Internet of Things and Advanced Digital Technologies
Specialization/Track "Internet of Things (IoT) and Advanced Digital Technologies"
The specialization "Internet of Things (IoT) and Advanced Digital Technologies" aims to educate and train scientists from various fields, but mainly from the domains of natural and technological sciences. It provides the necessary knowledge for the design, management, and support of new services on IoT platforms, the management of complex projects, equips students with the skills for designing and developing appropriate and innovative systems and services, analyzing big data, and provides the technical expertise in designing interdependent IoT systems connected to the functions of the digital city, smart homes, transportation, construction, energy, smart grids, smart health, smart agriculture, smart security, service provision, communications, smart digital infrastructure, education, smart security, development of governance systems, data security, protection of privacy and integrity of personal data, addressing cyber intrusions, protecting devices from attacks, and ensuring interoperability of systems and devices.
Who is the specialization "Internet of Things (IoT) and Advanced Digital Technologies" aimed at?
The specialization "Internet of Things (IoT) and Advanced Digital Technologies" - "Digital Culture, Smart Cities, IoT and Advanced Digital Technologies" within the M.Sc. (Master of Science) program accepts holders of a first-cycle degree from Greek or foreign universities, in accordance with the provisions of Law 4957/2022. The indicative list of eligible departments/schools includes Computer Science, Information and Communication Technologies, Computer Science, Electrical and Computer Engineering, Electronics and Computer Engineering, Information and Communication Systems Engineering, Computer Engineering and Computer Technology, Engineering Departments of Technological Education Institutes (TEIs), Polytechnic Schools, Departments of Digital Media, Sound & Image Arts, Cultural Technology & Communication, Cultural Management and New Technologies, TEI Schools, and other relevant disciplines related to the specialization. Graduates from Greek or foreign Universities, Polytechnic Schools, TEIs, or ASPETEs (Technological Education Institutes) of Greece, and graduates from foreign Universities are also eligible to apply (the above list is indicative and not binding) (for more information about each specialization/direction, you can contact the Secretariat of the MSc program, email: dcsciot@unipi.gr, tel: 210 4142451 (Monday to Friday, 12:00-14:00 & 16:00-18:00).
Master's Degrees
The M.Sc. program awards the Master's Degree (M.Sc.) with the title "Digital Culture, Smart Cities, IoT and Advanced Digital Technologies."
Course Program
The courses will start in October 2023. The teaching hours are from 18:00 to 21:00, four days a week.
Applications Interested individuals can submit their applications until October 30, 2023, electronically on the website http://www.cs.unipi.gr/registration/dicul.php and send their application and relevant documents to the Secretariat of the Postgraduate Studies Program (M.Sc.).
Cloud Computing, Content Delivery Networks, Agile and V2X Technologies
This course presents topics related to the study, design and implementation of modern distributed systems including cloud computing, content delivery networks and vehicular networks. The course offers a comprehensive study of key concepts related to distributed computing hardware and software. Emphasis is placed on the communication among the various components of the system as well as on task management, ontology naming and security. The course provides an in-depth examination of cloud computing architectures as well as emerging models that expand their capabilities (Network Function Virtualization - NFV, Software Defined Networking - SDN, Edge Cloud και Fog/Edge Computing). In addition, technologies and architectures of content delivery and vehicular networks will be studied. Relative composition models will be explored including heterogeneity, scaling, dynamic workflow representation techniques, quality assurance, classification of parameters and requirements, and fault tolerance techniques.
Learning Results
Professors
Name
Position
Office
Telephone
Email
Michalas Angelos
Professor in University of Western Macedonia
208/ΚΕKΤ
amichalas@unipi.gr
Skondras Emmanouil
Teaching Staff, Postdoctoral Researcher
208/ΚΕΚΤ
+30 210 4142458, +30 210 4142127, +30 210 4142060
skondras@unipi.gr
Papapanagiotou Stavros
Teaching Staff
104/ΓΛ126
+30 210 4142479
papapast@unipi.gr
Vergados Dimitrios
Professor
104/ΓΛ126
+30 210 4142479
vergados@unipi.gr
Data Analytics and Statistics
• Basic methods of clustering, categorization, and prediction. Inference and recommendation systems. Dimensionality reduction in large-scale data (Principal Component Analysis, Random Projections, Parallel Methods). Applications of large-scale data in various areas of daily life (World Wide Web, Social Media, Medicine, Smart Cities). Large-scale data visualization. Standards for Machine-Readable Data. Analysis of Open and Linked Data. Tools and Platforms for Big Data Management.
• Matrices, matrix operations, determinants, transpose and inverse of a matrix. Linear equations, methods for solving linear systems, Gauss elimination, Cramer's rule. Eigenvalues and eigenvectors. Probability theory, basic discrete and continuous random distributions.
• Data cleaning, transformation. Measures of similarity, distance. Linear and logistic regression. Introduction to the MATLAB program, programming in MATLAB. Introduction to R.
• Linear-multiple linear regression, logistic regression, inverse normal regression (Probit regression), analysis of variance (ANOVA-MANOVA). Exploratory factor analysis. The R language environment, syntax, basic structures and functions, applications in linear regression and logistic regression using R.
• Basic types of categorization. Statistical classification. Discriminant function analysis. Evaluation criteria for categorization methods. Data mining and advanced prediction techniques from databases. Applications of clustering and neural networks using MATLAB and R.
Learning Results
Professors
Name
Position
Office
Telephone
Email
Anagnostopoulos Ioannis
Professor in University of Thessaly
104/ΓΛ126
+30 210 4142479
janag@unipi.gr
Filippakis Michael
Professor
504/ΚΕΚΤ
+30 210 4142566
mfilip@unipi.gr
Tasoulas Ioannis
Assistant Professor
542/ΚΕΚΤ
+30 210 4142313
jtas@unipi.gr
Razis Gerasimos
Teaching Staff
104/ΓΛ126
+30 210 4142479
makisraz@unipi.gr
Mobile Applications, Edge Computing, Future Internet Network
The course introduces topics related to the design and development of mobile applications for smart city environments using Internet of Things (IoT) technologies (hardware and software), as well as programming in a cloud environment. Related apps within the area of Internet of Things include, but are not limited to: smart transport, smart cities, smart living, smart energy, smart health and smart learning. In addition, virtualization techniques of resources at the network edge involving Edge computing and fog computing are studied. Mobile Edge Computing (MEC) technology defines an innovative network architecture where cloud computing services are provided from the edge of the network, i.e. from smart base stations and network access points. The edge of the network is the part closest to the end user. Transferring the services to the edge, delays are reduced as the distance between the user and the service point is shorter. Further, design and development methodologies are discussed for 5G wireless networks, Ultra Dense Networks - UDN, Wireless Sensor Networks - WSN, Software Defined Networks – SDN and Vehicular Networks for smart cities environments.
Learning Results
On successful completion of this unit students will be able to: ● Identify the basic concept of wireless networks; Introduce various wireless systems and standards and their basic operation cases. ● Analyse traffic theories, mobile radio propagation, channel coding, and cellular concepts. ● Learn to model radio signal propagation issues and analyze their impact on communication system performance. ● Understand the techniques of radio spectrum allocation in multi-user systems and their impact on networks capacity. ● Compare and contrast multiple division techniques, mobile communication systems, and existing wireless networks. ● Classify network protocols, ad hoc and sensor networks, wireless MANs, LANs and PANs. ● Learn to simulate wireless networks and analyze the simulation results. ● Analyze and propose broad solutions for a range of mobile scenarios. ● To understand programming approaches for smart IoT devices. ● To understand personalization techniques for voice IoT devices. ● To understand virtualization. ● To implement virtualization. ● To analyze and design the modules needed for IoT programming using voice.
Professors
Name
Position
Office
Telephone
Email
Michalas Angelos
Professor in University of Western Macedonia
208/ΚΕKΤ
amichalas@unipi.gr
Skondras Emmanouil
Teaching Staff, Postdoctoral Researcher
208/ΚΕΚΤ
+30 210 4142458, +30 210 4142127, +30 210 4142060
skondras@unipi.gr
Alepis Efthimios
Associate Professor
540/ΚΕΚΤ
+30 210 4142311
talepis@unipi.gr
Sakkopoulos Evaggelos
Associate Professor
543/ΚΕΚΤ
+30 210 4142312
sakkopul@unipi.gr
Vergados Dimitrios
Professor
104/ΓΛ126
+30 210 4142479
vergados@unipi.gr
Entrepreneurship and Innovation, Administration of Smart Cities and Smart Regions - Green Transition
The objective of this course is to understand the new way of urban governance and management of "Smart Cities" through the utilization of digital technologies and the Internet of Things (IoT). Collaborations take place among industries, businesses, local authorities, and society, focusing on sustainable development, sustainable urban mobility, sustainable neighborhoods, sustainable built environment, technologies for energy, transportation, information, and communication infrastructure. The Internet of Things (IoT) and modern digital technologies, with the assistance of emerging businesses operating in this field, result in the enhancement of entrepreneurship, reduction of social inequalities in urban areas, reduction of unemployment, and the development of a new digital economy and modernization of public administration in collaboration with the private sector. Adopting innovative technological solutions contributes to the development of entrepreneurship by "controlling" the business through modern technological means. Through applications integrated into the Internet of Things, students will have the opportunity to recognize high-level specialized services for citizens and customers, with the ultimate goal of optimal information management.
Additionally, this course serves as an introduction to sustainable development and responsible innovation, particularly in the digital domain. It provides conceptual and empirical foundations for students to approach technology and entrepreneurship in their connections with environmental, social, and political factors. It familiarizes students with the practices and key issues surrounding the creation of new economic activities and the financing of such initiatives. Students will gain a deep understanding of the nature of innovations (smart technologies) in urban infrastructure systems. They will also learn and comprehend the most modern strategies that can be used for "smart infrastructure" solutions in cities while effectively managing the transition from older infrastructure to smart systems, supporting innovation and entrepreneurship in the process.
Learning Results
By the end of the course, students will be able to: ● Understand the key issues affecting finance decisions. ● Have a broad knowledge of issues related to the key goals, concepts, stakeholders, problems, decisions, variables, imitations and tools involved in the financial management of an organization managing cultural heritage. ● Prepare capital budgets, evaluate capital investment projects, and proceed to capital budgeting decisions. ● Identify the various financing options, sources and procedures that are available for funding Cultural Organizations and non-for-profit organizations. ● Prepare proposals for grants
Professors
Name
Position
Office
Telephone
Email
Siountri Konstantina
Teaching Staff
104/ΓΛ126
+30 210 4142479
ksiountri@unipi.gr
Psychogios Dimitrios
Associate Professor
319/Δεληγιώργη 107
+30 210 4142399
dpsycho@unipi.gr
Papapanagiotou Stavros
Teaching Staff
104/ΓΛ126
+30 210 4142479
papapast@unipi.gr
Vergados Dimitrios
Professor
104/ΓΛ126
+30 210 4142479
vergados@unipi.gr
Koronakos Gregory
Teaching Staff
Information Security of Public Services and Systems and Blockchain Technologies
The widespread use of technology, beyond simplifying and automating many of our daily tasks, exposes users and organizations to a multitude of risks. These risks can stem from various factors, such as flawed system architecture, incorrect configuration, or a lack of necessary control mechanisms. Within the framework of the course, real-world Public Service computing systems will be examined, focusing on common security issues and methodologies for their detection, both manually and using tools. Additionally, the course aims to identify fundamental security issues in web and mobile applications.
Given the need for decentralized and secure architectures in modern Public Service systems, the course will analyze Blockchain technologies, their security, their applications, as well as development platforms for such applications.
Learning Results
Application security vulnerabilities
Discovery of security vulnerabilities in web applications
Secure password storage
Hashing & encryption functions
Basic structural characteristics of Blockchains
Proof of Work
Proof of Stake
Applications of blockchains in various sectors
Tokenization
Writing Smart Contracts for Ethereum
Distributed storage space & Blockchains
IPFS
Professors
Name
Position
Office
Telephone
Email
Patsakis Constantinos
Associate Professor
540/ΚΕΚΤ
+30 210 4142261
kpatsak@unipi.gr
Thomas Dasaklis
Assistant Professor of Hellenic Open University
104/ΓΛ126
+30 210 4142479
dasaklis@unipi.gr
Vergados Dimitrios
Professor
104/ΓΛ126
+30 210 4142479
vergados@unipi.gr
Malamas Euaggelos
Teaching Staff
bagmalamas@unipi.gr
Software and Applications for IoT
The objective of this course is the development of applications that can be executed by modern IoT devices with an embedded operating system. These applications can be utilized within the context of smart homes, as well as in devices and equipment used by modern individuals, such as smartphones, and other smart devices that have emerged in recent years and utilize an operating system. IoT software includes, among others, software for computers, software for wearables, software for smart televisions, software for next-generation smart cars, as well as software for "Android Things" smart boards. This course analyzes the most popular IoT operating systems, as well as the development tools for applications on these systems. Additionally, software development methodologies and software development on cloud computing platforms are also examined.
Learning Results
Professors
Name
Position
Office
Telephone
Email
Michalas Angelos
Professor in University of Western Macedonia
208/ΚΕKΤ
amichalas@unipi.gr
Skondras Emmanouil
Teaching Staff, Postdoctoral Researcher
208/ΚΕΚΤ
+30 210 4142458, +30 210 4142127, +30 210 4142060
skondras@unipi.gr
Alepis Efthimios
Associate Professor
540/ΚΕΚΤ
+30 210 4142311
talepis@unipi.gr
Vergados J. Dimitrios
Associate Professor in University of Western Macedonia
104/ΓΛ126
+30 210 4142479
dvergados@unipi.gr
Stefanou Vasileia
Teaching Staff
104/ΓΛ126
+30 210 4142479
vstefanou@unipi.gr
Vergados Dimitrios
Professor
104/ΓΛ126
+30 210 4142479
vergados@unipi.gr
Tirovolas Dimitrios
Teaching Staff
104/ΓΛ126
+30 210 4142479
MSc Thesis
Learning Results
Professors
Name
Position
Office
Telephone
Email
Industry 4.0 and Smart Grids, M2M, IoT, Digital Twins
This course introduces the main challenges, solutions and application fields of machine-to-machine communications. As an emerging networking paradigm, machine-to-machine communications spans all communication processes that do not involve only humans and which are designed to pursue tasks of automation in the most general sense. This enables completely new application areas but introduces several novel and severe challenges, especially in the Smart Cities and IoT world. Many Issues have been addressed by research industry and by researchers over the last years and new standardization activities have initiated. This course deals with these new insights and technologies and related them to the new emerging application fields in IoT and smart cities. Indicatively, the course includes traditional automation systems, connected world and networking, Internet-of-things, smart grid, vehicular networks communications and application scenarios.
Also, this course M2M (Machine-to-Machine) includes drivers and benefits, business trends, relationship of M2M with Machine Learning and the IoT (Internet of Things), Machine Learning algorithms, M2M standardization efforts, M2M ecosystem and applications, M2M network infrastructure technologies, M2M network planning and implementation in Smart Cities, and other key topics.
Additionally, the course includes the following subjects: Fundamentals of Wireless Communications and Networking, Physical Modeling of Wireless Channels, Transmission Fundamentals, Multiple Access Techniques and Wireless Protocols, Channels’ Capacity. Next Generation Networks (NGN) and Applications, NGN Architectures, principal characteristics and platforms. Satellite Communications, DVB-T platform and DVB-S 2+, analysis and design of satellite links. Multihop networks. Wireless LAN, IEEE 802.11, and Ad-hoc/Wireless Sensor Networks (WSNs), Power Control and Energy Efficiency, Routing, Resource Allocation. M2M Communication Fundamentals. Requirements. Services. Application Examples. Information communication technologies. Wired transmission. Wireless transmission. Analysis of popular reference models, e.g., Lora, SigFox, LTE-M. Data Transfer protocols.
Learning Results
On successful completion of this unit students will be able to: ● Identify the basic concept of wireless networks; Introduce various wireless systems and standards and their basic operation cases. ● . Analyse traffic theories, mobile radio propagation, channel coding, and cellular concepts. ● Learn to model radio signal propagation issues and analyze their impact on communication system performance. ● Understand the techniques of radio spectrum allocation in multi-user systems and their impact on networks capacity. ● Compare and contrast multiple division techniques, mobile communication systems, and existing wireless networks. ● Classify network protocols, ad hoc and sensor networks, wireless MANs, LANs and PANs. ● Learn to simulate wireless networks and analyze the simulation results. ● Analyze and propose broad solutions for a range of mobile scenarios.
Professors
Name
Position
Office
Telephone
Email
Skondras Emmanouil
Teaching Staff, Postdoctoral Researcher
208/ΚΕΚΤ
+30 210 4142458, +30 210 4142127, +30 210 4142060
skondras@unipi.gr
Vergados J. Dimitrios
Associate Professor in University of Western Macedonia
104/ΓΛ126
+30 210 4142479
dvergados@unipi.gr
Sotiropoulos Dionisios
Assistant Professor
543/ΚΕΚΤ
+30 210 4142314
dsotirop@unipi.gr
Vergados Dimitrios
Professor
104/ΓΛ126
+30 210 4142479
vergados@unipi.gr
Miridakis Nikolaos
Assistant Professor in University of West Attica
104/ΓΛ126
+30 210 4142479
Tyrovolas Marios
Teaching Staff
Copyright, Personal Data and Regulatory Issues
The development of digital technologies, particularly the Internet of Things (IoT), raises a number of legal issues related to intellectual property law, privacy protection, consumer protection, free access to information, regulation of data rights (especially in the case of Big Data), as well as information security and cybercrime issues. This course examines all of the above and additionally explores the legal aspects of artificial intelligence, machine learning, blockchain technology, and smart contracts.
The purpose of this course is to enable students to identify and address the legal issues arising from the rapid development of digital technologies, particularly the new reality of the Internet of Things (IoT).
Learning Results
Upon completion, students are expected to be able to: ● Identify potential third-party rights infringement in the development of digital applications in the context of the Internet of Things and Advanced Digital Technologies ● Realize the legal boundaries in developing relevant applications ● Negotiate their position and responsibilities in the context of relevant actions ● Form their own opinion about the respective business strategies of private or public entities
Professors
Name
Position
Office
Telephone
Email
Vagena Evangelia
Teaching Staff, IT & IP Law Expert and lecturer, CIPP/E, vice president of HADPP
104/ΓΛ126
+30 210 4142479
evagena@unipi.gr
Vergados Dimitrios
Professor
104/ΓΛ126
+30 210 4142479
vergados@unipi.gr
Urban Design of Digital Cities
This course aims to create interdisciplinary teams of experts who can design innovative solutions to ensure the sustainability of future cities. We will explore technological trends and tools that support the digital transformation of our communities and delve into the environmental and social impacts that need to be considered when reimagining the future of a city.
Additional concepts covered in this course include: Basic Principles of Geographic Information Systems, Selection of Spatial Data Models (vector/raster depending on the nature of the study), fundamental concepts and cartographic techniques, basic principles of geographic database management systems, spatial analysis concepts and techniques, cartographic visualization of spatial data at regional and urban levels.
Learning Results
Upon completing this course, students are expected to be able to work on new principles of urban planning and digital feedback technologies that enable the creation of distributed and dynamic urban systems, significantly reducing resource consumption. They will learn that being "smart" does not necessarily imply the automation or artificial intelligence of these different systems but also refers to how designers, artists, theorists, engineers, and city officials approach the urban environment. They will understand that being "smart" in urban planning means understanding the economy, density, networks, social characteristics, and the unique profile of a place.
Additionally, students will be able to: ● Identify the fundamental concepts of geographic information systems. ● Analyze different spatial levels and scales and choose an appropriate spatial data model. ● Analyze demographic and general statistical data at the national/regional/district level and map them. ● Analyze data at the urban/urban planning level and map them. ● Formulate spatial queries and interpret their results.
Professors
Name
Position
Office
Telephone
Email
Siountri Konstantina
Teaching Staff
104/ΓΛ126
+30 210 4142479
ksiountri@unipi.gr
Vasilara Archontoula
Teaching Staff
104/ΓΛ126
+30 210 4142479
avasilara@unipi.gr
Tsigkas Epaminondas
Teaching Staff, Teaching and Research Staff (TRS) NTUA
104/Lam.126
+30 210 4142479
etsigkas@unipi.gr
Crowd Sourcing, Social Networking and Semantic Technologies
Introduction to Semantics, Knowledge and Data Management, Web Information Retrieval, Semantic protocols (RDF, RDF Schema, OWL, SPARQL). Semantic tools, Ontologies, Modern Search Engines, Web 3.0 Technologies, Text Analytics, Text mining and Sentiment Analysis on the Web and Social Networks, Collective Intelligence, Crowdsourcing.
