Safe Experimentation in Optical Levitation of Charged Droplets Using Remote Labs

Galán, Daniel; Isaksson, Oscar; Enger, Jonas; Rostedt, Mats; Johansson, Andreas; Hanstorp, Dag; Torre, Luís de la

doi:10.3791/58699

Cited by 4 publications

(1 citation statement)

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“…Previous researchers demonstrated various type of innovation in their remote learning. Galan D. et.al [7] have demonstrated the usefulness of conducting remote lab experiment for optical levitation that require proper setup to avoid harmful effect on the skin and eyes. Abreu P. et.al [8] have demonstrated the feasibility of performing experiments and monitoring pressure parameters of a pneumatic system that comprises of valve and pneumatic cylinder.…”

Section: Consideration Of Labview In Remote Laboratory Applicationmentioning

confidence: 99%

Cost-Effective Interfaces with Arduino-LabVIEW for an IOT-Based Remote Monitoring Application

Hairuddin¹,

Ashar²,

Abidin³

et al. 2021

LabVIEW - A Flexible Environment for Modeling and Daily Laboratory Use

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To date, research efforts have demonstrated the stimulated need for the Internet of Things (IoT) based monitoring device in their laboratory. The benefits of remote laboratories in overcoming time constraints and the disadvantages of usability of conventional laboratories are well known. In addition to the current control engineering laboratories, a remote lab that incorporates an industry-relevant method has been established to assist in the understanding of data acquisition with cost-effective platform integration. However, one of the greatest challenges is the creation of a low-cost and user-friendly remote laboratory experiment that is ideal for interacting with the actual laboratory via a mobile device. The main objective of this work is therefore to build a remote laboratory system based on the IoT using the LabVIEW-Arduino interface with the example of proportional-integral-derivative (PID) tuning scheme for the LD-Didactic temperature plant. The practical work would include the implementation of the low-cost Arduino module connecting the actual plant to mobile devices. In addition, interfaces have been built using the Blynk application to allow communication between the end user and the laboratory equipment. In line with the Industrial Revolution 4.0 (IR 4.0), the proposed study structure called for the digitization of the current laboratory experiment method.

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Section: Consideration Of Labview In Remote Laboratory Applicationmentioning

confidence: 99%

Cost-Effective Interfaces with Arduino-LabVIEW for an IOT-Based Remote Monitoring Application

Hairuddin¹,

Ashar²,

Abidin³

et al. 2021

LabVIEW - A Flexible Environment for Modeling and Daily Laboratory Use

View full text Add to dashboard Cite

show abstract

Teaching and Comprehensive Learning With Remote Laboratories and MATLAB for an Undergraduate System Identification Course

Lei

Zhou

et al. 2022

IEEE Trans. Educ.

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Automated training dataset collection system design for machine learning application in optical networks: an example of quality of transmission estimation

Fan

Zhou

et al. 2021

J. Opt. Commun. Netw.

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Applications of machine learning (ML) models in optical communications and networks have been extensively investigated. For an optical wavelength-division-multiplexing (WDM) system, the quality of transmission (QoT) estimation generally depends on many parameters including the number and arrangement of WDM channels; launch power of each channel; number and distribution of fiber spans; attenuation, dispersion, and nonlinearity parameters and length of each fiber span; noise figure; gain and gain tilt of erbium-doped fiber amplifiers; transceiver noise; digital signal processing (DSP) performance; and so on. In recent years, ML-based QoT estimation schemes have gained significant attention. However, nearly all relevant works are conducted through simulations because it is difficult to obtain sufficient and high-quality datasets for training ML models. In this paper, we demonstrate completely automated generation and collection of an ultra-large-scale experimental training dataset for ML-model-based QoT estimation by automation of transceivers and optical link parameters, as well as data transfer and DSP. Implementation details and key codes of automation are presented. Artificial neural network models with one and two hidden layers are trained by the collected dataset, and brief QoT estimation results are evaluated and discussed to verify the performance and stability of the established automated system.

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Safe Experimentation in Optical Levitation of Charged Droplets Using Remote Labs

Cited by 4 publications

References 0 publications

Cost-Effective Interfaces with Arduino-LabVIEW for an IOT-Based Remote Monitoring Application

Cost-Effective Interfaces with Arduino-LabVIEW for an IOT-Based Remote Monitoring Application

Teaching and Comprehensive Learning With Remote Laboratories and MATLAB for an Undergraduate System Identification Course

Automated training dataset collection system design for machine learning application in optical networks: an example of quality of transmission estimation

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