Real-time Collaboration Research Articles

Interprofessional Disaster Simulation During the COVID-19 Pandemic: Adapting to Fully Online Learning

BackgroundThis paper describes the rapid conversion of a face-to-face interprofessional (IP) disaster simulation to an online format in response to COVID-19 campus closures. MethodsThe online disaster simulation utilized internet-based tools allowing real-time collaboration between IP students. Team exercises involved disaster triage, disease outbreak investigation, and disaster response. Surveys measuring self-assessment of various IP skills and simulation learning outcomes (SLOs) were compared with responses from previous face-to-face simulations. ResultsResults indicated mean scores for IP skills were higher for online students when compared with in-person simulations, and all SLOs were met. ConclusionsThe online disaster simulation provided an effective, innovative IP educational opportunity.

A Distributed Virtual Reality System Based on Real-Time Dynamic Calculation and Multi-Person Collaborative Operation Applied to the Development Of Subsea Production Systems

To train inexperienced workers for the construction, production, and maintenance of subsea production systems, a virtual reality simulation platform was developed. The entire framework, software, and hardware platforms of the system were designed and introduced. A multi-person collaborative simulation was achieved based on the high-level architecture protocol. The real-time dynamic calculation software Vortex was used to add physical properties to each geometrical model and set collision detections and motion constraints so that the VR system can reflect the real motion response of the structures in real-time during virtual simulation. Visual simulation software Vega Prime and Vortex were integrated to realise the real-time rendering and drawing of virtual ocean engineering scenes. Thus, a virtual simulation system with large-scale complex scenes based on real-time dynamic calculation and multi-person collaborative operation was established. A typical ocean engineering case of subsea manifold installation was simulated using the virtual simulation system, and the detailed simulation flow was explained. A multibody dynamics system of the ship-cable-subsea manifold was established using Orcaflex to obtain the accurate motion response of the subsea manifold during lowering. In the virtual simulation process, the obtained hydrodynamic calculation results can provide an important guideline and reference to the operators. The developed simulation system is a suitable tool for training ocean engineering workers and realistically simulating ocean operation cases.

The multi-user computer-aided design collaborative learning framework

New developments to computer-aided design (CAD) software transform a once solitary modelling task into a collaborative one. The emerging multi-user CAD (MUCAD) systems allow virtual, real-time collaboration, with the potential to expand the learning outcomes and teaching methods of CAD. This paper proposes a MUCAD collaborative learning framework (MUCAD-CLF) to interpret backend analytic data from commercially available MUCAD software. The framework builds on several existing metrics from the literature and introduces newly developed methods to classify CAD actions collected from users’ analytic data. The framework contains two different classification approaches of user actions, categorizing actions by action type (e.g., creating, revising, viewing) and by design space (e.g., constructive, organizing), for comparative analysis. Next, the analytical framework is applied via a collaborative design challenge, corresponding to over 20,000 actions collected from 31 participants. Illustrative analyses utilizing the MUCAD-CLF are presented to demonstrate the resulting insight. Differences in CAD behaviour, indicating differences in learning, are observed between teams made up entirely of novices, entirely of experienced users, or a mix. In pairs of experts and novices, we see both a perceived high-satisfaction apprenticeship experience for the novices and preliminary evidence of an increase in expert design behaviours for the novices. The proposed framework is critical for MUCAD systems to make the most of the educational possibility of combining technical skill-building with team collaboration. Preliminary evidence collected in a fully-virtual design learning activity, and analyzed using the proposed MUCAD-CLF, shows that novice students gain advanced CAD design knowledge when collaborating with experienced teammates. With the user data captured by modern MUCAD software and the MUCAD-CLF presented herein, instructors and researchers can more efficiently assess and visualize students’ performance over the design learning process.

Cloud

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AN ANALYTICAL FRAMEWORK FOR COLLABORATIVE CLOUD-BASED CAD PLATFORM AFFORDANCES

AbstractCloud computing has had an increasing influence on engineering and design. A hallmark of sites such as Github is the promise of rapid iteration and real-time collaboration. Recently, cloud collaborative software has migrated into the realm of physical product design, with computer-aided design (CAD) software platforms such as PTC's Onshape. In this research, we suppose that the effect of cloud collaborative software is multi-faceted; that this type of tool affords a number of new capabilities and behaviours for design individuals and teams. We develop a framework on how to contextualize the changes to design tasks afforded by the unique attributes of these cloud-based, collaborative design tools. We find evidence in our research of design engineers leveraging many aspects of the framework, particularly in learning and engagement with their team, and with resources available from communities of users. However, we find that real-world design engineers are not yet utilizing the full capability of synchronous cloud-platforms with respect to real-time synchronous design iteration within teams or communities.

Inferring Trust From Users' Behaviours; Agents' Predictability Positively Affects Trust, Task Performance and Cognitive Load in Human-Agent Real-Time Collaboration.

Collaborative virtual agents help human operators to perform tasks in real-time. For this collaboration to be effective, human operators must appropriately trust the agent(s) they are interacting with. Multiple factors influence trust, such as the context of interaction, prior experiences with automated systems and the quality of the help offered by agents in terms of its transparency and performance. Most of the literature on trust in automation identified the performance of the agent as a key factor influencing trust. However, other work has shown that the behavior of the agent, type of the agent’s errors, and predictability of the agent’s actions can influence the likelihood of the user’s reliance on the agent and efficiency of tasks completion. Our work focuses on how agents’ predictability affects cognitive load, performance and users’ trust in a real-time human-agent collaborative task. We used an interactive aiming task where participants had to collaborate with different agents that varied in terms of their predictability and performance. This setup uses behavioral information (such as task performance and reliance on the agent) as well as standardized survey instruments to estimate participants’ reported trust in the agent, cognitive load and perception of task difficulty. Thirty participants took part in our lab-based study. Our results showed that agents with more predictable behaviors have a more positive impact on task performance, reliance and trust while reducing cognitive workload. In addition, we investigated the human-agent trust relationship by creating models that could predict participants’ trust ratings using interaction data. We found that we could reliably estimate participants’ reported trust in the agents using information related to performance, task difficulty and reliance. This study provides insights on behavioral factors that are the most meaningful to anticipate complacent or distrusting attitudes toward automation. With this work, we seek to pave the way for the development of trust-aware agents capable of responding more appropriately to users by being able to monitor components of the human-agent relationships that are the most salient for trust calibration.

Cloud BIM Technology as a Means of Collaboration and Project Integration in Smart Cities

Building Information Modeling (BIM) was created to address the Architecture, Engineering, and Construction (AEC) industry’s lack of collaboration among consultants. Advances in cloud BIM have led to the easy exchange of data and real-time collaboration among consultants from conceptual design to the detailed construction drawing stage and through the project life cycle. This is critical in the development of smart cities. Cloud BIM also facilitates visualization of the city and data exchange for internet of things (IoT). Smart city development involves incorporating data from sensors and hardware attached to existing infrastructure. This article studies cloud BIM technology as a means of project integration in smart city development. To do this, a case study of digital modeling for the development of a smart city was done. Benefits include seamless communication, monitoring real-time progress, and visualization of files. Problems encountered include governance problems, problems preserving work sets, the integrity of drawings, and difficulty specifying coordinates on-site.

A Cast Study to Investigate an Affordable Cloud-based Server for Worksharing to Benefit Academia &amp; Small Businesses

Real-time collaboration of multiple digital models is vital for successful construction projects using Virtual Design and Construction (VDC) or Building Information Modeling (BIM). Real-time collaboration allows users to workshare within a multidisciplinary team to co-author multiple smart digital models for better efficiency. This can be done in two ways, either using a physical server (Local Area Network/LAN server) or cloud-based server (Wide Area Network/WAN server). Such cloud-based servers are A360, C4R, Collaboration for Revit, or BIM360Design collaborate, etc. However, above-mentioned cloud services come at a significant price, making it challenging for academia and small businesses to perform real-time collaboration using BIM/VDC models. To find an affordable alternative, an attempt was made as part of the Virtual Design and Construction (VDC) course offered by the Construction Science and Management Department (CSM). For this case study, a popular and free (Google) cloud server was tested as a WAN server to host four multidisciplinary collaborative VDC central models for five users across five different geographic locations and time zones. The study rendered successful results to establish a real-time collaborative workshare environment; hence, can significantly benefit academia and small business.

Trello (product review)

Trello is a project management solution that supports real-time collaboration and communication to accomplish project tasks and goals. Ideal for small-to-medium sized libraries, Trello’s intuitive user interface and robust integrations provide teams the flexibility to customize their workflows to meet their unique needs while delivering value to their user communities. Available with a free or paid subscription, this tool enhances teamwork and provides control over simple and complex projects.

The Cyborg Philharmonic: Synchronizing interactive musical performances between humans and machines

Music offers a uniquely abstract way for the expression of human emotions and moods, wherein melodic harmony is achieved through a succinct blend of pitch, rhythm, tempo, texture, and other sonic qualities. The emerging field of “Robotic Musicianship” focuses on developing machine intelligence, in terms of algorithms and cognitive models, to capture the underlying principles of musical perception, composition, and performance. The capability of new-generation robots to manifest music in a human-like artistically expressive manner lies at the intersection of engineering, computers, music, and psychology; promising to offer new forms of creativity, sharing, and interpreting musical impulses. This manuscript explores how real-time collaborations between humans and machines might be achieved by the integration of technological and mathematical models from Synchronization and Learning, with precise configuration for the seamless generation of melody in tandem, towards the vision of human–robot symphonic orchestra. To explicitly capture the key ingredients of a good symphony—synchronization and anticipation—this work discusses a possible approach based on the joint strategy of: (i) Mapping— wherein mathematical models for oscillator coupling like Kuramoto could be used for establishing and maintaining synchronization, and (ii) Modelling—employing modern deep learning predictive models like Neural Network architectures to anticipate (or predict) future state changes in the sequence of music generation and pre-empt transitions in the coupled oscillator sequence. It is hoped that this discussion will foster new insights and research for better “real-time synchronized human-computer collaborative interfaces and interactions”.

Proposal for a Secure Data Sharing and Processing in Cloud Applications for Healthcare Domain

Information Technology (IT) services have become an inherent component in almost all sectors. Similarly, the health sector has been recently integrating IT to meet the growing demand for medical data exchange and storage. Currently, cloud has become a real hosting alternative for traditional on-permise software. In this model, not only do health organizations have access to a wide range of services but most importantly they are charged based on the usage of these cloud applications. However, especially in the healthcare domain, cloud computing deems challenging as to the sensitivity of health data. This work aims at improving access to medical data and securely sharing them across healthcare professionals, allowing real-time collaboration. From these perspectives, they propose a hybrid cryptosystem based on AES and Paillier to prevent the disclosure of confidential data, as well as computing encrypted data. Unlike most other solutions, the proposed framework adopts a proxy-based architecture to tackle some issues regarding privacy concerns and access control. Subsequently, this system typically guarantees that only authorized users can view or use specific resources in a computing environment. To this aim, they use eXtensible Access Control Markup Language (XACML) standard to properly design and manage access control policies. In this study, they opt for the (Abbreviated Language for Authorization) ALFA tool to easily formulate XACML policies and define complex rules. The simulation results show that the proposal offers simple and efficient mechanisms for the secure use of cloud services within the healthcare domain. Consequently, this framework is an appropriate method to support collaboration among all entities involved in medical information exchange.

Multi-energy conversion based on game theory in the industrial interconnection.

The multi-energy conversion system (MCS) plays an important role in improving the utilization of energy resources and realizing the energy transition. With the application of the new generation of information technologies, the new MCS can realize real-time information interaction, multi-energy collaboration, and real-time demand response, in which energy suppliers can intelligently motivate consumers' energy use behavior. In this paper, an MCS coupled with a cloud platform is proposed to address information explosion and data security issues. Due to the development of Internet technology, the increasing energy data, and the serious energy coupling, it is difficult for traditional optimization methods to deal with the interaction between participants of the MCS. Therefore, the non-cooperative game is used to formulate the interactions between participants with the aim of maximizing the energy suppliers' profit and minimizing the customers' cost. It is proved that the game model is an ordinary game with one Nash equilibrium. The simulation was performed with a gradient projection algorithm and the results show that the proposed MCS improves energy utilization efficiency through energy conversion while ensuring consumer satisfaction, and benefits both the customers and suppliers by reducing the energy consumption cost and the peak load demand, which effectively improve the supply quality and enrich the energy consumption patterns.

A Multi-Layer Architecture for Near Real-Time Collaboration during Distributed Modeling and Simulation of Cyberphysical Systems

Abstract We present a Web-based multi-layer architecture and implementation to enable near real-time collaboration within partially-distributed engineering teams in this paper. Our architecture named Distributed Modeling and Simulation (DisMoSim) enables collaborative 3D modeling and simulation of complex cyberphysical systems (CPS) across different servers, offices, lab spaces, or organizations. More specifically, DisMoSim creates networks of DisMoSim nodes that communicate using Web protocols with little or no perceptible delay. Each node provides different CPS services, e.g., user interface nodes provide collaborative 3D modeling; computational nodes provide simulations of multi-body dynamics or kinematics; storage nodes allow persisting and sharing models and simulation results; hardware-in-the-loop nodes connect physical testing workbenches to provide real-world sensor measurements as simulation input; software-in-the-loop nodes provide control signals to simulate hardware controllers. In the following, we derive a set of design goals and propose our DisMoSim architecture. We illustrate how we used our multi-layer conceptual architecture to implement a variety of CPS services for an example scenario. By this, we demonstrate the practicability and versatility of our approach and conclude by discussing limitations and future work.

Federated Learning in Robotic and Autonomous Systems

Autonomous systems are becoming inherently ubiquitous with the advancements of computing and communication solutions enabling low-latency offloading and real-time collaboration of distributed devices. Decentralized technologies with blockchain and distributed ledger technologies (DLTs) are playing a key role. At the same time, advances in deep learning (DL) have significantly raised the degree of autonomy and level of intelligence of robotic and autonomous systems. While these technological revolutions were taking place, raising concerns in terms of data security and end-user privacy has become an inescapable research consideration. Federated learning (FL) is a promising solution to privacy-preserving DL at the edge, with an inherently distributed nature by learning on isolated data islands and communicating only model updates. However, FL by itself does not provide the levels of security and robustness required by today’s standards in distributed autonomous systems. This survey covers applications of FL to autonomous robots, analyzes the role of DLT and FL for these systems, and introduces the key background concepts and considerations in current research.

Human-Robot Interaction and Collaboration (HRI-C) Utilizing Top-View RGB-D Camera System

In this study, a smart and affordable system that utilizes an RGB-D camera to measure the exact position of an operator with respect to an adjacent robotic manipulator was developed. This developed technology was implemented in a simulated human operation in an automated manufacturing robot to achieve two goals; enhancing the safety measures around the robot by adding an affordable smart system for human detection and robot control and developing a system that will allow the between the human-robot collaboration to finish a predefined task. The system utilized an Xbox Kinect V2 sensor/camera and Scorbot ER-V Plus to model and mimics the selected applications. To achieve these goals, a geometric model for the Scorbot and Xbox Kinect V2 was developed, a robotics joint calibration was applied, an algorithm of background segmentation was utilized to detect the operator and a dynamic binary mask for the robot was implemented, and the efficiency of both systems based on the response time and localization error was analyzed. The first application of the Add-on Safety Device aims to monitor the working-space and control the robot to avoid any collisions when an operator enters or gets closer. This application will reduced and remove physical barriers around the robots, expand the physical work area, reduce the proximity limitations, and enhance the human-robots interaction (HRI) in an industrial environment while sustaining a low cost. The system was able to respond to human intrusion to prevent any collision within 500 ms on average, and it was found that the system’s bottleneck was PC and robot inter-communication speed. The second application was developing a successful collaborative scenario between a robot and a human operator, where a robot will deposit an object on the operator’s hand, mimicking a real-life human-robot collaboration (HRC) tasks. The system was able to detect the operator’s hand and it’s location then command the robot to place an object on the hand, the system was able to place the object within a mean error of 2.4 cm, and the limitation of this system was the internal variables and data transmitting speed between the robot controller and main computer. These results are encouraging and ongoing work aims to experiment with different operations and implement gesture detection in real-time collaboration tasks while keeping the human operator safe and predicting their behavior.

Active and Reactive Power Control of PEV Fast Charging Stations Using a Consecutive Horizon-Based Energy Management Process

The energy management of the fast-charging stations (FCSs) in power systems, while maintaining the power quality and the grid codes, can be particularly challenging, given the highly dynamic load curve, the heterogeneous PEV charging, and the inconvenience to the FCS customers. In this article, a consecutive horizon-based energy management (CHEM) process is proposed for the optimal techno-economic operation of the FCSs integrated with battery energy storage systems (ESS). The proposed CHEM process employs a central supervisory control and a resilient distributed control, for the energy management of FCSs and the active and reactive power control to maintain the grid codes. As such, the grid operator can realize and direct the economic and technical operation of the FCSs with low computational burden, without the need for real-time collaboration with the FCSs. Moreover, the FCSs can autonomously cope with the volatility of PEV charging with the use of the ESS. Furthermore, a novel Volt/VAr control is proposed to confine the unpredicted voltage deviations, including voltage sags, within an acceptable limit. The heterogeneous PEV charging is modeled using the queuing theory, while the inherent characteristics of the lithium-ion batteries are considered. Through multiple case studies, it is shown that the developed CHEM process can provide lower costs and a leveled active power profile for the FCSs, while ensuring that the voltage deviations are well confined and the convenience of PEV owners can still be met.

Design of a Web-based Personalized E-learning Platform

It is important to carry out the distant learning especially in the COVID-19 period when most of schools have to close down. Therefore, a Web-based personalized e-learning platform is presented to satisfy the requests of the middle school student. Firstly, the features of the learner’s needs for e-learning are analysed as the base of the platform. Secondly a novel architecture is proposed that describes the components necessary for the distribution of courses and knowledge in Internet. Thirdly the design of the platform is enabled by the real time collaboration system, multimedia transmission and knowledge repository to help the middle school student study in their own natural ways such as gaming and blogging with friends from interests. The experiment results show that the designed e-learning platform can improve the performance of network throughput and the learner’s satisfactory level.

A Blockchain Framework for Secure Task Sharing in Multi-Access Edge Computing

In the context of Multi-access Edge Computing (MEC), the task sharing mechanism among edge servers is an activity of vital importance for speeding up the computing process and thereby improving the user experience. The distributed resources in the form of edge servers are expected to collaborate with each other in order to boost overall performance of a MEC system. However, there are many challenges to adopt global collaboration among the edge computing server entities and two of them are especially significant: ensuring trust among the servers and developing a unified scheme to enable real-time collaboration and task sharing. In this article, a blockchain framework is proposed to provide a trusted collaboration mechanism among edge servers in a MEC environment. In particular, a permissioned blockchain scheme is investigated to support a trusted design that also provides incentives for collaboration. Finally, Caliper tool and Hyperledger Fabric benchmarks are used to conduct an experimental evaluation of the proposed blockchain scheme embebbed in a MEC framework.

Novel Educational Responses to COVID-19: What is Here to Stay?

Novel Educational Responses to COVID-19: What is Here to Stay?

The growth of social media in science: Social media has evolved from a mere communication channel to an integral tool for discussion and research collaboration.

Social media has become popular among scientists to communicate within and beyond their communities. More specialized channels and the ongoing lockdowns further increase their value and use.