studies
M.Sc. in "Digital Culture, Smart Cities, IoT and Advanced Digital Technologies"
Smart Cities and Advanced Digital Technologies
Obligatory Courses
1st semester
Cloud Computing, Content Delivery Networks and Vehicular Technologies
The 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.
302, Central Building
+30 210 4142137
fax +30 210 4142472
Professor
104/Lam.126
+30 210 4142479 | fax +30 210 4142119
Data Analytics and Statistics
• Tables, operations with tables, definitions, inverse and inverse of a table. Linear equations, methods of solving linear systems, Gauss elimination, Cramer's rule. eigenvalues and eigenvectors. probability theories, random distributions of basic discrete and continuous distributions.
• Data cleaning, transformation. Measures of similarity, distance. Linear and accounting regression. Introduction to Matlab Programming, Programming in mat lab. Introduction to R.
• Linear Multiple Linear Regression, Logistic Regression, Probit Regression, ANOVA-MANOVA. Exploratory factor analysis. The R language environment, Syntax, Basic Structures and Functions, Linear regression and Accounting regression applications, with R.
• Basic types of categorization. Statistical classification. Discriminant function analysis. Criteria for evaluating categorization methods. Database mining and advanced forecasting techniques.

-, GL126
+30 210 4142347
M2M Communications
The 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.
On successful completion of this unit students will be able to:
1. Identify the basic concept of wireless networks; Introduce various wireless systems and standards and their basic operation cases.
2. Analyse traffic theories, mobile radio propagation, channel coding, and cellular concepts.
3. Learn to model radio signal propagation issues and analyze their impact on communication system performance.
4. Understand the techniques of radio spectrum allocation in multi-user systems and their impact on networks capacity.
5. Compare and contrast multiple division techniques, mobile communication systems, and existing wireless networks.
6. Classify network protocols, ad hoc and sensor networks, wireless MANs, LANs and PANs.
7. Learn to simulate wireless networks and analyze the simulation results.
8. Analyze and propose broad solutions for a range of mobile scenarios.
Professor
104/Lam.126
+30 210 4142479 | fax +30 210 4142119
543, Central Building
+30 210 4142314
Sustainable Cultural Development for Digital Cities
Course Description Conceptual Approach of Cultural Routes, European Cultural Routes, promotion of cultural routes - digital means. Paths, European Long Distance Paths, Digital Paths, Creating Digital Cultural Routes, Case Studies.
Providing knowledge that examines the relationship between human and space through dimensions of time at a practical, emotional and ideological level.
The perceptual structure of the place. The city. The landscape of the city as a collective cultural processing by man. Concepts of space, place, landscape. Mapping and visualization of qualitative and intangible site data. Modern mapping and digital technology. Mapping evolution.
On successful completion of this unit students will be able to:
1. Identify the key concepts of cultural paths.
2. Understand the techniques of promoting cultural paths.
3. Analyse and propose techniques for designing digital cultural paths.
4. Define basic concepts of space and place.
5. To distinguish the elements that make up a site's profile.
6. To distinguish, analyze and process the multi-sensory landscapes of a place.
7. Use modern methods of capturing and representing the structural and physiological elements of a site.
8. Become familiar with modern methods of analyzing and visualizing landscape data.
9. Understand the city as a complex and complex system of big data.
10. Be able to apply modern practices of depicting cultural elements in the workshop for Piraeus.
Katapoti Despoina
Assistant Professor
104/Lam.126
+30 210 4142479
Copyright, Personal Data and Regulatory Issues
The evolution of digital technologies, in particular the Internet of Things, raises a wealth of legal issues ranging from copyright law, privacy issues, consumer protection, free access to information, data rights regulation (in particular the Big Data issue) and the security of information systems (cybercrime issues). The course examines all of the foregoing and, more specifically, the legal aspects of artificial intelligence, machine learning, blockchain technology and smart contracts.
The purpose of the course is to detect and address the legal issues related to the rapid development of digital technologies focusing also to the new reality of the Internet of Things (IoΤ).
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
Professor
104/Lam.126
+30 210 4142479 | fax +30 210 4142119
2nd semester
Information Governance and Compliance / Entrepreneurship - Administration of Smart Cities
Περιγραφή Μαθήματος
Αντικείμενο του μαθήματος είναι η κατανόηση του νέου τρόπου αστικής διακυβέρνησης και διαχείρισης των «Έξυπνων Πόλεων» με την αξιοποίηση ψηφιακών τεχνολογιών και του Διαδικτύου των Πραγμάτων (IoT). Οι συμπράξεις είναι μεταξύ βιομηχανίας – επιχειρήσεων, τοπικών αρχών και κοινωνίας και επικεντρώνουν στη βιώσιμη ανάπτυξη, τη βιώσιμη αστική κινητικότητα, τις βιώσιμες γειτονιές, το βιώσιμο δομημένο περιβάλλον, τις τεχνολογίες για υποδομές ενέργειας, μεταφορών, πληροφοριών και επικοινωνίας. Το Διαδίκτυο των Πραγμάτων (IoT) και οι σύγχρονες ψηφιακές τεχνολογίες, με τη συνδρομή νεοφυών επιχειρήσεων που δραστηριοποιούνται στο τομέα αυτόν, έχουν σαν αποτέλεσμα την ενίσχυση της επιχειρηματικότητας, την μείωση των κοινωνικών ανισοτήτων στον αστικό ιστό και τη μείωση της ανεργίας, καθώς και την ανάπτυξη μια νέας ψηφιακής οικονομίας και εκσυγχρονισμού της Δημόσιας Διοίκησης και σύμπραξης με τον Ιδιωτικό Τομέα. Η υιοθέτηση καινοτόμων τεχνολογικών λύσεων συμβάλουν στην ανάπτυξη της Επιχειρηματικότητας, «ελέγχοντας» με σύγχρονο τεχνολογικό τρόπο την επιχείρηση. Μέσω εφαρμογών που εντάσσονται στο Διαδίκτυο των Πραγμάτων, οι σπουδαστές θα έχουν την ευκαιρία να αναγνωρίσουν υψηλού επιπέδου εξειδικευμένες υπηρεσίες για τον πολίτη, τον πελάτη, με απώτερο στόχο τη βέλτιστη διαχείριση της πληροφορίας.
The course provides the basic concepts, fundamental approaches and key tools for aspiring decision makers who do not necessarily hold financial positions or backgrounds. It will equip students with the state-of-the art tools, methodologies and ideas needed in making and analyzing the two key decisions in finance concerning Investments and Financing.
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
303/Lam.126
+302104142476
Professor
104/Lam.126
+30 210 4142479 | fax +30 210 4142119
Algorithms for Urban Transportation
The subject of the course is the modeling and presentation of algorithmic techniques for computational problems that arise in the field of urban transport. Specifically, optimization techniques and algorithms for the design and management of the transport of goods and people as well as the induced traffic in an urban environment will be presented. The lectures of the course will cover the following topics: Traffic forecasting, Service pricing, Multi-model transport, Congestion modeling and reduction techniques, Line design for public transport and route planning (timetabling), User Behavior Models, Design Routing in road networks, Management of delays and emergencies, Fleet routing and supply chain issues, Central traffic management, Electricity and green transport, Car sharing systems (car sharing, car pooling, ride sharing), Tourist route planning, Motivation of users, Intelligent parking solutions, Mobility as a Service and use of one ticket for all urban travel.
Pantziou Grammati
Professor
301, Lam. 126
+302104142124
Energy Management, Smart Grids and Smart Agriculture
The course presents topics related to the study of new technologies applied to a smart building as well as on farms, allowing the monitoring of energy consumption as a whole as well as the individual consumptions of specific devices. Emphasis will be placed on technologies including the Internet of Things (IoT), sensors and actuators, geo-tracking systems and Big Data. The course will focus on the following topics: Technologies that allow remote control of loads using controllable loads, innovative algorithms for automatic load management using sensors and actuators (heating / humidity / motion / presence / window), decision support systems (DSS) for integrated farm management to optimize performance, dynamic real-time load-based management systems taking into account the energy market conditions to minimize the cost of consumption thus enabling their participation in energy communities.
Additionally, the course includes the following subjects: Introduction to Smart Grid (Architecture, Feasibility, Alternative Implementation Technologies), ITU Smart Grid Analysis Model, Smart Grid Ownership / Regulatory Issues, Smart Meters and Big Data, Smart Grid Benefit Analysis, Energy management for buildings, Introduction to ISO 50001, building energy signature, energy management information infrastructure, Drone use in agricultural activities.
Upon successful completion of this module students will be able to:
1. Understand the architectural structure of the Smart Grid and alternative technologies for its implementation.
2. Evaluate the utility of smart grid technologies according to the characteristics of the implementation area.
3. Become familiar with smart meters and the needs generated for big data and cloud infrastructures.
4. Learn the basic principles of the institutional framework for energy infrastructure management with emphasis on building infrastructure (offices, process, industrial).
5. Understand the utility of installing an energy management system and regularly performing energy audits in accordance with the law.
6. Understand the key variables affecting energy consumption and how to determine the energy signature.
7. Understand the energy management of information infrastructure with emphasis on data centers.
8. Become familiar with UAV technologies for smart farming.
Livieratos Spyridon
Professor
slss@unipi.gr
Professor
104/Lam.126
+30 210 4142479 | fax +30 210 4142119
Urban Design of Digital Cities
Principles of Geographic Information Systems, Selection of Spatial Data Models (vector / raster depending on the nature of the case study), basic concepts and cartographic techniques, basic principles of geographic database management systems, concepts and techniques of spatial analysis, mapping spatial data in regional and urban level.
Upon successful completion of this module students will be able to:
1. Identify the basic concepts of geographic information systems.
2. Analyze different spatial levels and scales and select an appropriate spatial data model.
3. Analyze demographic and general statistics at country / regional / sub-regional level and mapping them.
4. Analyze data at urban / urban level and mapping them.
5. Perform spatial queries and interpret their results.
Software for Smart Cities
The subject of the course is the development of software that can be used in the context of smart cities. This software can be installed and run on both modern "smartphones" and other smart devices, that have appeared in recent years and use an operating system. The software that can be used in smart cities includes, among others, software for wearables, software for smart TVs, software for the new generation of smart cars, as well as software for smart boards "Android Things". The course analyzes the most popular IoT operating systems, as well as the application development tools in them, however the material mainly includes the use of object-oriented Java programming language, for the development of applications on mobile devices under the Android operating system, and software development on cloud computing platforms.
Professor
507, Central Building
+30.210.4142269
Professor
104/Lam.126
+30 210 4142479 | fax +30 210 4142119
540, Central Building
3rd semester
MSc Thesis