Track 1: SMART ENERGY
Carlo Cecati, Univesity of L’Aquila, IES Italy Chapter
Fabio Viola, University of Palermo
Hadi Kanaan, Saint Joseph University, Beirut, Lebanon
Session 1.1 – Conversion and Control of Sustainable Energy Sources
Pierluigi Siano, University of Salerno, Italy
Kamal Al-Haddad, University of Montreal, Canada
Massimo La Scala, Politecnico di Bari, Italy
ABSTRACT – Research on sustainability has, in the last few decades, been the way that some countries have modernized their energy systems, emission profiles, and low carbon networks in order to respond to the challenges and problems that the world faces regarding global warming and climate change. Sustainability is achieved by balancing the species and resources within an environment. To maintain this equilibrium, available resources must not be depleted faster than resources are naturally generated, and natural, renewable resources must be used as efficiently as possible, ensuring high conversion yields, controlling the different resources both accumulated and foreseeable.
Keywords – Load flow; sustainable and renewable energy sources, biomass and biofuels, hydro production and energy storage, sustainable chemistry and chemical engineering, wind, solar, hydro, geothermal, nuclear, and bioenergy, air pollution and climate change, energy conversion and management, sustainable education awareness and development, life cycle assessment,environmental exposure mitigation strategies.
Session 1.2 – Power Electronics and Control in Smart Grids, Industry and e-Transportation
Alfonso Damiano, University of Cagliari, Italy
Giuseppe Schettino, University of Palermo, Italy
ABSTRACT – The new technologies in transportation and mobility are changing the way on how the mobility should be managed. It is expected that there will be over 250 million connected vehicles by 2022. This translates into huge data collection by integrated and interconnected sensors to create sophisticated global models on several parameters such as traffic flow or precise roadway maps. Moreover, connected vehicles and integrated communications technologies could provide valuable services to car user. Vehicles equipped with electronic control modules and sensors that enable Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications can proactively propose and recommend re-routings to avoid road hazards and calls for assistance in the event of an accident.
Keywords – Intelligent Transport Infrastructure and systems, Connected, Autonomous, self-driving systems, Shared Mobility and demand-responsive transport, Sustainable Mobility towards low-carbon Cities, Mass Transit Networks, Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) communications.
Session 1.3 – Energy Storage Systems and their Control
Andrea Mazza, Politecnico di Torino, Italy
Daniela Proto, Università degli Studi di Napoli Federico II, Italy
ABSTRACT – In the last few decades, energy storage systems were investigated because of their potential role in the electrical grid operation and planning, both in case of stationary installation (characterized by larger sizes in terms of both power and energy, including Power-to-X technologies, P2X) and mobile technologies (the so-called Vehicle-to-X, V2X, more widespread in the territory and typically distinguished by lower capacity). Thanks to their fast dynamics, energy storage systems represent one of the key technologies to operate the future electrical systems, being able to handle with several critical aspects strictly related to the undergoing paradigm change (from load-following to generation-following system), supporting the grid integration of renewables, improving the grid stability margins and power quality levels, smoothing the variability of electricity demand and lowering the electricity costs. They also represent the enabling technology for green transformation of the mobility and transportation sectors, because of their electrification. Energy storage systems differ from other technologies also in the breadth of their addressable market and of the typologies of involved stakeholders. Their control, however, is technically challenging involving different approaches, which can be complicated by the presence of auxiliaries requiring tailored control algorithms. Furthermore, the materials used may be an issue because of their availability and their costs.
This session is devoted to the cross-cutting on-going research related to electrical energy storage systems and multi-energy storage systems, including their optimal planning and operation in both stationary and mobile applications.
Keywords – Planning and operation of mobile and stationary distributed energy storage systems, integration of energy storage systems into the grids, policy/regulatory aspects of energy storage systems, electrical energy storage systems, multi-energy storage systems, Vehicle-to-X (V2X), Power-to-X (P2X).
Session 1.4 – Electrical Machines and Drives for Industry and Renewable energy Systems
Sobhan Mohamadian, School of Engineering, Damghan University, Iran
Massimo Caruso, University of Palermo, Italy
ABSTRACT – Nowadays, the energy consumption determined by electric drives corresponds to 46% of the global energy demand and, therefore, new optimization techniques and control algorithms have been developed to either maximize the efficiency or reduce the harmonic content of electric machines and drives applied to both industry and Renewable Energy Systems (RES). Moreover, advanced and high-accuracy equipment of measurement is needed in order to allow the performance improvement of the whole drive. Therefore, this session aims to present and disseminate the most recent advances and future perspectives related to the development of both traditional and unconventional electric machines and drives applied to both RES and Industry.
Keywords – Electrical machines for RES, Electrical drives for industry, Winding design, Fault tolerant drives, Finite Element Analysis, Permanent Magnet Machines, Induction machines, Multiphase motors and generators, Power loss minimization, Wind farms.
Session 1.5 – Energy Management, Smart Metering and Distributed Energy Resources
Giuditta Pisano, University of Cagliari, Italy
Ciro Spataro, University of Palermo, Italy
ABSTRACT – The administration of distributed energy resources in smart grids is the most promising answer to cope with the increasingly growing demand of electrical energy all over the world, accounting for the requirement of planning a sustainable future from both environmental and economic viewpoints. In fact, the presence of renewable generation injecting power into the electrical grids, as well as the presence of various types of distributed energy resources (e.g., electric vehicles, responsive loads, and distributed storage), leads to several critical conditions of unpredictability and insecurity, which require researchers and utilities to develop innovative smart grid. Smart grids require the following challenging characteristics in order to be implemented effectively: safety, reliability, efficiency, affordability, environmental “cleanliness”, technical and economical optimization, interaction with electricity markets, self-healing ability, and the presence of an appropriate regulatory framework.
Keywords – Renewable generation, distributed energy resources, smart grids, microgrids, power quality, optimal planning and operation, smart protections, power electronics, reliability, adequacy.
Session 1.6 – Electric Mobility: challenges, trends, safety and EMI issues
Stefano Bracco, University of Genova, Italy
Giorgio Sulligoi, University of Trieste, Italy
Daniele Bosich, University of Trieste, Italy
ABSTRACT – Over the last years, the global community has been involved into an unprecedented revolution in the mobility sector, with a significant evolving of technology from internal combustion engine vehicles to hybrid and full electric vehicles. For this reason, the interest of researchers towards the transportation systems and the related environmental impact has significantly increased over the last years, evaluating the optimal integration of electric mobility systems in urban areas. These aspects refer to the use of public and private vehicle fleets fed by appropriate charging infrastructures and managed through advanced IoT platforms which allow the implementation of innovative strategies including demand response approaches and smart charging.
Keywords – Vehicle grid integration and related challenges, Charging infrastructures, Smart charging of electric vehicles, Integration of electric vehicles with renewable sources Energy management systems, Environmental impact evaluations, Electric vehicles safety and Emi issues.
Session 1.7 – Application of Machine Learning and Artificial Intelligence in Smart Grids
Alessandro D’Innocenzo, University of Aquila, Italy
Gianfranco Chicco, Politecnico di Torino, Italy
ABSTRACT – In recent years, many advances have been introduced in the smart grid context, because of the progressive integration of information and communication technologies, enhanced applications of monitoring and control systems, and new techniques for signal processing and data analytics. The current framework considers cyber-physical systems, paying attention to various layers dedicated to technical, economic, environmental, and social aspects, also dealing with the corresponding security issues. Data-driven approaches are emerging in different applications to smart energy networks, smart buildings, and smart cities, especially when the complexity of the systems makes it impractical to derive physics-based models. The new tools developed follow specific paradigms for extracting knowledge from the large amount of data available from the field, such as deep learning, and exploit different ways for handling uncertainties. The relevant applications include forecasting, metering, state estimation, automation, operation, fault analysis, planning, asset management, energy management, provision of services to the grid or customers, and support to decision-making.
Keywords – Artificial neural networks, Asset management, Cyber-physical systems, Data analytics, Deep learning, Distribution automation, Energy system monitoring, Forecasting, Knowledge-based applications, Machine learning.
Session 1.8 – Energy Harvesting, Wireless Power transfer and Power Electronics Systems
Minh Nguyen, Thai Nguyen University of Technology, Vietnam
Luigi Costanzo, University of Campania, Italy
ABSTRACT – The last years have seen a very increasing diffusion of electronic devices that must be supplied by rechargeable batteries. Examples are: mobile consumer devices like smartphones and smartwatches; wearable devices for healthcare, fitness, and military applications; electric cars; wireless sensor nodes frequently employed, for monitoring purposes, in environments or infrastructures where a wired energy supply is not present or its distribution is not economically convenient. Whichever is the application, batteries need to be frequently recharged due to their limited capacities. In order to avoid the use of cables for battery recharging purposes, an unprecedented amount of attention has been devoted to the development of novel wireless power delivery methods. In this context, Energy Harvesting and Wireless Power Transfer are currently receiving considerable attention and, in order to avoid the waste of precious energy, the design and optimization of their Power Electronics Systems is of crucial importance.
The objective of the session is to focus on all the new technologies and advances in the fields of Energy Harvesting and Wireless Power Transfer and on all the latest scientific results in the analysis, the design and the optimization of their Power Electronics Systems.
Keywords – Energy harvesting; Vibration Energy; Piezoelectric Harvesters; Electromagnetic Harvesters; Photovoltaic; Micro Wind Turbines; Thermoelectric Generators; Regenerative Suspensions; Rail Track Vibration Energy Harvesters; Rainfall Energy Harvesters; Wearable Energy Harvesters; Wireless Power Transfer, Inductive Power Transfer; Capacitive Power Transfer; Wireless charging; Resonance; Impedance Matching; Maximum Power Transfer; Maximum Power Point Tracking.
Session 1.9 – Cyber Security and Big Data Issues for Smart Grid Systems
Seref Sagiroglu, Gazi University, Turkey
Pierluigi Gallo, University of Palermo, Italy
ABSTRACT – The worldwide need for an energy transition is becoming major, and is faced by significant and far-reaching challenges. More than ever, transportation, communications, resource management (water and air), and even agriculture are enabled by modern electrical power and energy systems promoting automation. It is clear that energy is going more to be electrical and this is a great chance to integrate a higher portion of renewables, promoting a more efficient and decentralized energy system, by involving advanced digital technologies and systems such as smart devices, faster and more flexible gateways, smart meters, and Internet of things (IoT). However, this transition comes with a significant cost: The need for cyber-defense measures, strategies, algorithms, schemes, tools, and frameworks to maintain or improve the infrastructure’s security posture.
Keywords – Intrusion detection systems and big data analytics for accurate anomaly detection for smart grids; Cybersecurity mechanisms, tools, and frameworks in modern smart grids; Privacy-preserving tools, frameworks, and schemes in modern smart grids; Security information and event management in modern smart grids; Privacy standards and certificates for smart grids and energy networks; Blockchain technologies for accessing and sharing energy data in modern smart grids; Anonymous communication channels in smart grids and energy networks; Trust management and mechanisms in modern smart grids; Security certification processes in electric smart grids; Big data analytics, machine learning tools, and deep learning techniques for anomaly detection in smart grids and energy systems.
Session 1.10 – Special Technical Session – Electrification of small islands
Marco Merlo, Politecnico di Milano, Italy
Enrico Ragaini, ABB
ABSTRACT – All around the world, Small Islands have started to strongly integrate renewables into their electricity supply mix. The expected benefits include reducing dependency on costly, sometimes volatile fossil-fuel imports. But local utilities must also ensure reliable supply amid the shift to variable sources, such as solar and wind energy. The technical solution under investigation can be classified as a hybrid architecture where a.c. and d.c. are asked to be interoperable, resulting in a major challenge. Resource optimization and customized equipment design are assuming a pivotal role for obtaining a technical and economical viability.
Keywords – Smart and sustainable islands; virtual synchronous generators; tools for sizing the generation portfolio; tools for siting the generators and for routing the distribution feeders ; tools for assessing and improving the microgrid liability; EMSs (Energy Management Systems): tools for an optimal energy management in a microgrid ; Innovative Equipment for microgrid; real life study cases.
Session 1.11 – Special Technical Session – Advanced Control of Grid-Connected Converters for Distributed Generation and Power Quality
Hadi Y. Kanaan, Saint-Joseph University of Beirut, Lebanon
Fadia Sebaaly, Ecole de Technologie Supérieure, Canada
ABSTRACT – Renewable sources, such as photovoltaic panels, wind generators and fuel cells, are usually connected directly to the grid for cogeneration. This connection is made through power electronics interfaces that should ensure high stability, voltage regulation, power flow control, and low electromagnetic emission, along with high power density, low cost and high reliability. In some applications where high power level is required, the switching frequency of the power semiconductors is limited and the use of multilevel or interleaved converters becomes mandatory in order to get an acceptable power quality. This session addresses the issues of advanced control techniques applied to such converters to improve their performance, efficiency, reliability and cost-effectiveness.
Keywords – Advanced Control of Multilevel Inverters; Advanced Control of Power Electronics In DC Grids; Grid-Connectivity Control Requirements; Control Of Paralleled or Interleaved Topologies; Modeling And Model-Based Control of Switch-Mode Power Converters; Optimal Control in Hybrid Cogeneration Systems; Predictive Control of Power Converters; Intelligent Control of Power Converters; Direct Power Control of Power Converters; Power Quality Control in Renewable Energy Systems; New PWM Techniques for Power Electronics Control; Real-Time Control and Simulations of High Power Converters.
Session 1.12 – Special Technical Session – Advances in Power System Dynamics for Smart Grids
Enrico De Tuglie, Politecnico di Bari, Italy
Pasquale Montegiglio, Politecnico di Bari, Italy
Désiré D. Rasolomampionona, Warsaw University of Technology, Poland
ABSTRACT – The Smart Grid (SG) concept is widely acknowledged as one of the most powerful innovations in energy systems. As energy supply infrastructures with expected high quality of service, efficiency, and high renewable generation share, SGs are foreseen to provide important advancements in terms of mitigation of the environmental impact due to energy usage, through efficient and advanced supply and service provision.
Research efforts are in progress for developing next generation SGs cover a wide range of investigation domains and applications. In this respect, the recent developments of distributed generation, storage and demand side flexibility have a deep impact on power system dynamics. The strategies adopted to manage the SG dynamics are quickly evolving, fostering the development of more and more sophisticated management algorithms, both for the bulk power system and from the perspective of self-organized microgrids and local energy communities.
This special session is open to contributions from researcher, engineers, manufacturers, and practitioners on recent advances and developments SG dynamic modeling techniques and simulation tools, real-time monitoring and control of SG components, and future challenges and directions for SG dynamics.
Keywords – power system dynamics, dynamic simulation, real-time monitoring, blackout, transmission systems, microgrid control.
Session 1.13 – Special Technical Session – Smart solution for high penetration of PV generation in Renewable Energy Communities
Gabriele Maria Lozito, University of Firenze, Italy
José M. Blanes, University Miguel Hernández of Elche, Spain
ABSTRACT – Renewable Energy Communities (RES communities) are defined at EU level as aggregations of consumers and prosumers by Directive 2018/2001 on Renewable Energy Sources and Directive 2018/944 on common rules for internal energy market. RES communities could be considered as Virtual Power Plants, being an aggregation of energy resources that can be treated as a single larger resource from the grid operator’s perspective but may not be geographically co-located and generally do not have the ability to operate independently from the grid. A RES community could be entitled for economic incentives if energy self- consumption is achieved. This incentive gives a prosumer perspective in terms of energy management that affects the smart-grid behaviour and control.
Both in urban, suburban, and extra-urban environment a RES community’s existence depends on the possibility of a sizeable, distributed energy generation from renewable sources. In this scenario, photovoltaic (PV) generation plays a central role due to its scalability, economic profile, and natively electrical nature. Indeed, the development and diffusion of RES communities is limited, among other factors, by the degree of penetration of PV distributed power generation. This limit can be traced to several challenges faced both in design, monitoring and operation of a grid connected PV generation system.
Photovoltaic applications need to manage the uncertain and irregular nature of the energy source, through accurate electrical modelling, and by providing appropriate energy conditioning and management in the form of power converters. The typical power converters in a PV generation chain often perform high DC voltage elevation and AC conversion for grid connection, resulting in the necessity for protection systems and harmonics filtering. Moreover, both the electronics and the PV source is subject to aging and deterioration, which results in the necessity of real-time monitoring solutions for fault detection and prevention, pursuing an increased reliability of the whole RES community.
This session welcomes all contributions that presents ideas and innovative solutions to accelerate the PV penetration in RES communities, with the goal of aiding the diffusion of a more sustainable energetic environment.
Keywords – Photovoltaics, Solar Power Generation, Energy Community, Maximum Power Point Trackers, Modelling, Optimization, Fault Detection, Reliability, Power Converters, AC Protections, DC Protections, Filtering.
Session 1.14 – Special Technical Session – The Power Supplies System (PSS) and the Electrical Distribution System (EDS) of Tokamak Experimental Facilities
Gianmario Polli, ENEA-DTT, Italy
Pietro Zito, ENEA Research Center Frascati, Italy
ABSTRACT – Among tokamak facilities currently in construction like ITER (in France) and JT60-SA (in Japan), Divertor Tokamak Test (DTT) facility is part of the general European programme in fusion research.
The technical session is focused on the role, the physic characteristics, the design status and progress of power supply systems and of the electrical distribution system of DTT. In particular, the toroidal power supply system feeds 18 toroidal superconducting magnets that confine the plasma into the vacuum vessel, whereas the poloidal power supply system feeds 6 central solenoid and 6 poloidal field superconducting magnets. The Switching Network Units are connected in series to those power supplies that cannot provide the required value of voltage for the breakdown of plasma. Also, Fast Discharge Units (FDU) are power devices for the quench protection of superconducting magnets. In-vessel coils generally in copper perform the function to control the vertical position of the plasma. Among these, Vertical Stabilization coils are fed by VS power supplies for vertical control of plasma. These power supplies are very critical both for vertical stabilization of plasma both for the L-H and H-L transitions. Further its design is critical due to the plasma disruptions and Vertical Displacement Events (VDE). Furthermore, the divertor power supplies feed in-vessel coil that control locally the magnetic field close to divertor area. In-vessel Not-Axial-Symmetric coils are fed by NAS power supplies. They control local and MHD instabilities of plasma. Finally, electrical distribution system and the earthing network and their characteristics are currently analysed for DTT facility.
In this framework, we encourage the submission of papers dealing with (but not limited to) the following topics:
– Large / medium size tokamak and its main systems
– High current power supplies;
– High voltage power supplies;
– High Voltage AC power cable connection;
– HV/MV Sub-Station to power both pulsed and stationary electric power systems;
– Power supply for vertical stabilization of plasma;
– Quench protection systems;
– Static Var Compensation (SVC) and Filtering systems;
– Electrical Distribution System;
– Earthing network design.
Keywords – Tokamak, Superconducting Magnets, High Current and High Voltage Power Converters, Quench Protection Systems, Electrical Distribution System, Earthing Network.
Track 2: SMART INDUSTRY
Giambattista Gruosso, Politecnico di Milano
Federico Baronti, University of Pisa
Juan José Rodríguez-Andina, University of Vigo, Spain
Session 2.1 – Smart Materials & Smart Sensor for Industry 4.0
Patrizia Lamberti, Università degli Studi di Salerno, Italy
Polina Kuzhir, University of Eastern Finland, Finland
ABSTRACT – Industry 4.0 is synonymous for smart industrial evolution in terms of automation and control: everything is getting smarter and data generated at all levels of the production process can be used, for example, to improve product quality, flexibility, and productivity. Smart materials represent the key enable technology leading to realize Smart sensor that can be integrated in a structure to transform it in a self communicating system, by exploiting the particular considered multifunctionality, moving for example from the self monitoring to the self-powering and/or to the self healing. The proposed session will collect recent development in terms of smart materials and their integration in smart sensor to be applied in the industrial sector in the next future.
Keywords – smart material; smart sensor; multifunctionality; energy harvesting; self-healing; self-sensing; self-monitoring.
Session 2.2 – Sustainable Industrial Processes and Products
Andrea Matta, Politecnico di Milano, Italy
Ramez M. Daoud, American University in Cairo, Egypt
ABSTRACT – The twenty first century is the era of sustainability. All new projects, designs and products have to be sustainable. For the good of the environment as well as for the long term profitability of the enterprises, sustainable industries must prevail. During the past two years of pandemic, a need rose for production lines to be operative with minimum down time because of the huge lack of manpower for technical assistance and spare part supply. New design, planning and control methodologies as well as new materials and new technologies must be explored for high efficient and low carbon impact production systems and industrial plants. Also, fault-tolerance and reliability of the electronics circuits and chips is essential for the overall performance either at machine and system levels.
Keywords – fault-tolerance, reliability, sustainability, recovery, maintenance, industrial process, production control, production systems.
Session 2.3 – Modelling and Simulation of Advanced Products and Manufacturing Processes
Joanna Olszewska, University of West Scotland, UK
Giambattista Gruosso, Politecnico di Milano, Italy
ABSTRACT – With the Industry 4.0, smart products and manufacturing processes require advanced modelling and simulation methods, including but not limited to digital-twin modelling, interoperable knowledge representation, ontology engineering, algorithmic and mathematical formalization, software and hardware simulations as well as signal processing, data processing, semantic processing, image and video processing. Nowadays, the design and development of smart products and manufacturing processes involve also testing, verification and validation of autonomous systems, intelligent agents, systems of systems, etc., and aim for explainable algorithms, dependable software, and trustworthy cyber-physical systems. To this end, advanced modelling and simulation methods must be investigated taking into account aspects such as safety, transparency, explainability, trustworthiness, accuracy, efficiency, dependability, interoperability, verification & validation, and emerging standards.
Keywords – industry 4.0; smart manufacturing; emerging standards;digital twin; knowledge-driven approaches; ontologies; machine learning approaches; explainable artificial intelligence; transparent manufacturing processes; transparent autonomous systems; trustworthiness in autonomous manufacturing systems; chatbots; cobots; robotics knowledge management; augmented operators; smart products design; smart processes modelling; algorithm modelling and processing; system and software development life-cycles; verification & validation; safety in robotic systems; safe human-machine interaction; safety of innovative process designs; software and system testing; dependable software; tools and techniques for advanced products’ and manufacturing processes’ verification; data processing; modelling and simulation of cyber-physical systems; internet of things; edge computing; cloud-robotic systems; machine vision.
Session 2.4 – Additive Manufacturing Technologies, Applications and Measurement
Gianluca Fiori, University of Pisa, Italy
Gabor Sziebig, Sintef manufacturing, Norway
ABSTRACT – Additive manufacturing (also referred as 3D printing) has become the enabling technology for a wide range of applications, and, most importantly, it is the driving force for the manufacturing paradigm shift towards Industry 4.0:
i) (in the long terms) client’s self-production and on demand, with reduction of costs (transportation, logistics and material);
ii) (in the short term) the realization of low-cost prototypes and custom-made parts, which should reduce the time to market of a product, especially important from the industrial point of view.
This session aims addressing the perspectives of additive manufacturing, with particular focus on industrialization of additive manufacturing (e.g., robotized production) and printed electronic applications. Additive manufacturing today is mainly in research stage due to the high cost of machinery and the not yet proved mechanical properties of products manufactured with this technology. The session will highlight the challenges and some success stories. For what concerns printed electronics, additive manufacturing can be the game changer on a wide range of applications, as for example in wearable and flexible systems, RFID tag, printed antenna, just to cite few. In the session, all the main aspects and issues related to this kind of applications will be addressed.
Keywords – 3D printing, lattice structure, WAAM, Printed Electronics, Flexible and wearable circuits, RFID tags, printed antenna.
Session 2.5 – Smart Systems and Artificial Intelligence for Manufacturing
Giancarlo Fortino, University of Calabria, Italy
Wenfeng Li, Wuhan University of Technology, China
ABSTRACT – In recent decades we have witnessed a fast development of smart systems in almost every industry. Digital economy is a new feature of Industry 4.0. And COVID-19 has changed our life and also pushed the application of new IT technologies such as the Internet of Things and Artificial intelligence into our industry, such as logistics and manufacturing. This session is dedicated to the recent development and application of artificial intelligence in manufacturing and logistics and the new practice of smart systems in these fields, especially when facing the impact of pandemic of COVID-19. The main topics include but not limit to, modeling and simulation, scheduling and resource allocation, optimization algorithm, artificial intelligence, big data, Internet of Things, distributed sensing and control, edge computing and cloud service, digitization technology, advanced robots, intelligent mechanism; typical application fields include smart manufacturing, multimodal transport, smart harbors, smart logistics, and digital supply chain.
Keywords – Smart Manufacture, Smart Logistics, Logistic Automation, Multimodal Transport, Smart Harbor, Artificial Intelligence, Big Data, Internet of Things, Smart Objects, Machine Learning, Convolutional neural networks, Data mining, Data visualization, Deep learning, Digital Twins, Knowledge engineering, Scheduling, Intelligent Optimization, Logistics and Supply Chain, Pandemic.
Session 2.6 – Smart Technology for Autonomous Systems: from Robots to Drone
Seiichiro Katsura, Keyo University, Japan
Paulo Jorge Sequeira Gonçalves, Instituto Politécnico de Castelo, Portugal
ABSTRACT – Nowadays there is a strong demand to develop innovative robotic solutions for complex environments and multiple operations, including data gathering, inspection, mapping, surveillance, and intervention, on several types of scenarios. The track aims contributions that go beyond the state-of-the-art on smart technologies that increase the autonomy of autonomous systems, e.g., physical robotics agents, from Robots to Drones. Applications of such smart technologies on autonomous systems can include, but not limited to: autonomous navigation; long-term deployments; sensing, mapping, and intervention; multiple platform operations; knowledge representation.
Keywords – smart sensors; autonomy; autonomous robots; drone; mapping; smart manufacturing; semantic mapping; knowledge representation.
Session 2.7 – Automation, Robotics and Smart Factories: Collaborative Machines and Systems
Eray Abdurrahman Baran, Instabul Bilgi University, Turkey
Mohammad Safeea, University of Coimbra, Portugal
ABSTRACT – The recent advances in smart manufacturing and Industry 4.0 paved the way for collaborative task execution between humans and machines. Together with the emergence of novel control algorithms and soft interaction interfaces, today, human-robot collaboration plays a crucial role in smart factories. Originating from this point, new generation robots are desired to provide an improved dexterity and flexibility using novel control algorithms. Achievement of those goals are possible by simultaneous satisfaction of the requirements on extreme precision and soft interaction in an unstructured and dynamic environment. Hence, this special session welcomes submissions of original work in the area of Collaborative machines and systems addressing not exclusively any of the fields below.
Keywords – Human-Machine Interaction, Collaborative Robots, Cyber-Physical Systems, Soft Actuation, Soft Sensors, Compliant and Soft Robotics, Assistive Robotics, Robot-Environment Interaction, Haptics for Human Support.
Session 2.8 – Augmented Reality-Based and Virtual Reality
Luca Leonardi, University of Catania, Italy
Marco Rossoni, Politecnico di Milano, Italy
ABSTRACT – Thanks to the enormous progress made in digital technology, Augmented Reality (AR) and Virtual Reality (VR) are being widely adopted in several sectors: defense, manufacturing and medical applications are just a few examples. Despite the level of maturity of AR and VR is increasing rapidly, several challenges still prevent these technologies to take off. This session aims to provide a forum for the presentation of scientific works spanning from the fundamental theories of VR and AR to high-level applications in different domains, e.g., arts, medicine, industry, defense, design, and education.
Keywords – AR and VR for maintenance, Virtual training, Digital Twin, Assembly and Quality Control, Collaborative AR and VR.
Session 2.9 – Agriculture 4.0: Technology and Solution
Sergio Saponara, University of Pisa, Italy
Danilo De Marchi, Politecnico di Torino, Italy
ABSTRACT – Agriculture 4.0 is an emerging application domain where Electronics and Electrical Engineering are having an important impact at all the different levels, from sensors and readout, up to the management, elaboration and transmissions of data. This Session wants to collect contributions from stakeholders engaged in developing electronics, and the related instruments, measurements and control systems, for the edge technologies applied to:
– production, for Agriculture 4.0 methodologies, optimizing cultivations in terms of yield and quality, reducing the use of treatments (pesticides, …) and of resources (water, …); for implementation of automated equipment for harvesting, treatment, and packaging;
– monitoring, including the use of drones for agriculture, and also for following the goods during their shipment, obtaining useful information for best transportation and optimized delivery in terms of time to reach customer tables;
– regulation, that introduces the need of online environment control and crops and food status, during harvesting, elaboration, packaging and shipping.
The need of monitoring systems at all levels is mandatory. This involves the introduction of new instruments and platforms connected, following the IoT (Internet of Things) paradigm, to efficient and low-power smart electronic systems, with the challenges to be as much as possible autonomous and low-cost. For all these reasons the Session wants to collect the most advanced studies that the scientific community is doing in this emerging field, fundamental for the health and the well-being of our human society.
Keywords – Precision Agriculture, Smart Agriculture, Smart Systems, Smart Sensors, Crop Monitoring, Water Control.
Session 2.10 – Digital Manufacturing: from Data Collection to Intelligent Systems
Gaetano Patti, University of Catania, Italy
Veera Ragavan, Monash University, Malaysa
ABSTRACT – Digital Manufacturing: from Data Collection to Intelligent Systems” aims to bring together experts from various domains, such as IT, Telecommunication, Automation, and many others, to discuss the current challenges in the field of industrial systems.
The confluence of computer, communication, and manufacturing technologies has opened new frontiers in manufacturing. Also called cyber-physical production systems, they are enabled by new digital technologies – AI, big data, digital twins, the internet of everything, etc. Typically, there is no one-solution-fits-all communication technology, but a mixture of several interconnected technologies is required. Developers of such systems face several hard constraints, such as low latency, high reliability, real-time transmissions, safety, and security, distributed among many cooperative, computational elements controlling the time-critical physical entities. This poses several challenges for the integration, maintenance, configuration, and management of such complex systems. Applications in the industrial domain, need innovative approaches and a fine balance between communication performance, flexibility, interoperability, and user-friendliness.
Keywords – Cyber-Physical Production Systems, Digital Twins, Industrial Communications, Cloud, Edge, Fog and Roof computing, Communication for Industry 4.0, Real-time communications, Software Defined Networking (SDN), edge/fog computing, Network Function Virtualization (NFV), Time Sensitive Networks (TSN).
Track 3: SMART HEALTHCARE
Sergio Cerutti, EMB Italy Chapter Chair
Thomas Penzel, Charité University Hospital, Berlin, Germany
Session 3.1 – Services, Applications and Solutions in Smart Healthcare
Maria Gabriella Signorini, Politecnico di Milano, Italy
Fernando Vaquerizo-Villar, Institute for Bioengineering of Catalonia, Spain
ABSTRACT – With the advancement of technology in the health sector, the concept of smart healthcare has come to the fore as a transformation of the traditional medical system in an all-round way, making healthcare more efficient, more convenient, and more personalized. Smart healthcare uses novel products and technologies for disease prevention and monitoring, diagnosis and treatment, hospital management, health decision-making, and medical research, among others. In this session we want to highlight novel services, applications, and solutions in healthcare which have clear benefits for clinical/scientific research institutions, regional health decision-making institutions, and/or individual end users.
Keywords – Health management; Hospital management; Health Big Data; Wearable and Robotic Solutions; Biomechanics; Web and Mobile Applications; Clinical decision-support systems, Biomedical systems modeling; Emergency applications.
Session 3.2 – Big Data Integration and Personalised Medicine
Luca Faes, University of Palermo, Italy
Dimitrios Fotiadis, University of Ioannina, Greece
ABSTRACT – Modern approaches to Healthcare offer solutions to manage personalized data relative to the single patient, including medical records and biomedical signals and images, aimed to improve diagnostic and therapeutic strategies and to shift the management of patients and frailty individuals from hospital to outpatient and home settings. These approaches typically require to create networks of devices for the recording of vital signs and medical parameters, as well as to deal with very large amounts of data which need to be properly processed and correctly interpreted. The development of these solutions is nowadays favored by the increasing availability of wearable sensors that can be easily inserted into everydaylife objects (watches, garments, optical sensors for presence, ambient measurements, etc) and of IoT architectures and Big Data algorithms. Moreover, the processing of this large amount of data requires the development of advanced techniques for biosignal analysis and the use of Artificial Intelligence to extract the relevant pathophysiological information.
Keywords – Electronic Medical Record, Health Big Data Analytics, Health Big Databases, Advanced and Smart Sensors, Body Area Network Sensors, Multivariate Biosignal Processing, Internet of Things (IoT) in Health, Artificial Intelligence and Machine Learning for Patient Classification
Session 3.3 – E-Health and IoT for Smart HealthCare
Paulo de Carvalho, University of Coimbra, Portugal
Nicos Maglaveras, Lab of Computing Medical Informatics and Biomedical Imaging Technologies, Aristotle University, Greece
ABSTRACT – Currently our healthcare system is undergoing vast changes mainly due to the COVID-19 pandemic. The last two years exposed the weaknesses of our healthcare system especially in terms of efficiency, access to medical data and information, efficient implementation of clinical protocols, prevention and follow-up. Further the explosion in multimorbid patients which has increased with COVID-19 the lack of pragmatic mechanisms to support integrated and coordinated care as well as the lack of wide uptake of eHealth and mHealth modules has hampered the healthcare system capacity to provide viable solutions both in the hospital and in the community.
The integration of wearable technologies, mHealth/eHealth systems, information from social media, Artificial Intelligence and the IoT ecosystem is necessary to address the current challenges. In this session we will fuse new eHealth systems, outcomes and R&D in the following axes:
1. Wearable technologies useable in eHealth/mHealth systems
2. Data models and semantic integration based on interoperable platforms supporting HL7/FHIR
3. Advanced and trustworthy data analytics approaches using ML/AI/DL
4. Medical decision making and efficient management of multimorbid patients for preventive and acute interventions
5. User requirements and User I/Fs enabling good and interoperable use of integrated healthcare
Keywords – Trustworthy AI, eHealth/mHealth systems, data models and semantics, IoT, Integrated Health and Connected Health.
Session 3.4 – Neural and Cognitive Engineering
Anna Maria Bianchi, Politecnico di Milano, Italy
Patricia Figuereido, Istituto Superior Tecnico, Portugal
Henrique Madeira, University of Coimbra, Portugal
ABSTRACT – The complexity of the neural systems, central and peripheral, requires proper and specific methodologies in order to be completely understood in its structure and functions. In particular, by integrating information from multimodal sources related to the brain or to other organs (i.e. ECG signal, respiration, skin conductance and others) allows to develop models for a better comprehension of brain responses to physical and cognitive stimuli. Extraction and classification of various biomarkers from these sources of information are useful to better understand and to try to quantify how central nervous system is involved and controls different tasks. Important applications are in a better understanding of cognitive mechanisms, in quantification of cognitive effort, in rehabilitation and in control of prostheses and orthoses as well as in the evaluation of complex central functions, like memory, mental states, emotion classification, sleep studies, etc.
Keywords – Brain functionality, Brain connectivity, Multimodal analysis, Brain models, Cognitive Neurophysiological Responses.
Session 3.5 – Advances in Medical Informatics for HealthCare Applications
Dagmar Krefting, University Medical Center, Germany
Silvana Quaglini, University of Pavia, Italy
ABSTRACT – Broad focus:
Medical Informatics covers the broad field of gathering, managing, and processing of medical data, information and knowledge to improve healthcare. Specific advances have been made in the recent years in:
– Interconnection and interoperability of health data along the full patient journey
– Artificial intelligence in healthcare applications, with particular attention to explainability of the results
– Integration of multiple data sources into healthcare applications
– mobile Healthcare applications and patient self-reporting
Focus on interoperability and standards:
Digital transformation is in full progression in healthcare worldwide. To leverage the full potential of digitalization in HealthCare Applications, it is important not just to provide paper-based information as an electronic file, but to make health information systems interconnected and provide data, information and knowledge structured and interoperable. The remaining barriers to the re-use of medical data must also be addressed in order to fully exploit them for the benefit of the entire population.
Keywords – Medical Informatics, Clinical Informatics, Clinical Decision Support Systems, Healthcare applications, Interoperability, Reusability.
Session 3.6 – Biotechnologies: advanced Devices and Sensors
Henri Korkalainen, University of Eastern Finland, Kuopio University Hospital, Finland
Massimo Mischi, University of Einthoven, The Netherlands
ABSTRACT – As our society is rapidly ageing, we are currently confronted with an epochal challenge to cope with exploding healthcare costs, paralleled by limited human resources to deploy the required healthcare services. To address these problems, healthcare technology is showing tremendous advances with the aim of reducing healthcare costs and demands by enabling the extramural transition of healthcare through the introduction of wearable and home-monitoring solutions for patient care and diagnostics. Indeed, advanced (multimodal) sensing technology, ranging from electrophysiological, motion, optical, ultrasound, up to sweat sensing, combined with dedicated signal processing/analysis, is a key enabler for the introduction of cost-effective solutions in healthcare, favoring early diagnosis and optimal treatment tailoring. Moreover, novel devices and solutions for minimally invasive intervention allow shortening patient recovery and hospitalization, reducing the associated costs while improving the quality of life.
Keywords – Biomedical sensors, biomedical diagnostics, patient monitoring, home monitoring, wearable sensors, minimally-invasive intervention, biomedical signal processing, multimodal sensing.
Session 3.7 – Bio-electromagnetic modeling
Paolo Ravazzani, IEIIT, CNR, Milano, Italy
Patrizia Lamberti, DIEM, University of Salerno, Italy
ABSTRACT – Computational bioelectromagnetic techniques are fundamental for a better comprehension of the interactions between electromagnetic fields and biological systems, allowing the conception and the investigation of new biomedical applications which make use of electromagnetic radiation to stimulate the biological systems and to transfer power and data in and out of the body.
Bioelectromagnetics modeling is of crucial importance also to provide the needed dosimetry related to the human exposure to electromagnetic fields. This session is designed to provide an overview of models and applications of electromagnetic fields for medicine and health.
Keywords – Bio-Electromagnetic Modelling, Numerical methods, Electric Stimulation, Magnetic Stimulation; Exposure to EM Field in Health Environment, circuital model.
Session 3.8 – Special Technical Session – Nanostructured devices and smart materials for biophotonics applications
Antonio d’Alessandro, Sapienza University of Rome, Italy
Stefan G. Stanciu, University Politehnica of Bucharest, Romania
ABSTRACT – The important advances that have occurred over the past decade in chemical engineering and nanotechnology have led to the advent of a wide palette of functional nanomaterials and nanostructued devices devoted to biomedical applications. As a result, the field of medicine is witnessing a paradigm shift, with such development paving the way for a new generation of diagnostics and therapeutic options with unprecedented performance. This technical session focuses on related topics, calling for contributions dealing with nanodevice-based prototypes and microsystems with applications in life and environmental sciences, with special focus on solutions devoted to high precision medicine, in which photonics is the key enabling tool. Contributions on latest hour characterization techniques that can solve subtle properties of smart nanomaterials and nanodevices are also welcomed.
In brief, the sessions will particularly welcome contributions on:
device and system technologies for bio-imaging and microscopy, chemical, biochemical and physical sensors, fiber sensors, lab-on-chip, optogenetics, optofluidics, image sensors, smart nanomaterials, including molecular composite materials with important optical properties for biophotonic applications.
Keywords – bio-imaging and microscopy; chemical, biochemical and physical sensors; fiber sensors; lab-on-chip; optogenetics; optofluidics; image sensors; smart nanomaterials; photonic integrated circuits.
Track 4: SMART DIGITAL COMMUNITIES
Barbara Masini, CNR-IEIIT
Francesco Masulli, CI Italy Chapter Chair
Alexey Vinel, Halmstad University, Sweden
Session 4.1 – Smart Education Technologies
Francesca Pozzi, CNR, Istituto Tecnologie Didattiche, Italy
Symeon Retalis, University of Piraeus – Department of Digital Systems, Greece
ABSTRACT – In the Technology Enhanced Learning research field, the notion of “smart education” is attracting a lot of attention, alongside other emerging concepts, including “smart learning”, “smart teaching”, “smart-e-learning”, “smart classrooms”, “smart universities”, etc. A number of conferences and academic journals focus on such a research area, which is constantly in expansion and whose boundaries are still quite blurred. Despite several definitions exist, the term ‘smart’ when associated to the educational context, does not only refer to the use of digital technologies, which – per se – might fail to lead to ‘smart learning’ experiences, especially if technologies are associated with traditional teaching methods. On the contrary, smartness in education usually implies technology-enhanced student-centred, interactive, multi-sensory and collaborative learning approaches, able to meet the new generations’ needs and to engage them in personalised, seamless, context-aware, ubiquitous learning activities (Cheung et al., 2021; García-Tudela, 2021; Giovanella, 2014; Kinshuk et al., 2016; Singh, & Miah, 2020; Spector, 2014). In order to contribute to such a lively debate, in this session we welcome theoretical perspectives, review articles, methodological developments, empirical research and exemplar evidence-based practices, in the field of technologies for smart education.
Papers submitted for publication are expected to promote reflection on how various technologies (IoT, AI, AR/VR, digital games, cloud computing, mobile devices, learning analytics, etc.) can contribute to create smart learning environments.
Keywords – Technology enhanced learning, smart learning, smart education, smart learning environment.
Session 4.2 – Cognitive Computing, Artificial Intelligence & Machine Learning
Paolo Maresca, University of Napels Federico II, Italy
Danilo Pau, ST Microelectronics, Italy
Mattia Rigotti, IBM Research, Switzerland
ABSTRACT – Cognitive computing (CC) is disrupting models and methods of training, skills and competences as it is a disruptive technology. It uses a mix of other technologies: the cloud, big data, IOT, and the connection between networks. Together with Artificial Intelligence (AI) and Machine Learning (ML), cognitive computing will help us solve highly complex problems and problems that are complex due to the large amount of data they present. There are many emerging technologies including: composite AI, AI Orchestration and Automation Platform, AI governance, generative AI, human-centered AI and synthetic data. Technologies that are expected to reach adoption in a period of between two and five years. While the current landscape is currently dominated by four technologies that include the operation of AI platforms, efficient use of resources, responsible AI and an approach that combines small & wide data. As an example of emerging technologies which occupied the top of expectations for 2021 (in the hype cycle for artificial intelligence see gartner.com) we find, Machine learning (ML) on the edge that is an increasingly important field for the embedded AI community due to its potential for increasing energy efficiency, privacy, responsiveness, and autonomy of edge devices. Edge ML has been focused on mobile devices, while in recent years, there have been expanding to ultra-low-power devices, such as sensors, micro-controllers and low power dedicated hardware.
Current focus is about inference on-device, and near or in-sensor computing, however the perspectives include on-device learning with reinforcement approaches. ML at the edge enables greater responsiveness and privacy while avoiding the energy cost associated with communication to the cloud, and quite importantly offers a scalable alternative to the paradigm based on availability of virtually un-limited computing and storage resources in the cloud.
This session is dedicated to the collection of works and case studies from emerging technologies and technologies of the current landscape around CC, AI & ML. Therefore, case studies, algorithms, applications, tools, software, hardware solutions for both paradigms: CC, AI & ML in the cloud vs at the edge are welcome.
Keywords – Artificial General Intelligence, AI TRISM, Physics-Informed AI, Cognitive computing, Cognitive computing Applications, Composite AI, AI Orchestration and Automation Platform, AI Skills, Machine customers, ModelOps, Responsible AI, AI Governance, Generative AI, Human Centered AI, Neuromorphic Hardware, Synthetic Data, Decision Intelligence, Transformers, Smart Robots, Knowledge Graph. Edge AI, AI Maker and Teaching Kits, AI teach AI, Deep Neural Network ASICs Digital Ethics AI Cloud Services, Deep Learning, Data Labeling and Annotation Services, Natural language Processing, Machine Learning, Intelligent Applications, Advanced Chatbots, Autonomous Vehicles, Semantic Search, Computer vision.
Session 4.3 – Semantic Web, Big data & Analytics
Francesco Colace, University of Salerno, Italy
Brij Gupta, National Institute of Technology Kurukshetra, India
ABSTRACT – Our society is characterized by an increasingly massive presence of pervasive systems that, thanks to the growing diffusion of the Internet of Things (IoT) paradigm, can collect and send data to systems capable of inferring actions related to the reference context. This huge proliferation of networked devices has led to the generation of what is commonly referred to as a “data deluge”. The term “Big Data” refers to a set of data that is exceptionally large or complex, the automatic processing of which is of great complexity if not through the adoption of appropriate techniques. A single IoT device can produce huge amounts of data for analysis, and when you have tens of thousands of interconnected devices, the challenge is finding the most valuable ways to collect, store, analyze, and use that data. Knowing how to manipulate and manage Big Data is the key to implementing predictive approaches and understanding user behavior. There is the need to develop techniques and methodologies able to allow a semantic analysis of data through the use of ontological structures and Machine Learning techniques. This track welcomes innovative and high-quality papers describing theory and practice of storing, accessing, searching, mining, processing, and visualizing big data. In particular, the track would like to papers that describe or demonstrate how ontologies and Semantic Web technologies can handle the problems arising when integrating massive amounts of multi-thematic and multi-perspective information from heterogeneous sources are.
Keywords – Internet of Things; Big Data; Ontology; Semantic Web; Context Awareness; Analytics; Artificial Intelligence.
Session 4.4 – Smart Living Technologies
Riccardo Bassoli, TU Dresden, Germany
Juan A. Cabrera Guerrero, TU Dresden, Germany
ABSTRACT – The study and design of 5G seems to have reached its end and 5G communication systems are currently under deployment. In parallel, 5G standardization is as Release 17, which is going to complete the definition and the design guidelines of the 5G. Because of that, the interest of the scientific and industrial communities has already started focusing on the future 6G communication networks. The preliminary definition of future technology trends towards 2030, given by major standardization bodies, and the flagship 6G projects worldwide have started proposing various visions about what 6G will be. 6G envisions the unification of the physical, digital and human worlds achieved through a new ecosystem of networks, sub-networks and device technologies. AI for network management and operations, 3D networking, and full network softwarization and programmability are the pivotal aspects of future 6G architecture. These technologies will ensure the support for very sensitive verticals like the ones related to the Tactile Internet. The Tactile Internet will enable remote health, Industry X.0, new transfer of skill, and the realization of digital twinning. Predictive networking will be fundamental to achieve very low latency in such context. Some very preliminary applications of molecular communications may become part of 6G infrastructure, considering the time-horizon 2030-2035 for the first deployment. Molecular communications will be employed in 6G communication networks to enhance the capabilities of remote health monitoring and control of industrial environments.
Keywords – 6G, Tactile Internet, network softwarization and programmability, 3-dimensional Internet of Things, molecular communications, in-network AI, predictive networking, post Shannon communications.
Session 4.5 – 5G and beyond Wireless Networks
Francesco Guidi, CNR-IEIIT, Italy
Ahmed Elzanaty, University of Surrey, UK
ABSTRACT – As of today, 5G wireless networks are on the way to be deployed around the world, permitting a set of diverse applications with different requirements, e.g., throughput and latency, but without making substantial changes to the available physical layer. In this direction, its evolution towards the so called beyond 5G networks will be a rendezvous of sensing, localization and communication capabilities enabled by the advent of new technologies, such as THz communications, extremely massive antenna arrays, and large intelligent surfaces. Indeed, it is widely assumed that localization and sensing will be an essential feature of 6G wireless networks to enhance new services, such as extended reality and intelligent transportation systems. In this thrilling context, this session aims to host diverse contributions revolving around new disruptive techniques and technologies that are expected for 5G and beyond networks including, but not limited to, mm-wave and THz communications, large intelligent surfaces, and joint sensing and communication.
Keywords – millimeter waves, THz Communication, Large Intelligent Surfaces, Joint Communication & Sensing.
Session 4.6 – Digital Twins for Smart Cities
Slawomir Nowaczyk, Halmstad University, Sweden
Thorsteinn Rögnvaldsson, Halmstad University, Sweden
ABSTRACT – The amount of data generated by Smart Cities has increased exponentially due to the usage of monitoring systems and sensing technologies, which are emerging together with Industry 4.0. The term Smart City builds upon rapid advancements in technology and the evolution of fields such as Artificial Intelligence and Machine Learning, intending to enhance citizens’ quality of life. The data produced today requires new concepts and AI-based exploitation methodologies that can be used to analyse and extract valuable knowledge about citizens, infrastructure, processes or organisations. Various actors are moving towards digitalisation, collecting Big Data to increase the efficiency of their operation. Data-driven methods are becoming more prominent in many areas, including predictive maintenance, mobility, healthcare, smart energy, etc. Dealing with big streaming data requires the combination of multiple data sources, the ability to handle concept drift. The increased knowledge about our cities allows us to create digital twins, models mirroring a system together with its environment, using two-way communication. In many scenarios, there is a large diversity in both the model configurations as well as their usage, which requires novel AI techniques. Challenges include low data quality, supervised and unsupervised machine learning, representation learning, domain shift, anomaly detection, visual analytics and high uncertainty in the labels.
Keywords – IoT and Industry 4.0; Predictive and Prescriptive Maintenance; Cyber-Physical Systems; Big Data; Explainable AI; Anomaly Detection; Concept Drift; Fault-Tolerant Control Systems; Active Learning; Visual Analytics and Interactive Machine Learning; Smart Cities; Information Modelling and Representation; Visualisation; Deep Learning Architectures for Digital Twins.
Session 4.7 – 3D Networks (terrestrial and aerial)
Franco Davoli, University of Genoa and CNIT S2N National Lab, Italy
Mario Marchese, University of Genoa and CNIT S2N National Lab, Italy
Ana Perez-Neira, Centre Tecnològic Telecomunicacions Catalunya, Spain
ABSTRACT – The fifth generation of mobile networks (5G) has accelerated the integration of the mobile and fixed network segments and further fostered the network “softwarization” process brought forth by Software Defined Networking (SDN) and Network Functions Virtualization (NFV). As 5G consolidates, the progress toward the sixth generation (6G) is currently characterized by the pursuance of enhanced capabilities and more demanding Key Performance Indicators (KPIs). In such framework, the presence of the space segment – including satellites on different orbits, constellations of nano-satellites, High Altitude Platforms (HAPs) and Unmanned Autonomous Vehicles (UAVs) – is gaining relevance as a new network dimension, from 2D to 3D. The coordinated operation of this space segment with the rest of the network and its integration within the Mobile Edge Computing (MEC) paradigm poses new challenges in terms of control, management, and orchestration of functionalities. The session aims at investigating some of the main issues involved by this 3D networking environment.
Keywords – 3D networks, Internet of Space Things, nano-satellites, HAPs, UAVs, MEC offloading, 3D architectural paradigms, network management and control, multi-layer and multi-tenant network orchestration, AI/ML in 3D network modelling and optimization.
Session 4.8 – Remote Sensing Methods and Applications
Gloria Bordogna, CNR-IREA, Italy
Dino Ienco, INRAE, UMR TETIS, France
ABSTRACT – We are in the era of Earth Observation and free geo big data generated periodically with high revisiting time. Just to cite some sources of remote sensing data, the Sentinel missions for Earth observation of the joint ESA/European Commission initiative Copernicus are bringing reliable, up-to-date and free high-and medium resolution images for ecosystem monitoring and managing, for agriculture, forests, land-use and land-cover change, coastal and inland waters monitoring, etc.. The PRISMA pre-operational medium-resolution hyperspectral imaging mission funded by the Italian Space Agency (ASI) provides a global observation capability for specific areas of interest in Europe and in the Mediterranean region. National, regional and local geoportals of public authorities provide upon requests, free LiDAR data. Nevertheless, to extract useful information from remote sensing data, methods capable of fully exploiting these systems and their complementarity are necessary to provide robust and operational semantic information that is easily interpretable by humans to take decisions. To this end, models physically based, data driven approaches laying under the umbrella of Artificial Intelligence methods and their combination constitute a challenge for remote sensing of the future.
The “Remote Sensing Methods and Applications” session of the “Smart Digital Communities” aims to bring together scientists, researchers and research scholars to exchange and share their experiences and research results on methods and techniques for the acquisition, calibration, filtering, fusion, analysis, interpretation and validation of Remote Sensing data (from both active and passive sensors on board of satellites, airbornes, UAVs, and LiDAR, SONAR, etc.) and applications in all areas of Earth Observation. It also provides an interdisciplinary forum for researchers and practitioners to present and discuss recent innovations, challenges, trends, and solutions adopted in the fields of Remote Sensing. Contributions describing original and unpublished results of theoretical approaches, conceptual models, empirical and experimental studies in Remote Sensing are relevant for the session and invited for presentation at the conference.
Keywords – Model-based remote sensing; Data-driven remote sensing; Deep learning for remote sensing; Multisource remote sensing data fusion; Hyperspectral remote sensing; LIDAR data analysis and applications; Earth Observation applications; Environmental monitoring; Precision agriculture; Event detection and tracking; Remote sensing image series analysis; Remote sensing data visualization methods; Advanced statistical modelling for remote sensing; Computing infrastructures for remote sensing; Interoperable remote sensing.
Session 4.9 – IoT and Smart Communications
Ali Balador, RISE, Sweden
Francesco Flammini, Mälardalen University, Sweden
ABSTRACT – Internet of Things (IoT) plays an important role in the current and future generation of information, network, and communication and applications. IoT is being employed in more and more areas making “Everything Smart”, such as smart home, smart city, intelligent transportation, environment monitoring, security systems, and advanced manufacturing. This track focuses on challenges for IoT applications and communication technologies needed to deveople smart IoT applications and Cyber-Physical Systems (CPS). As digital computing and communication become faster, cheaper and less power consuming, these capabilities are increasingly embedded in many objects and structures in the physical environment. CPS are co-engineered interacting networks of physical and computational components. These systems will provide the foundation of our critical infrastructure, form the basis of emerging and future smart services, and improve our quality of life in many areas.
Keywords – Systems, Technology, and Foundations of IoT; Emerging applications and use cases in IoT; Industrial 4.0 and Industrial IoT; IoT Sensing, monitoring, networking and routing; Edge computing/Fog computing; Smart cities, intelligent transportation and internet of vehicles; Artificial Intelligence, Machine learning and Evolutionary Computing; Cloud, Middleware and Networks for IoT; Communication and networking for IoT; MAC-layer and network-layer protocol design for IoT; Energy efficient communications for the IoT; Coexistence of wireless technologies in IoT; SDR, SDN and NFV as enabling technologies for IoT; Data security and privacy for IoT; Safety and security co-engineering; Dependability (real-time, reliability, availability, safety, security); Modeling, simulation, and visualization.
Session 4.10 – Smart Mobility and Transportation
Ion Turcanu, Luxembourg Institute of Science and Technology, Luxemburg
Florian Klingler, Paderborn University, Germany
ABSTRACT – Today’s transportation systems are currently experiencing significant transformations that are expected to affect how society will interact in the future. On the one hand, climate change, air and noise pollution, as well as traffic congestion, are putting more stringent requirements on the transportation systems, pushing towards more environmentally friendly mobility solutions. On the other hand, the integration of transportation engineering methods with vehicle electrification, shared mobility, as well as advances in areas such as Information and Communications Technologies (ICT), the Internet of Things (IoT), distributed ledger technology (Blockchain), have the potential to disrupt the mobility landscape and boost innovation. This session will be an opportunity for specialists coming from academia and industry to share their knowledge and experience in the area of smart mobility and transportation in modern digital and connected cities.
Keywords – digital city, smart mobility, internet of things, vehicular communications, intelligent transportation systems.