An IoT Based Architecture for Enhancing the Effectiveness of Prototype Medical Instruments Applied to Neurodegenerative Disease Diagnosis

Human errors are probably the most critical cause of the large amount of medical accidents. Medical cyber-physical systems (MCPS) have been suggested as a possible approach for detecting and limiting the impact of errors and wrong procedures. However, during the initial development phase of medical instruments, regular MCPS systems are not a viable approach, because of the high costs of repeating complex validation procedures, due to modifications of the prototype instrument. In this work, a communication architecture, inspired by recent Internet of Things (IoT) advances, is proposed for connecting prototype instruments to the cloud, to allow direct and real-time interaction between developers and instrument operators. Without loss of generality, a real-world use case is addressed, dealing with the use of transcranial magnetic stimulation (TMS) for neurodegenerative disease diagnosis. The proposed infrastructure leverages on a message-oriented middleware, complemented by historical database for further data processing. Two of the most diffused protocols for cloud data exchange (MQTT and AMQP) have been investigated. The experimental setup has been focused on the real-time performance, which are the most challenging requirements. Time-related metrics confirm the feasibility of the proposed approach, resulting in an end-to-end delay on the order of few tens of milliseconds for local networks and up to few hundreds of milliseconds for geographical scale networks.

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An Adaptive Bitrate Switching Algorithm for Speech Applications in Context of WebRTC

ACM Transactions on Multimedia Computing Communications and Applications ◽

10.1145/3458751 ◽

2021 ◽

Vol 17 (4) ◽

pp. 1-21

Author(s):

Mohannad Alahmadi ◽

Peter Pocta ◽

Hugh Melvin

Keyword(s):

Real Time ◽

Data Exchange ◽

Quality Of Experience ◽

End User ◽

High Quality ◽

Content Type ◽

Switching Algorithm ◽

Wide Range ◽

The Impact

Web Real-Time Communication (WebRTC) combines a set of standards and technologies to enable high-quality audio, video, and auxiliary data exchange in web browsers and mobile applications. It enables peer-to-peer multimedia sessions over IP networks without the need for additional plugins. The Opus codec, which is deployed as the default audio codec for speech and music streaming in WebRTC, supports a wide range of bitrates. This range of bitrates covers narrowband, wideband, and super-wideband up to fullband bandwidths. Users of IP-based telephony always demand high-quality audio. In addition to users’ expectation, their emotional state, content type, and many other psychological factors; network quality of service; and distortions introduced at the end terminals could determine their quality of experience. To measure the quality experienced by the end user for voice transmission service, the E-model standardized in the ITU-T Rec. G.107 (a narrowband version), ITU-T Rec. G.107.1 (a wideband version), and the most recent ITU-T Rec. G.107.2 extension for the super-wideband E-model can be used. In this work, we present a quality of experience model built on the E-model to measure the impact of coding and packet loss to assess the quality perceived by the end user in WebRTC speech applications. Based on the computed Mean Opinion Score, a real-time adaptive codec parameter switching mechanism is used to switch to the most optimum codec bitrate under the present network conditions. We present the evaluation results to show the effectiveness of the proposed approach when compared with the default codec configuration in WebRTC.

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The Impact of Digital Transformation for Social Enterprise

10.31227/osf.io/3px8d ◽

2019 ◽

Author(s):

reine yolite

Keyword(s):

Real Time ◽

Inventory Management ◽

Cost Effective ◽

Digital Transformation ◽

Social Enterprises ◽

Business Decisions ◽

Social Media Networks ◽

Customer Expectation ◽

Time Interaction ◽

The Impact

Nowadays most people remain connected via social media networks. This is a highly lucrative and expansive market for social enterprises to penetrate and evaluate the buying patterns of customers so that they can provide customized user experiences. Digital transformation provides countless advantages and options, including improved inventory management, detailed insights, enhanced real-time customer interaction, higher productivity, reliable forecasting, dependable business decisions, improved resourced allocation, and real time interaction with customers. This sort of technology and innovation, when coupled with digital business, lends support to the digital transformation of a company, providing it with the requisite degree of competitive advantage. Digital transformation helps businesses meet the demands of the changing digital economy. Also with the help of digital transformation, companies are finally able to go paperless. So with lots of this social enterprises in Asia that use or participant in digital transformation it can help them to meet customer expectation soon, and digital transformation is cost effective when social enterprises profits, the community or the society profits.

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Real-time monitoring of seismic moment and radiated energy

10.5194/egusphere-egu2020-19253 ◽

2020 ◽

Author(s):

Davide Scafidi ◽

Daniele Spallarossa ◽

Matteo Picozzi ◽

Dino Bindi

Keyword(s):

Real Time ◽

Seismic Moment ◽

P Wave ◽

Calibration Data ◽

S Wave ◽

Data Set ◽

Local Networks ◽

Radiated Energy ◽

The Impact ◽

Large Earthquakes

<p>Understanding the dynamics of faulting is a crucial target in earthquake source physics (Yoo et al., 2010). To study earthquake dynamics it is indeed necessary to look at the source complexity from different perspectives; in this regard, useful information is provided by the seismic moment (M0), which is a static measure of the earthquake size, and the seismic radiated energy (ER), which is connected to the rupture kinematics and dynamics (e.g. Bormann & Di Giacomo 2011a). Studying spatial and temporal evolution of scaling relations between scaled energy (i.e., e = ER/M0) versus the static measure of source dimension (M0) can provide valuable indications for understanding the earthquake generation processes, single out precursors of stress concentrations, foreshocks and the nucleation of large earthquakes (Picozzi et al., 2019). In the last ten years, seismology has undergone a terrific development. Evolution in data telemetry opened the new research field of real-time seismology (Kanamori 2005), which targets are the rapid determination of earthquake location and size, the timely implementation of emergency plans and, under favourable conditions, earthquake early warning. On the other hand, the availability of denser and high quality seismic networks deployed near faults made possible to observe very large numbers of micro-to-small earthquakes, which is pushing the seismological community to look for novel big data analysis strategies. Large earthquakes in Italy have the peculiar characteristic of being followed within seconds to months by large aftershocks of magnitude similar to the initial quake or even larger, demonstrating the complexity of the Apennines&#8217; faults system (Gentili and Giovanbattista, 2017). Picozzi et al. (2017) estimated the radiated seismic energy and seismic moment from P-wave signals for almost forty earthquakes with the largest magnitude of the 2016-2017 Central Italy seismic sequence. Focusing on S-wave signals recorded by local networks, Bindi et al. (2018) analysed more than 1400 earthquakes in the magnitude ranges 2.5 &#8804; Mw &#8804; 6.5 of the same region occurred from 2008 to 2017 and estimated both ER and M0, from which were derived the energy magnitude (Me) and Mw for investigating the impact of different magnitude scales on the aleatory variability associated with ground motion prediction equations. In this work, exploiting first steps made in this direction by Picozzi et al. (2017) and Bindi et al. (2018), we derived a novel approach for the real-time, robust estimation of seismic moment and radiated energy of small to large magnitude earthquakes recorded at local scales. In the first part of the work, we describe the procedure for extracting from the S-wave signals robust estimates of the peak displacement (PDS) and the cumulative squared velocity (IV2S). Then, exploiting a calibration data set of about 6000 earthquakes for which well-constrained M0 and theoretical ER values were available, we describe the calibration of empirical attenuation models. The coefficients and parameters obtained by calibration were then used for determining ER and M0 of a testing dataset</p>

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Remote Indoor Construction Progress Monitoring Using Extended Reality

10.20944/preprints202011.0585.v1 ◽

2020 ◽

Author(s):

Ahmed Khairadeen Ali ◽

One Jae Lee ◽

DoYeop Lee ◽

Chansik Park

Keyword(s):

Real Time ◽

Data Exchange ◽

Progress Monitoring ◽

Laser Scanner ◽

Visual Programming ◽

Inspection System ◽

Cloud Data ◽

Recent Developments ◽

Scan Data ◽

Processing And Storage

Despite recent developments in monitoring and visualizing construction progress, the data exchange between construction jobsite and office lacks automation and real-time recording. To address this issue, a near real-time construction work inspection system called iVR is proposed; this system integrates 3D scanning, extended reality, and visual programming to visualize interactive onsite inspection for indoor activities and provide numeric data. iVR comprises five modules: iVR-location finder (finding laser scanner located in the construction site) iVR-scan (capture point cloud data of jobsite indoor activity), iVR-prepare (processes and convert 3D scan data into a 3D model), iVR-inspect (conduct immersive visual reality inspection in construction office), and iVR-feedback (visualize inspection feedback from jobsite using augmented reality). An experimental lab test is conducted to validate the applicability of iVR process; it successfully exchanges required information between construction jobsite and office in a specific time. This system is expected to assist Engineers and workers in quality assessment, progress assessments, and decision-making which can realize a productive and practical communication platform, unlike conventional monitoring or data capturing, processing, and storage methods, which involve storage, compatibility, and time-consumption issues.

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A simulation method of three-dimensional cloud over WRF big data

EURASIP Journal on Wireless Communications and Networking ◽

10.1186/s13638-019-1584-0 ◽

2019 ◽

Vol 2019 (1) ◽

Author(s):

Yonghua Xie ◽

Xiaoyong Kou ◽

Ping Li

Keyword(s):

Real Time ◽

Particle System ◽

3D Visualization ◽

Human Life ◽

Experimental Simulation ◽

Spherical Particles ◽

Cloud Data ◽

The Impact ◽

New Particles ◽

Visualization Simulation

AbstractNowadays, due to the expansion of people’s living ranges and the impact of human life on the natural environment, climate changes fiercely than before. In order to observe the changing climate environment accurately, multi-modal sensors are used to collect the various data around us, and we could analyze and predict the weather based on these collected data. One of the applications is 3D visualization simulation, and the 3D visualization simulation of cloud data has always been the research hotspot in the field of computer graphics and meteorology. Currently, it is a key challenge to resolve the problems of 3D cloud simulation, such as reducing complexity of modeling and computation and improving the real-time performance. Technically, a method for data modeling and optimizing based on Weather Research and Forecasting (WRF) is proposed in this paper, aiming to solve the problems of the existing 3D cloud simulation and realize 3D virtual simulation of real-world cloud data. According to the characteristics (e.g., color, size, shape) of the cloud, the spherical particle system is designed to model, and the initial color, size, shape, and other attributes are given to these spherical particles to realize the modeling of WRF cloud data. From the perspective of new particles’ generation, the level of detail (LOD) technique, based on the relationship between the quantity of new generated spherical particles and the distance of the viewpoint, is used to change the quantity of new particles generated in real time according to the distance of the simulated scene distance. Finally, illumination model is introduced to render and simulate the modeling particles. Experimental simulation results verify the effectiveness of this method in improving the modeling and rendering speed of cloud data as well as the fidelity of the 3D virtualization model.

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The Impact of SearchTrails on the Quality of Collaborative Search

i-com ◽

10.1515/icom-2016-0041 ◽

2017 ◽

Vol 16 (1) ◽

pp. 3-14

Author(s):

Sebastian Franken ◽

Ulrich Norbisrath ◽

Wolfgang Prinz

Keyword(s):

Real Time ◽

Research Question ◽

Search Process ◽

Search Results ◽

Time Interaction ◽

Collaborative Search ◽

Search Processes ◽

The Impact ◽

The Given

AbstractSeveral collaborative search systems build upon real-time collaboration during search processes. With the software SearchTrails, we present a novel way of capturing and exchanging the search process between collaborators. We achieve this by asynchronously exchanging the newly developed search trails between collaborators and thus overcome the necessity of real-time interaction for search support. In a study with 29 participants, we evaluate the value of search trails as collaboration artifacts to answer the research question whether search trails improve the quality of collaborative search results. We confirm this and show that users can build upon work of co-searchers in a very efficient way by analyzing and extending the given search trails.

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The Calculation of TTR in PROFIBUS System

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.482-484.2183 ◽

2012 ◽

Vol 482-484 ◽

pp. 2183-2187 ◽

Cited By ~ 1

Author(s):

Li Ping Zhen ◽

Shao Wei Si ◽

Huan Qing Xie

Keyword(s):

Real Time ◽

Data Exchange ◽

Selection Method ◽

Time Behavior ◽

The Real ◽

Transmission Errors ◽

Random Behavior ◽

Token Passing ◽

Master Station ◽

The Impact

In PROFIBUS system, we analyzed the time behavior of data exchange and token-passing, and give the TTR selection method, when each master station holding enough token time. And then we discussed the random characteristics of networks and FDL, give the formula of random behavior to calculate time, and get the TTR and the revised value of TTR in PROFIBUS system which has FDL and MS1 communication. Finally, further discussed the case of transmission errors, analyzed the impact of transmission errors to TTR and the real-time of system, and give the TTR and the revised value in this situation.

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Technological Support of Real-Time Interaction in Web Clients of Analytical Fraud Detection Systems

KnE Social Sciences ◽

10.18502/kss.v3i2.1576 ◽

2018 ◽

Vol 3 (2) ◽

pp. 450

Author(s):

Radygin V.Y. ◽

Kupriyanov D. Yu

Keyword(s):

Real Time ◽

Data Exchange ◽

Fraud Detection ◽

Time Data ◽

Web Based ◽

Technological Support ◽

Detection Systems ◽

Time Interaction ◽

Client Software ◽

Detection Software

The optimal tools selection for design of web-based visual mining client for real time fraud detection systems was discussed. The features of modern real time fraud detection software were analyzed. The necessity of transition to using of web-based technologies for client software design was shown. The market of web-frameworks and browser to web-server data exchange technologies were investigated. Basing on experimental research the most efficient toolset for design of web-client software for real time fraud detection systems was offered. Keywords: fraud detection, Visual Mining, real time data exchange, web-visualization, webSockets, MessageBus.

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Real-time Augmented Reality Demo Platform for Exploring Consumer Emotional Responses with Shopping Applications

International Journal of Online and Biomedical Engineering (iJOE) ◽

10.3991/ijoe.v9is8.3379 ◽

2013 ◽

Vol 9 (S8) ◽

pp. 41 ◽

Cited By ~ 2

Author(s):

Jasmina Stoyanova ◽

Ricardo Gonçalves ◽

Pedro Quelhas Brito ◽

Antoniio Coelho

Keyword(s):

Augmented Reality ◽

Real Time ◽

Marketing Research ◽

Evaluation Process ◽

Physical World ◽

Interactive Systems ◽

3D Registration ◽

Time Interaction ◽

Consumer Experiences ◽

The Impact

The present-day revival of Augmented reality (AR) technology has led to its vast expansion in various applications. In marketing, the hunt for more inventive and intriguing approaches for immersive consumer experiences has endorsed the implementation of AR in multiple brand advertising campaigns, specifically for improved product display. The engaging potential of this technology is established in the fusion between computer-generated data and the physical world as seen by the user, where 3D registration and real time interaction are inseparable parts of this system. Alternatively, impressions from user experiences serve as a principal instrument in the evaluation process of the effectiveness of interactive systems. In order to get deeper insight into consumersâ?? reflections from a real-time AR shopping experience, we present a demo platform for the purchase of sneakers, focusing on usersâ?? behavior and more precisely on their perceptions, emotions, personal preferences before, during and after use of the platform. To fully evaluate and compare consumer experiences with the main AR platform, two other shopping systems were designed: a marker-based and a static one. Consecutively, we aim at defining a system of metrics for measuring shopping experiences with AR, as well as at establishing a ground base for subsequent marketing research in the field. Motivated by the large application of the technology and aiming at understanding the impact of AR on consumer psychology, the application will assist in exploring the antecedents of consumer purchase intentions.

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