IoT Devices Signals Processing Based on Shepard Local Approximation Operators Defined in Riesz MV-Algebras

Noje, Dan; Dzitac, Ioan; Pop, Nicolae; Tarca, Radu

doi:10.15388/20-INFOR395

Informatica

IoT Devices Signals Processing Based on Shepard Local Approximation Operators Defined in Riesz MV-Algebras

Volume 31, Issue 1 (2020), pp. 131–142

Dan Noje Ioan Dzitac Nicolae Pop Radu Tarca

https://doi.org/10.15388/20-INFOR395

Pub. online: 23 March 2020 Type: Research Article

Open Access

Received
1 November 2018

Accepted
1 October 2019

Published
23 March 2020

Abstract

The Industry 4.0 and smart city solutions are impossible to be implemented without using IoT devices. There can be several problems in acquiring data from these IoT devices, problems that can lead to missing values. Without a complete set of data, the automation of processes is not possible or is not satisfying enough. The aim of this paper is to introduce a new algorithm that can be used to fill in the missing values of signals sent by IoT devices. In order to do that, we introduce Shepard local approximation operators in Riesz MV-algebras for one variable function and we structure the set of possible values of the IoT devices signals as Riesz MV-algebra. Based on these local approximation operators we define a new algorithm and we test it to prove that it can be used to fill in the missing values of signals sent by IoT devices.

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Biographies

Noje Dan

dan.noje@primus-tech.ro

D. Noje received his BSc (eq.MSc) in mathematics and informatics (1996) and MSc in mathematics (1997) from University of Oradea. He was a lecturer at University of Oradea between 1996 and 2016. Since 2016 he is the head of Research Department of Primus Technologies SRL. His current research focus is on IoT, artificial inteligence, innovation and technology transfer. He has published 3 books and 25 scientific papers. He is a member of the EUSDR PA8 Working Group Innovation and Technology Transfer.

Dzitac Ioan

ioan@dzitac.ro

I. Dzitac received his BSc (eq.MSc) in mathematics (1977) and PhD in information sciences (2002) from Babes-Bolyai University of Cluj-Napoca. In 2019 he has defended his Habilitation Thesis “Soft Computing for Decision Making” at Alexandru Ioan Cuza University of Iasi. He is a mathematics and information sciences professor at Agora University of Oradea (since 2017) and at Aurel Vlaicu University of Arad (since 2009). Also he is a PhD supervisor at University of Craiova. He was an adjunct professor at University of Chinese Academy of Sciences, Beijing, China (2013–2016) and since 2016 he is an advisory board member at Graduate School of Management of Technology, Hoseo University, South Korea. His current research interests include different aspects of artificial intelligence, soft computing and applications of fuzzy logic in economy (decision making, quantitative management, qualitative management, e-learning platforms management, etc.). He is a senior member of IEEE (since 2011), member of Publication Committee of International Academy of Information Technology and Quantitative Management (IAITQM, since 2014), etc. He was an invited/tutorial speaker and/or invited special sessions’ organizer and chairman in China (2013: Beijing, Suzhou and Chengdu, 2015: Dalian, 2016: Beijing), India (2014: Madurai, 2017: Delhi), Russia (2014: Moscow), Brazil (2015: Rio), Lithuania (2015: Druskininkai), South Korea (2016: Asan), USA (2018: Nebraska). He has published 3 books, 12 courses and materials for students, 6 proceedings and more than 80 scientific papers in journals and conferences’ proceedings (over 40 in ISI Web of Science indexed journals with over 200 citations). In Google Scholar he has over 510 citations.

Pop Nicolae

nicpop@gmail.com

N. Pop received his BSc (eq.MSc) in mathematics (1973) from West University of Timisoara, Romania and PhD in mathematics (1997) from Babes-Balyai University of Cluj-Napoca, Romania. In 2016 he has defended his habilitation thesis at School of Advanced Studies of the Romanian Academy, Bucharest. He is a professor emeritus Dr. at North University Center, Baia Mare, in Technical University of Cluj-Napoca, Romania, and a senior researcher at the Institute of Solid Mechanics of the Romanian Academy, Bucharest, Department of Robotics & Mechatronics. He is a specialist in variational analysis and numerical methods for frictional contact problems in elasticity and in solving partial differential equations; in methods control in dynamic systems and piecewise-smooth dynamical systems with friction, with applications in robotics; in stability, balance, optimal control and tracking of mobile robot trajectories; in advanced robotics intelligent control research and solid mechanics integrated into the versatile, intelligent, and portable robot platform. He has published many research papers and books that have an international reputation.

Tarca Radu

rtarca@uoradea.ro

R. Tarca received his BSc (eq.MSc) “cum laudae” in mechanical engineering (1992) from Technical University of Cluj Napoca, and Bachelor in Economics from University of Oradea. He received his PhD title “cum laudae” in robotics (2001) from University Politehnica Timisoara. He received his professor title in robotics in 2004. From 2004 to 2016, he was the head of Mechatronics Department, and from 2008 he is a Co-Chairholder of the UNESCO chair in Information Technologies at the University of Oradea. He is the director of the “PRODUCTICA IMT” Research Centre since 2007. Currently he is the director of the council for doctoral studies at the University of Oradea. He has published over 150 papers in international journals and conferences’ proceedings and he has coordinated seven national and international grants as a project manager. His current research interests include aspects related to robotics, sensors and artificial intelligence.

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Keywords

IoT devices signal processing Shepard local approximation operators local approximation operators approximation algorithms Riesz MV-algebras vectorial MV-algebras

Funding

This research was funded by UEFISCDI Romania, grant number 198PED /2017, grant code: PN-III-P2-2.1-PED-2016-1955. With this grant, a new fiber optic Bragg grating sensor system designed to monitor the ethanol fermentation during the bioethanol and wine production was developed.

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