BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Date iCal//NONSGML kigkonsult.se iCalcreator 2.20.2// METHOD:PUBLISH X-WR-CALNAME;VALUE=TEXT:Eventi DIAG BEGIN:VTIMEZONE TZID:Europe/Paris BEGIN:STANDARD DTSTART:20191027T030000 TZOFFSETFROM:+0200 TZOFFSETTO:+0100 RDATE:20201025T030000 TZNAME:CET END:STANDARD BEGIN:DAYLIGHT DTSTART:20200329T020000 TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:calendar.19551.field_data.0@www.ugov-ricerca.uniroma1.it DTSTAMP:20260404T190712Z CREATED:20200314T161731Z DESCRIPTION:PhD Course on Smart Environments: Technologies\, state of the a rt and research challengesNOTE: Due to Coronavirus restrictive measures\, the dates of the PhD Course have been moved to the last two weeks of April Credits: 3 CFU (20 academic hours)Lecturers: Ioannis Chatzigiannakis and F rancesco Leotta - Sapienza Università di Roma========= Short Description = =========Recent advances in communication and computation technologies sug gest an imminent explosion of the Internet-of-Things (IoT)\, i.e.\, a visi on of billions of everyday life objects connected to offer new solutions a nd services to final users. Areas of application of IoT include smart spac es\, i.e.\, private and public spaces realizing the paradigm of so called Ambient Intelligence. Smart spaces include smart houses\, public spaces (e .g.\, airports)\, offices but also\, in the context of the Industry 4.0 re volution\, factories and manufacturing processes inside them\, also includ ing the involved supply chain. In this PhD course\, students will learn fu ndamentals of IoT and techniques for smart environments.========= Overview ==========Internet-of-Things (IoT) represents the vision of billions of c omputers and everyday life objects connected together to provide high-leve l customized services. The first part of the course will analyze how the i dea of IoT evolved in the last years from the initial approaches based on wireless sensor networks\, to modern approaches where connected devices ar e not only sensors but real computers that can contribute to the computati on in the form of edge and fog computing. As communication between devices is a fundamental component of IoT\, prominent protocols and communication s technologies will be introduced to the students ranging from low-energy protocols (such as Zigbee\, Zwave) to the imminent introduction of 5G. In addition\, the student will be introduced to software platforms and framew ork that simplify the development of IoT applications.Among the several ap plications of IoT\, this course will then focus on smart spaces. The conce pt of smart space is the modern evolution of building automation\, where i ntelligence (also known as Ambient Intelligence - AmI) allows to provide c ustomized services to final users. Nowadays smart spaces can highly benefi t of IoT as a mean to acquire information about the smart context (e.g.\, a house\, a hospital\, an airport) and to perform operations on the enviro nment through the employment of actuators. In this sense the concept of sm art space is a fundamental part of the Industry 4.0 movement\, which is ga thering increasing interest from industry and institutions\, these latter ones promoting it through special regulations and funding channels. In the context of Industry 4.0\, devices of the Internet-of-things are often cal led digital twins\, as they provide a faithful representation of physical machinery and persons involved in the production processes and in the supp ly chain.In the second part of the course\, instructors will introduce the above concepts and will show techniques employed to realize the paradigm of ambient intelligence and how they relate to the techniques introduced i n the first part of the course. Additionally\, available software platform s and facilities will be introduced.========= Table of Contents ========== 1.    Introduction to IoT\, Sensors\, Communication Technologies (small sc ale and broad scale) - 2 hours2.    Cloud-based Data Processing for IoT de ployments\, Software Architectures and Available Platforms - 4 hours3.     Edge-based Data Processing for Wearable Devices and Privacy-aware IoT depl oyments\, Scenarios and Research Challenges - 4 hours4.    Ambient Intelli gence - 4 hours5.    Smart spaces and Industry 4.0 - 2 hours6.    Digital Twins in Industry 4.0 and available platforms - 2 hours7.    Research pers pectives on Industry 4.0 and Ambient Intelligence (2 hours)========= Calen dar ===========-    Wednesday April 22nd – 14:00 – 18:00 Room B101-    Fri day April 24th – 14:00 – 18:00 Room B101-    Monday April 27th – 14:00 – 1 8:00 Room B101-    Wednesday April 29th – 14:00 – 18:00 Room B101-    Thur sday April 30th – 14:00 – 18:00 Room B101========= Learning Objectives\, P rerequisites and Evaluation ==========The learning objectives of this cour se are:-    Mastering the technologies and techniques involved in IoT with particular focus on the applications in the fields of smart spaces and in dustry 4.0\;-    Understanding the challenges involved in the application of proposed approaches to physical\, and potentially harmful\, contexts.Th is course is aimed at PhD students\, Master students and (potentially) pro fessionals. A basic understanding of networks and machine learning (at the undergraduate level) is assumed.In order to get the credits provided by t he course\, a short project on the application of IoT to smart spaces or i ndustry 4.0 from the course participants (to be held individually or in gr oup) is required. With the project\, the participants must demonstrate the ability to put into practice the notions illustrated during the course.== ======= References ==================-    Alessandro Scirè\, Fabrizio Trop eano\, Aris Anagnostopoulos\, Ioannis Chatzigiannakis: Fog-Computing-Based Heartbeat Detection and Arrhythmia Classification Using Machine Learning. Algorithms 12(2): 32 (2019)-    Orestis Akrivopoulos\, Dimitrios Amaxilat is\, Irene Mavrommati\, Ioannis Chatzigiannakis: Utilising fog computing f or developing a person-centric heart monitoring system. JAISE 11(3): 237-2 59 (2019)-    Ignacio Rodríguez-Rodríguez\, Ioannis Chatzigiannakis\, José Víctor Rodríguez\, Marianna Maranghi\, Michele Gentili\, Miguel Angel Zam ora-Izquierdo: Utility of Big Data in Predicting Short-Term Blood Glucose Levels in Type 1 Diabetes Mellitus Through Machine Learning Techniques. Se nsors 19(20): 4482 (2019)-    Ignacio Rodríguez-Rodríguez\, José Víctor Ro dríguez\, Ioannis Chatzigiannakis\, Miguel Angel Zamora-Izquierdo: On the Possibility of Predicting Glycaemia 'On the Fly' with Constrained IoT Devi ces in Type 1 Diabetes Mellitus Patients. Sensors 19(20): 4538 (2019)-     Georgios Mylonas\, Dimitrios Amaxilatis\, Ioannis Chatzigiannakis\, Aris A nagnostopoulos\, Federica Paganelli: Enabling Sustainability and Energy Aw areness in Schools Based on IoT and Real-World Data. IEEE Pervasive Comput ing 17(4): 53-63 (2018)-    Leotta et al. Surveying Human Habit Modeling a nd Mining Techniques in Smart Spaces – Future Internet (2019)-    Leotta e t al. Visual process maps: a visualization tool for discovering habits in smart homes JAIHC (2019)-    Leotta et al. Applying process mining to smar t spaces: Perspectives and research challenges – RW-BPMS CAISE (2015)-     Leotta et al. IoT for BPMers. Challenges\, Case Studies and Successful App lications – BPM (2019)-    Leotta et al. A Conceptual Architecture and Mod el for Smart Manufacturing Relying on Service-Based Digital Twins – ICWS ( 2019) DTSTART;TZID=Europe/Paris:20200422T140000 DTEND;TZID=Europe/Paris:20200430T180000 LAST-MODIFIED:20200314T180126Z LOCATION:Room B101 DIAG SUMMARY:PhD Course on Smart Environments: Technologies\, state of the art a nd research challenges (TYPE B CREDITS) - NEW DATES - Ioannis Chatzigianna kis and Francesco Leotta URL;TYPE=URI:http://www.ugov-ricerca.uniroma1.it/node/19551 END:VEVENT END:VCALENDAR