society and from a mature gaming industry, Metaverse is much more than an incubator of marketing and advertising ideas for brands, Metaverse is envisioned as a social disruption. This scenario raises three relevant questions to resolve over time: 1) Will the Metaverse finally take shape as a virtual society or, on the contrary, will it be integrated as one more channel of relationship within the context omnichannel? 2) how customers, brands and institutions are reacting to the Metaverse and 3) in any case, what transversal disruptive changes will be necessary in the new scenario of the Metaverse? From the deep and constant search for information in secondary sources (desk research methodology), this article seeks a holistic vision of the Metaverse, and its reading will allow defining specific areas of research on behavior patterns of people in this new virtual reality

Toward Data-Driven Digital Therapeutics Analytics: Literature Review and Research Directions

With the advent of Digital Therapeutics (DTx), the development of software as a medical device (SaMD) for mobile and wearable devices has gained significant attention in recent years. Existing DTx evaluations, such as randomized clinical trials, mostly focus on verifying the effectiveness of DTx products. To acquire a deeper understanding of DTx engagement and behavioral adherence, beyond efficacy, a large amount of contextual and interaction data from mobile and wearable devices during field deployment would be required for analysis. In this work, the overall flow of the data-driven DTx analytics is reviewed to help researchers and practitioners to explore DTx datasets, to investigate contextual patterns associated with DTx usage, and to establish the (causal) relationship of DTx engagement and behavioral adherence. This review of the key components of data-driven analytics provides novel research directions in the analysis of mobile sensor and interaction datasets, which helps to iteratively improve the receptivity of existing DTx.Comment: This paper has been accepted by the IEEE/CAA Journal of Automatica Sinic

Digital twins from smart manufacturing to smart cities: a survey

Digital twins are quickly becoming a popular tool in several domains, taking advantage of recent advancements in the Internet of Things, Machine Learning and Big Data, while being used by both the industry sector and the research community. In this paper, we review the current research landscape as regards digital twins in the field of smart cities, while also attempting to draw parallels with the application of digital twins in Industry 4.0. Although digital twins have received considerable attention in the Industrial Internet of Things domain, their utilization in smart cities has not been as popular thus far. We discuss here the open challenges in the field and argue that digital twins in smart cities should be treated differently and be considered as cyber-physical "systems of systems", due to the vastly different system size, complexity and requirements, when compared to other recent applications of digital twins. We also argue that researchers should utilize established tools and methods of the smart city community, such as co-creation, to better handle the specificities of this domain in practice.This work was supported in part by the Project ‘‘I3T—Innovative Application of Industrial Internet of Things (IIoT) in Smart Environments’’ (MIS 5002434) implemented under the ‘‘Action for the Strategic Development on the Research and Technological Sector,’’ funded by the Operational Programme ‘‘Competitiveness, Entrepreneurship and Innovation’’ (NSRF 2014–2020), and in part by Greece and the European Union (European Regional Development Fund)