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Tutorials Speakers of SETIT 2022

Prof. Stefano Rovetta

Genoa, Italy

Title: Optimisation in Computational Intelligence

Abstract: One key component of virtually all machine learning methods is optimization of some objective function. Recent methods like deep neural networks require the solution of very large problems, and there is a host of techniques that has been developed for this purpose, both with solid theoretical ground and out of hands-on experience. However, there is more to computational intelligence than just neural networks.

Stefano Rovetta is currently an Associate Professor of computer science with the University of Genova, Italy, as a member of the Department of Informatics, Bioengineering Robotics, and Systems Engineering (DIBRIS). He has authored more than 180 scientific articles in machine learning, neural networks, clustering, fuzzy systems, and bioinformatics. Chair of organiser of international conferences, including the main Italian conferences on fuzzy logic (WILF) and neural networks (WIRN). He is a member of the Italian Neural Network Society, the European Neural Network Society, and the European Society for Fuzzy Logic and Technology. Recipient of the 2008 Pattern Recognition Society Award.

Prof. Valeriu Beiu


Title: The Race for Mighty AI Chips

Abstract: This tutorial-style presentation will start with a historic overview of Artificial Intelligence (AI), shortly going over the earlier AI waves. The focus will be on the rapid rise of AI in the last decade, narrowing it down to Deep Learning, perceived as an ubiquitous solution for a plethora of applications. This trend was/is stimulated by massive financial support and flourishing on the growth of plenty of custom AI chips. The fast pace rising start-ups in these deceptively esoteric fields will be identified, and their latest results surveyed. Currently, a key ingredient, besides new designs, is extreme ultraviolet lithography EUVL (Extreme_ultraviolet_lithography)— at the heart of fabricating the most advanced few-nanometer integrated circuits (powering cloud, fog, and edge AI & IoT, and most probably quantum computing as well). We will mention some of the technical problems faced, and go over the latest solutions (some landing the German Future Prize in Fall 2020). All of these pinpoint to a monopolistic growth potential revealing extremely stringent financial and technological constraints. Finally, we will conclude by commenting on the forthcoming growth potential of AI hardware in the wider context of rebooting and quantum computing, as seen through the expected demise of Moore’s law.

Valeriu Beiu (S’92–M’95–SM’96) received the MSc in Computer Engineering from the University “Politehnica” Bucharest in 1980, and the PhD summa cum laude in Electrical Engineering from the Katholieke Universiteit Leuven in 1994. Since graduating in 1980 he has been with the Research Institute for Computer Techniques, “Politehnica” University of Bucharest, Katholieke Universiteit Leuven, King’s College London, Los Alamos National Laboratory, Rose Research, Washington State University, United Arab Emirates University, and currently is with the “Aurel Vlaicu” University of Arad. His research interests have constantly been on biological-/neural-inspired circuits and brain-inspired architectures (low-power, highly reliable, massively parallel), being funded at over US$ 50M, while publishing close to 300 papers (over 50 invited and more than 10 patents) and giving over 220 invited talks as well as organizing over 130 conferences. Dr. Beiu has received five fellowships and nine best paper awards, and is a Senior Member of the IEEE as well as a member of: ACM, INNS, ENNS, and MCFA. He was a member of the SRC-NNI Working Group on Novel Nano-architectures, the IEEE CS Task Force on Nano-architectures, and the IEEE Emerging Technologies Group on Nanoscale Communications, and has been an Associate Editor of the IEEE Transactions on Neural Networks (2005–2008), the IEEE Transactions for Very Large Scale Integration Systems (2011–2015), and the Nano Communication Networks (2010–2016), while since 2020 is on the Editorial Board of Mathematics (MDPI) and Applied Sciences (Springer). In 2021, based on his entire career record, he was included in the list of “top 2% scientists in his field” by Stanford/Scopus.


Ninevah, Iraq

Title: From Fractal Nature to Communication Engineering

In various places of nature, we see certain patterns that repeat themselves after some scaling in size and placement or rotation. These patterns have been studied and modeled by fractal geometries like the Cantor, Koch, Peano, and Sierpinski. There, a certain dimension or angle of the object shape that is being repeated is expressed by a certain mathematical formula that shows the relation between the repeated shapes. On the other hand, some new shapes exhibiting scaling, repetition, and filling have been generated with the help of computer graphics, thus achieving much more complex shapes. The lecture will discuss fractals in nature, former trials to model them, and the mathematical relations that generate new shapes. The lecture will then emphasize the use of fractals in communication engineering. Of special interest is the use of the fractal concept in the design of antennas. It will be shown how the two features of the fractals, scaling and repetition are employed to design wideband antennas and filters. It also aims to propose new fractal concepts that offer flexibility in the design of antennas. A challenge is raised for developing new uses of fractal geometries in the general field of communication engineering.

Prof Khalil Sayidmarie received his B.Sc. degree in Electronics & Communication Eng. from Mosul University, Iraq, in 1976, and his Ph.D. Degree from Sheffield University, UK in 1981. Then he joined the College of Engineering at Mosul University in 1983 and was promoted to full Professor in 1992. Previously he worked as the head of the electrical engineering department/ University of Mosul for 9 years, manager of the engineering consulting bureau for 5 years, and acting dean of the College of Electronics Engineering at Mosul University 2002-2003. Sayidmarie worked as Prof. of communication engineering at the College of Engineering, University of Amman / Jordan from Oct 2006 to Sept 2009, where he was dean of the Faculty of Engineering for the academic year 2008-2009. Sayidmarie has been a Prof. of communication engineering at the college of electronic engineering/ Ninevah University from 2002 till his retirement in 2021 when he moved to the rank of Emeritus Professor. He was a recipient of two research scholarships from the Australian Endeavour in 2007 and in 2018, both spent at the ITEE/University of Queensland/ Australia. He was a visiting professor for one month at Bradford University/UK in 2013. Sayidmarie holds four Iraqi patents and has authored five book chapters. His research interests cover antennas, propagation, and microwaves, where he has published more than 140 papers in international refereed journals and conferences. He has supervised 43 Ph.D. and M.Sc. theses.

Prof. Francesco Masulli

University of Genoa,Italy

Title: Short Term Urban Traffic Flow Forecasting: An Approach Exploiting Computational Intelligence Methods.

We introduce the Layered Ensemble Model which combines Graded Possibilistic Clustering model and ensemble of Artificial Neural Network predictors, obtaining in such a way an accurate forecaster of the traffic flow rates with outlier detection. Experimentation has been carried out on two different data sets. The former consists on real UK motorway data and the latter is obtained from simulated traffic flow of a street network in Genoa (Italy). The proposed model for short-term traffic forecasting provides promising results and given its characteristics of outlier detection, accuracy, and robustness can be fruitful integrated in traffic flow management systems, allowing the local administration to streamline the traffic and reduce traveling time. This will lead to significant energy savings, less pollution, and a better quality of life of the population.

Francesco Masulli is the Chair of IEEE Italy Section Computational Intelligence Society Chapter, a Full Professor of Computer Science with the University of Genoa (Italy), an Adjunct Professor at the Center for Biotechnology of the Temple University in Philadelphia (PA, USA), and a founding partner of the innovative start-up company Vega Research Laboratories s.r.l.s. He was a visiting professor at the International Computer Science Institute in Berkeley (CA-USA) and at the I3S Labs-University of Nice Sophia-Antipolis (France). He received the 2008 Pattern Recognition Society Award and was the chair of several international conferences and Ph.D courses and author of more than 200 scientific papers in Clustering, Machine Learning, Neural Networks, Fuzzy Systems and Bioinformatics.

Prof. Alexander Makarenko

Institute of Applied System Analysis at National Technical University of Ukraine (I. Sykorski KPI), Ukraine

Title: Cellular Automata. Some New Algirithms, Tools, Applications and Anticipation Accounting.

New generalizations of cellular automata are proposed. Cellular automata had been considered in the restricted regions of space. The cases of external and internal boundaries ware considered. Special rules for cells near boundaries are proposed. Special rules for cells near the boundaries are proposed for gliders. The concepts for modeling logical gates are proposed. For the implementation of logical gates the propagation of the gliders of cellular automata in bounded domain is proposed. Special rools for collisions of gliders with walls and obstacles are proposed. The realization of logical operations ‘AND’, ‘ÓR’, ‘NOT’, ‘XOR’. Cellular automata on Riemann surfaces are described. Also it is considered the general formulations and properties of cellular automata with cells which have the strong anticipatory property (introduced by D. Dubois). Multivalued behavior (hyperincursion) of solutions of such CA is describe. It was posed new research problems of computation theory related to presumable multivaluedness of cellular automata with strong anticipation property. Extending of classical automata, Turing machine and algorithms had been proposed. Also some relation of such cellular automata and quantum mechanics are discussed. Two-Slit computer experiments with cellular automata with strong anticipation are considered. Some applications of cellular automata are described: football; migration on science and high education; epidemic spreading; artificial life.

Professor, Dr, Alexander Makarenko graduated from Moscow Phisico-Tecgnical Institute. He has completed his Dr. degree from Institute of Cybernetic, Ukraine. He is specialist in AI, system analysis, mathematical modeling and systems with anticipation. He is the Head of Applied Nonlinear Analysis at Institute of Applied System Analysis Department of National Technical University of Ukraine (I. Sykorski KPI), a premier research and educational organization. He has published more than 100 papers in reputed journals and has been serving as an editorial boards member.

Prof. Reda Reda


Title: Next Generatinon Artificial Intelligence and Machine Learning. Expected Impact on the Industry, Research and the Global Economy

Abstract :
Numerous aspects of modern technology have only become realistic as a result of the rapid development of the disciplines Artificial Intelligence and Machine Learning. These two disciplines are expected in the near future to dominate many aspect/process of our day-to-day life. First, this tutorial will introduce key aspects of artificial intelligence and computer systems able to solve complex problems, such as intelligent search algorithms, mathematical optimization and evolutionary computation. Subsequently, the concepts of autonomous vehicles, energy storage and robots will be introduced. Second, we zoom in on the Machine Learning as subset of Artificial Intelligennce. We discussed supervised, unsupervised and reinforced learning, as well as communication networks applications. Furthermore, the feature „next product to buy“ as a smart application will be introduced. Last but not least, a brief overview of the two disceplines in the near future will be introduced, focusing on super inteligence, disease cure, high-level creativity and communication networks performance. Finally, a representative example will be presented that employs Artificial Intelligence to enable an automated manufacture and production of software-defined computer networks (SDN) demonstrating a revolutionary development of High-Tech networks. As an overall result, the micro, macro, and global economies are expected to grow significantly.

Biography :
Dr. Reda Started his career in Europe working as R&D engineer, promoted to team leader, project manager, marketing manager and marketing director within an enterprise of 450.000 employees worldwide. In 2005 he established his own company “Innovation Communication Technologies” with core business as future, market-oriented next generation technologies and market researches. From the Academic point of view, Dr. Reda worked as guest professor / tutor in Cairo University, UCLA, Belarus Academy of Public Administration and several European Universities. In addition, Dr. Reda acted/is acting as senior consultant for a number of international organizations e.g. EU Commision, the Information and Decision Support Center IDSC of of the Egyptian Government, UAE project MASADAR. Dr. Reda chaired/ acted as keynote speaker in a numerous conferences of International Organisations e.g. IEEE; IARIA, IASTEAD and IFIP. Meanwhile Dr. Reda has more than 50 Publications.

Prof. Johan Debayle


Title: Digital twins for image and video analysis of granulats media

Abstract: Granular media are widely used in many industrial applications and fields of science from physics to chemistry, biology or agronomy. In energy, power and chemical engineering systems, in particular, it is generally desired to extract information on geometrical characteristics and on spatial distribution from 2D images of the population of particles/grains involved in the process. For example in pharmaceutics, the size and the shape of crystals of active ingredients are known to have a considerable impact on the final quality of products, such as drugs. As another example, the performance of fuel cells (SOFC/SOEC) is mainly related to the electrode microstructure (size and spatial distribution of the solid and porous phase). The purpose of this talk is then to show different ways (deterministic and stochastic methods using digital twins) of image processing, analysis and modeling to geometrically characterize such granular media from 2-D or 3-D images/videos. The developed methods will be presented by addressing different issues: overlapping, projection, blur... The methods are mainly based on image enhancement, restoration, segmentation, tracking, modeling, feature detection, stereology, stochastic geometry, pattern recognition and machine learning. The methods will be particularly illustrated on real applications of crystallization processes (for pharmaceutics industry), multiphase flow processes (for nuclear industry). and fuel cell power systems (for energy industry).

Johan Debayle received his M.Sc., Ph.D. and Habilitation degrees in the field of image processing and analysis, in 2002, 2005 and 2012 respectively. Currently, he is a Full Professor at the Ecole Nationale Supérieure des Mines de Saint-Etienne (MINES Saint-Etienne) in France, within the SPIN Center and the LGF Laboratory, UMR CNRS 5307, where he leads the PMDM Department interested in image analysis of granular media. He is also the Deputy Director of the MORPHEA CNRS GDR 2021 Research Group. He is the Head of the Master of Science in Mathematical Imaging and Spatial Pattern Analysis (MISPA) at MINES Saint-Etienne. His research interests include image processing and analysis, pattern recognition and stochastic geometry. He published more than 170 international papers in international journals and conference proceedings. He has been invited to give a keynote talk in several international conferences. He is the General Chair of the international conferences ISIVC’2020, ICIVP’2021, ICMV’2021, ECSIA’2021, ISIVC’2022, ICPRS’2022 and served as Program committee member in several international conferences. He is Associate Editor for 6 international journals: Pattern Recognition Letters (PRL), Pattern Analysis and Applications (Springer), Journal of Electronic Imaging (SPIE), Journal of Imaging (MDPI), IET Image Processing (IET-Wiley) and Image Analysis and Stereology (ISSIA). He is a Fellow of the Institution of Engineering and Technology (IET), Fellow of the International Association for Computer Science and Information Technology, Member of the International Society for Optics and Photonics (SPIE), International Association for Pattern Recognition (IAPR), International Society for Stereology and Image Analysis (ISSIA), Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and Vice-Chair Membership of IEEE France Section. More information can be found at:

Prof. Deepak Gupta

Maharaja Agrasen Institute of Technology, India

Title: Deep Learning and its applications in Natural Language Processing

Within the field of machine learning, deep learning approaches have resulted in state-of-the-art accuracy in natural language processing. Deep learning techniques hold the promise of emerging technologies. This tutorial is divided into two parts. First, we provide intuitive insights into artificial intelligence, machine learning and focusses mainly on deep learning models and show their applications in natural language processing. We then discuss two case studies on NLP viz BloomNet: A Robust Transformer based model for Bloom’s Learning Outcome Classification and CatBoost: An Ensemble Machine Learning Model for Prediction and Classification of Student Academic Performance.

Prof Deepak Gupta received a B.Tech. degree in 2006 from the Guru Gobind Singh Indraprastha University, Delhi, India. He received M.E. degree in 2010 from Delhi Technological University, India and Ph. D. degree in 2017 from Dr. APJ Abdul Kalam Technical University (AKTU), Lucknow, India. He has completed his Post-Doc from National Institute of Telecommunications (Inatel), Brazil in 2018. He has co-authored more than 192 journal articles including 153 SCI papers and 53 conference articles. He has authored/edited 63 books, published by IEEE-Wiley, Elsevier, Springer, Wiley, CRC Press, DeGruyter and Katsons. He has filled four Indian patents. He is convener of ICICC, ICDAM & DoSCI Springer conferences series. Currently he is Associate Editor of Alexandria Engineering Journal (Elsevier), Computer & Electrical Engineering Journal (Elsevier), Expert Systems (Wiley), and Intelligent Decision Technologies (IOS Press). He is the recipient of 2021 IEEE System Council Best Paper Award. He have been featured in the list of top 2% scientist/researcher database in the world since the last two years. In India, Rank 1 as a researcher in the field of healthcare applications (as per Google Scholar citation) and Ranked #78 in India among Top Scientists 2022 by He is also working towards promoting Startups and also serving as a Startup Consultant. He is also a series editor of “Elsevier Biomedical Engineering” at Academic Press, Elsevier, “Intelligent Biomedical Data Analysis” at De Gruyter, Germany, “Explainable AI (XAI) for Engineering Applications” at CRC Press. He is appointed as Consulting Editor at Elsevier. Accomplished productive collaborative research with grants of approximately $24000 from various international funding agencies and he is Co-PI in an International Indo-Russian Joint project of Rs 1.31CR from Department of Science and Technology.

Prof. Pascal Lorenz

University of Haute-Alsace, France, France

Title: Advanced architectures of Next Generation Wireless Networks

Internet Quality of Service (QoS) mechanisms are expected to enable wide spread use of real time services. New standards and new communication architectures allowing guaranteed QoS services are now developed. We will cover the issues of QoS provisioning in heterogeneous networks, Internet access over 5G networks and discusses most emerging technologies in the area of networks and telecommunications such as IoT, SDN, Edge Computing and MEC networking. We will also present routing, security, baseline architectures of the inter-networking protocols and end-to-end traffic management issues.

Pascal Lorenz received his M.Sc. (1990) and Ph.D. (1994) from the University of Nancy, France. Between 1990 and 1995 he was a research engineer at WorldFIP Europe and at Alcatel-Alsthom. He is a professor at the University of Haute-Alsace, France, since 1995. His research interests include QoS, wireless networks and high-speed networks. He is the author/co-author of 3 books, 3 patents and 200 international publications in refereed journals and conferences. He was Technical Editor of the IEEE Communications Magazine Editorial Board (2000-2006), IEEE Networks Magazine since 2015, IEEE Transactions on Vehicular Technology since 2017, Chair of IEEE ComSoc France (2014-2020), Financial chair of IEEE France (2017-2022), Chair of Vertical Issues in Communication Systems Technical Committee Cluster (2008-2009), Chair of the Communications Systems Integration and Modeling Technical Committee (2003-2009), Chair of the Communications Software Technical Committee (2008-2010) and Chair of the Technical Committee on Information Infrastructure and Networking (2016-2017). He has served as Co-Program Chair of IEEE WCNC'2012 and ICC'2004, Executive Vice-Chair of ICC'2017, TPC Vice Chair of Globecom'2018, Panel sessions co-chair for Globecom'16, tutorial chair of VTC'2013 Spring and WCNC'2010, track chair of PIMRC'2012 and WCNC'2014, symposium Co-Chair at Globecom 2007-2011, Globecom'2019, ICC 2008-2010, ICC'2014 and '2016. He has served as Co-Guest Editor for special issues of IEEE Communications Magazine, Networks Magazine, Wireless Communications Magazine, Telecommunications Systems and LNCS. He is associate Editor for International Journal of Communication Systems (IJCS-Wiley), Journal on Security and Communication Networks (SCN-Wiley) and International Journal of Business Data Communications and Networking, Journal of Network and Computer Applications (JNCA-Elsevier). He is senior member of the IEEE, IARIA fellow and member of many international program committees. He has organized many conferences, chaired several technical sessions and gave tutorials at major international conferences. He was IEEE ComSoc Distinguished Lecturer Tour during 2013-2014.

Prof. Adriana Burlea-Schiopoiu

University of Craiova, Romania

Title: Dispersal of information and digital technology: a disruptive challenging relationship

Since the beginning of 2020, people, organizations, and governments worldwide have faced several challenges. We ask if we can speak about the circular effects of rapid technological evolution on human behavior. The coronavirus outbreak crisis has disrupted what we all referred to as a ‘normality’ in our daily lives and perturbed the entire world economy. What will the ‘normality’ look like after this challenging time? It is not easy to find answers to this question, and for this reason, we will put into value the importance of the DISPERSAL OF INFORMATION in the relationship between digital technology and human behavior which the coronavirus pandemic has seriously influenced. Finding solutions to this challenge is the purpose of any researchers and practitioners, regardless of their field of interest. All together are seeking solutions to fight against this invisible enemy and re-open the ‘REAL LIFE’ of the people.

Prof. Adriana Burlea-Schiopoiu is a professor of Management at the University of Craiova, Romania, Romanian ambassador for ARGH (Association Francophone de Gestion des Ressources Humaines; President of the Regional Commission of Experts (CRE) - Central and Eastern Europe -, President of the AIS SIG – Cognitive Analytics Management (SIGCAM), Member of the Scientific Council of the University Agency of the Francophonie (AUF) -; Head of Cyber-Security Branch – Scientific Innovation Research Group (SIRG); Member of the Directors Board of Doctoral School of the University of Craiova - She is a professor teaching and research in Human Resources Management, Project Management, Social Audit, Corporate Social Responsibility, and Negotiation Techniques at the University of Craiova, Faculty of Economics and Business Administration in Romania. She was visiting Professor teaching and research in Cross-Cultural Management, Human Resources Management, Intercultural Management at universities in France, Poland, and Latvia. Professor Adriana Burlea-Schiopoiu was invited as the keynote speaker for many international conferences in France, Portugal, Albania, Lebanon, India, Indonesia, Iraq, and Turkey. She is a member of many organizing committees of the national and international journals and conferences. She stimulated and encouraged the cooperation between her university and the other universities around the world (for example, cooperation with staff and teachers from other International Universities in various scientific projects – For example, universities from France, USA, UK, Swiss, Belgium, Italy, Portugal, Norway, and Holland). She published in prestigious journals, for example, Journal of Cleaner Production, Corporate Social Responsibility, Environmental Management, International Journal of Finance & Economics, Socio-economic Planning Sciences, and International Journal of Environmental Research and Public Health.

Prof. Robert Laurini


Title: Structuring a geographic knowledge base

For any territory, knowledge corresponds to information potentially useful to (i) explain and make understandable its internal dynamics as well as its interactions with other adjoining regions in the same or neighboring countries; (ii) manage a region by some local authorities, i.e. by means of some decision-support system, in the spirit of territorial intelligence; (iii) to monitor its daily development through feedbacks and adaptation; (iv) to simulate the future, and design novel projects; and (v) to orient actions for the future. As a consequence, any knowledge base must include the following components (i) geographic objects with their toponyms, characteristics and geometry; (ii) an ontology regrouping types together with topological relations; (iii) a gazetteer regrouping the various names of a place; (iv) some physico-mathematical models, for instance to simulate pollution diffusion; (v) external knowledge which can be an influence over the territory dynamics; and finally (v) rules to articulate all the previous components by mixing logics and computational geometry. In addition, we will show how designed geographic objects of any urban or environmental project will progressively become real objects.

After graduating in electronic engineering in 1970, he received two doctorates (1973, 1980) from INSA (University of Lyon,) France, institution which he practically made his whole carrier as professor in information technology and as a specialist in Geographic Information Systems. He worked also in other various universities, in Italy, in UK, in USA, in Mexico and Argentina. He wrote more than 250 papers and wrote 9 books; the last one, published in 2017 is entitled “Geographic Knowledge Infrastructure: Applications to Territorial Intelligence and Smart Cities”. Presently, he is Professor Emeritus at the Knowledge Systems Institute, USA, and president of the NGO “Universitaires Sans Frontières-Academics Without Borders” the goal of which is to help universities in developing countries. Website:


University of Technology of Belfort Montbéliard,France

Title: Application of machine learning techniques for personalized and predictive remote monitoring

The Big Tech advocate the use of science to overcome the biological limits of the human body. This new world with technology, where science evolves every day to compensate the deficits of the human body, this new world will most certainly end up creating post-humans: improved men with increased capacities and life expectancy almost infinite. Man is clearly tempted to take power over the environment and over himself. We have ultra-powerful machines, IoT for data collection, storage capacity and of course algorithms, that is to say artificial intelligence. This artificial intelligence can indeed let us believe that man can take power over the environment and over himself. In recent years, machine learning has become an important solution in the healthcare industry. It allows us today to predict a decompensation several days before its occurrence and this is a reality today.

Amir HAJJAM EL HASSANI is Deputy Director of Nanomedecine, Imagerie, Therapeutique of Université de Franche Comté (UFC) and Research Team Leader of Health Systems Organization. His research areas include data mining and machine learning for decision support in the field of e-Health. He is Editorial Board Member of four international journals and the author/co-author of 3 books and has more than 200 archival publications to his credit in high impact factor journals and international conferences. He was Co-Chair of the first international conference eTelemed'09 and is its advisory Chair since 2010. He is member of the Science Steering Committee of the annual conferences IADIS e-Health, eHealth, e-Medisys, etc. He has organised many conferences and chaired several technical sessions. He also acts as an expert to the ANR France, ARI France and CNRST Morocco. Amir is the head of IT Engineer Training under Apprentice status at Université de Technologie de Belfort Montbéliard,France.

Prof. Christos Liambas


Title: Smart Sensing Train

The problem of safe transportation by using trains is a global challenge, where has been a significant increase in accidents with undesirable consequences (human losses) and damaging effects. Under this framework, the proposed study concerns the development of an optimization algorithm by analyzing collected data of an IoT device with LIDAR distance sensors (time-of-flight sensor can measure up to 300 meters to natural surfaces and up to 3,000 meters when using a retroreflective target), which is installed on the train’s engine, in order to detect obstacles such as cars, rocks from landslides, tree trunks, etc., aiming to automatically activate the train’s braking system. Thus, the algorithm compares the already measured distances (which are stored in a database) and the new measurements by the same sensors on the exact same routes (where the initial measurements had been stored), in order to detect the differences between them (shorter distances) and minimizes the reaction time for the activation of the braking system. Also, it should be noted that the initial approach was developed by using LEGO Mindstorms EV3 set (with an ultrasonic distance sensor), which was presented as an innovative project idea in the First LEGO League 2022 robotics competition.

Prof. Christos Liambas is an expert in Optimization Algorithms, Signal Processing (Image and Video), and Digital Forensics as an invited Professor at the Ecole Nationale Supérieure des Télécommunications de Bretagne (French Engineering Academy), invited Professor at the University of Sfax (Tunisia), associate Lecturer at the University of East London (UK) and Programme Leader of Faculty of Computing (Greece) at the Metropolitan College, member of many international scientific committees, and also he served as Professional Member and Mentor at the Academy of Sciences (NY-USA). The originality and technical expertise of his scientific work is reflected through international distinctions (SETIT-IEEE-ISECS and SIAM/SIMAI) received in 2008, 2009, and 2019, where his research has been funded by the Greek Ministry of Education as well as by the European Commission. Also, he is a Digital Forensics Expert at the Greek Courts of Justice. Finally, the research team members for the above-mentioned research under the title “Smart Sensing Train” are Mr. Stavros Barberis, Mr. Konstantinos Chatzigeorgiou, Mr. Andreas Kaplanis, Ms. Elpida Sikalidou, and Ms. Evdoxia Vasileiou-Avgoustoglou (students of Mandoulides School).