Editorial for JEC Volume 2 Issue 2 (2023)
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Abstract
This editorial presents innovative research at the intersection of edge computing and various disciplines, demonstrating the transformative potential of edge computing technologies. The issue includes a study on a digital Proportional-Integral-Derivative (PID) regulator model for controlling unmanned aerial vehicles, using digital filtering methods and a genetic algorithm; discusses an autonomous Internet of Things (IoT) system for monitoring classroom microclimates, contributing to the understanding of how microclimate parameters influence the physiological state of students; details the design and implementation of an educational model for a smart home, integrating various subsystems and renewable energy sources. This issue aims to inspire further exploration and innovation in edge computing, driving the field forward and opening up new possibilities for technology and society.
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Balyk, N., Leshchuk, S. and Yatsenyak, D., 2023. Design and implementation of an IoT-based educational model for smart homes: a STEM approach. Journal of Edge Computing, 2(2), pp.148–162. Available from: https://doi.org/10.55056/jec.632. DOI: https://doi.org/10.55056/jec.632
Klymenko, M.V. and Striuk, A.M., 2023. Design and implementation of an edge computingbased GPS tracking system. Journal of Edge Computing, 2(2), pp.175–189. Available from: https://doi.org/10.55056/jec.634. DOI: https://doi.org/10.55056/jec.634
Korenivska, O.L., Benedytskyi, V.B., Andreiev, O.V. and Medvediev, M.G., 2023. A system for monitoring the microclimate parameters of premises based on the Internet of Things and edge devices. Journal of Edge Computing, 2(2), pp.125–147. Available from: https://doi.org/10.55056/jec.614. DOI: https://doi.org/10.55056/jec.614
Petrosian, A.R., Petrosyan, R.V., Pilkevych, I.A. and Graf, M.S., 2023. Efficient model of PID controller of unmanned aerial vehicle. Journal of Edge Computing, 2(2), pp.104–124. Available from: https://doi.org/10.55056/jec.593. DOI: https://doi.org/10.55056/jec.593
Tkachuk, A.G., Hrynevych, M.S., Vakaliuk, T.A., Chernysh, O.A. and Medvediev, M.G., 2023. Edge computing in environmental science: an intelligent robotic platform for water quality assessment and reservoir bottom topography analysis. Journal of Edge Computing, 2(2), pp.163–174. Available from: https://doi.org/10.55056/jec.633. DOI: https://doi.org/10.55056/jec.633