SS01 - Deep Learning Methods for Medical Image Analysis

Special Session Organized by

Yu-Dong Zhang, University of Leicester, United Kingdom; Shui-Hua Wang, University of Loughborough, United Kingdom;

With advancement in biomedical imaging, the amount of data generated are increasing in biomedical engineering. For example, data can be generated by multimodality image techniques, e.g. ranging from Computed Tomography (CT), Magnetic Resonance Imaging (MR), Ultrasound, Single Photon Emission Computed Tomography (SPECT), and Positron Emission Tomography (PET), to Magnetic Particle Imaging, EE/MEG, Optical Microscopy and Tomography, Photoacoustic Tomography, Electron Tomography, and Atomic Force Microscopy, etc. This poses a great challenge on how to develop new advanced imaging methods and computational models for efficient data processing, analysis and modelling in clinical applications and in understanding the underlying biological process.

Deep learning is a rapidly advancing field in recent years, in terms of both methodological development and practical applications. It allows computational models of multiple processing layers to learn and represent data with multiple levels of abstraction. It is able to implicitly capture intricate structures of largescale data and ideally suited to some of the hardware architectures that are currently available.

The focus of this special session is to carry out the research article which could be more focused on to the latest medical image analysis techniques based on Deep learning. In recent years Deep Learning method and its variants has been widely used by researchers. This Issue intends to bring new DL algorithm with some Innovative Ideas and find out the core problems in medical image analysis.

Topics under this track include (but not limited to):

  • Application of deep learning in biomedical engineering
  • Transfer learning and multi-task learning
  • Joint Semantic Segmentation, Object Detection and Scene Recognition on biomedical images
  • Improvising on the computation of a deep network; exploiting parallel computation techniques and GPU programming
  • New Model of New Structure of convolutional neural network
  • Visualization and Explainable deep neural network

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SS02 - Monitoring, Diagnosis, Prognosis and Resilient Control Methods and Applications

Special Session Organized by

Zhiwei Gao, University of Northumbria, United Kingdom; Shen Yin, Harbin Institute of Technology, China;

Industrial systems, such as aero engine, power network, chemical automation process, wind turbine systems, and so forth, are safety-critical systems. Therefore, there is an ever-increasing demand to provide a highlevel system reliability and safety for practical engineering systems by implementing real-time monitoring, fault diagnosis, prognosis and resilient control and management. This special session aims to provide a platform for the researchers and participants from both academic community and industrial sectors to report recent research and application progress in the field of condition monitoring, fault diagnosis, fault prognosis, resilient control and their applications.

Topics under this track include (but not limited to):

  • Model-based monitoring and fault diagnosis methods
  • Knowledge-based monitoring and fault diagnosis methods
  • Signal-based monitoring and fault diagnosis methods
  • Prognosis methods and remaining use life prediction
  • Resilient control methods
  • Health monitoring and management for industrial systems
  • Real-time implementation of monitoring, diagnosis and tolerant control in practical applications

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SS03 - Engineering of Software Products for Industry

Special Session Organized by

Anirban Sarkar, National Institute of Technology Durgapur, India; Narayan C. Debnath, International Society for Computers and Their Applications;

The discipline of Software Engineering has already established itself as a prime contributor towards sustenance and accelerated growth of infrastructural development process of enterprise system. Major areas of concerns regarding effectiveness of software products in the domains of their applicability generally emanate from the proper lack of understanding of the requirements and formulation of appropriate functional specializations. The complexity has further grown due to wide adoption of distributed computing paradigm in enterprise software. Absence of common consensus on proper process model for enterprise software and together with non–availability of sufficient software methodologies very often make the software development process difficult for enterprise level industrial software products.

This special session aims at addressing these critical issues concerning the engineering of enterprise software products in the perspective of industrial technology through bringing together the researchers and practitioners from industry and academia. Major areas of prime focus will be formal modeling, functional specifications, verification & validation, performance evaluation etc. The session will also concentrate on state-of-the art research trends making Industrial software products more effective.

Topics under this track include (but not limited to):

  • Business Process Modelling
  • Business Intelligence and Big Data
  • Interoperability and Service-Oriented Architecture
  • Enterprise Software Technologies for Industry
  • Trust, Security and Privacy of Industrial Software
  • Cloud Computing based Software Development
  • Internet and Web-Based Software Development
  • Knowledge Engineering for Industrial software
  • Tools for Industrial Software Product Development
  • Industrial Software Quality Management

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SS04 - Informatics Methods for IoT-enabled Health Care

Special Session Organized by

Dr Po Yang, Liverpool John Moores University, United Kingdom; Prof Guangjie Han, Hohai University, China; Prof Yun Yang, Yunnan University, China;

Significant advancements in the Internet of Things (IoT) have generated extensive opportunities for innovation across both academic and industrial communities, particularly in the health care field. Due to the exponential growth of wearable devices and mobile apps, a promising trend is the exploding role of the Internet-of-Things (IoT)—transforming the traditional hubs of healthcare, such as hospitals and clinics, to personalized health care systems, especially in the mobile environment. Current research in IoT-enabled health care is highly interdisciplinary, involving methodologies from computer science, engineering, information science, behavioral science, decision science, as well as many applied areas in medicine and public health.

A promising trend in these studies is the development of sophisticated techniques that will enable: (i) Cost-effective wearable biomedical devices. (ii) A highly secured, privacy-protected and trustworthy health care system. (iii) The effective and efficient analysis of long-term health data for supporting wise clinical decision-making. Many researchers have recently accepted the assignment of IoT-enabled system architectures into a four-layer organizational structure: sensing, networking, data processing and application.

It is of great importance to study informatics methods in each layer, seeking ways to empower successfully the utility of IoT enabled technology in healthcare. Such work is associated with issues in the areas of smart sensing technologies, network communication and data mining. In the long term, innovative informatics methodologies in IoT-enabled health care will benefit the establishment and enhance the efficiency of (a) practically interoperable IoT systems for care delivery and research, (b) adequate data and knowledge standards of self-empowerment, and (c) sound clinical decision-making foundations.

Topics under this track include (but not limited to):

  • Smart sensing technologies for IoT-enabled health care
  • Network communication for IoT-enabled health care
  • Exploration and management of health care data derived from innovative IoT health care systems
  • Control theories and tools for modelling, simulating and optimizing health care processes

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SS05 - Efficiency in Future Data Centers

Special Session Organized by

Tor-Björn Minde, RISE SICS North, Luleå, Sweden; Xiaojing Zhang, Department of Power Device, ABB AB, Västerås, Sweden; Chen-Wei Yang, Luleå University of Technology, Luleå, Sweden;

With the increasing expansion of information and communication technologies (ICT), the data center facilities are becoming a sizable part of the energy system. Datacenters are large loads which accounted for 3% of all electricity use worldwide and 2% of the global CO2 emissions, on par with the carbon footprint of the airline industry. It’s estimated that data centers will have the fastest growth in carbon footprint from across the whole ICT sector due to the increasing adoption of cloud computing and internet services. Future data centers require cutting-edge industrial automation, information, control and power system technologies to efficiently manage their power supply, cooling, security and other facilities. The efficiency of data centres has many contributors, such as heating, cooling, ventilation, data processing, and air-conditioning, which can be improved via active load balancing, energy consumption and electrical power management. This special session is organized to address the current challenges and problems of this new and fast growing industry from the perspective of efficiency. We invite researchers and technologists from a broad range of expertise and specializations to discuss and share their ideas, found problems, challenges and solutions in this multidisciplinary arena of research and development.

Topics under this track include (but not limited to):

  • Data center energy efficiency and performance metrics
  • Data center power infrastructure (power supply technologies, UPS solutions, power quality, power losses, alternative data center designs)
  • Data center and power grid: demand response, smart load, load balancing
  • Data center modeling: servers, cooling, entire infrastructure, data center dynamics (fan motors, pumps, UPS, backup generators)
  • Data center asset management, maintenance and operation
  • Thermal modelling of the server rooms
  • Industrial automation for data centers
  • Building management system in data centers
  • Artificial intelligence applications in Data Centers

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SS06 - Efficient Multimedia Sensing and Computing on Industrial Applications

Special Session Organized by

Tommy W. S. Chow, Department of Electronic Engineering, City University of Hong Kong, Hong Kong; Zhou Wu, Department of Automatic Control, Chongqing University, Chongqing, China; Jingjing Cao, School of Logistics Engineering, Wuhan University of Technology, Wuhan, China;

In most real-world industrial applications, such as multi-modal retrieval, traffic surveillance, video advertisement embedding, and automatic driving systems, information usually comes through multimedia data. For example, Web images in a multi-model retrieval system usually involve textual descriptions and multi-label tags; the videos in traffic surveillance contain both acoustic and visual signals; and sensory perceptions typically used in automatic driving system may need extensive multi-media data from multi-channel inputs in visual, auditory and motor pathways. Thereby, how to characterize the property of multimedia data so that it can be managed to enable different learning tasks of industrial applications is essential. This requires research to develop robust and sophisticated models to classify, retrieve and understand multi-media information. Moreover, with the explosion of multimedia data, the efficiency of model should also be considered so that systems can cope with the ever-demanding real-world industrial applications. In this special section, we look for cutting-edge techniques to efficiently handle multimedia data-information for sensing and computing in industrial applications.

Topics under this track include (but not limited to):

  • Multi-media information retrieval
  • Multi-label and multi-model classification
  • Deep learning-based image classification, semantic segmentation and object detection
  • Video advertisement embedding
  • Video surveillance
  • Image processing for unmanned drones
  • Modeling and optimization of industrial applications
  • Vision-based recognition in cashier-less retail
  • Multi-sensor data fusion

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SS07 - 5G for Vertical Industry Services

Special Session Organized by

Dr. Yulei Wu, University of Exeter, United Kingdom; Dimitra Simeonidou, University of Bristol, United Kingdom; Osvaldo Simeone, King"s College London, United Kingdom; Payam Barnaghi, University of Surrey, United Kingdom;

The International Telecommunication Union (ITU) has identified three broad use cases: enhanced mobile broadband (eMBB), ultra-reliable and low-latency communication (uRLLC), and massive machine-type communications (mMTC). 5G networks are expected to allow the coexistence of these use cases over the same physical infrastructure. However, different vertical industry services have diversified requirements. For example, the applications like self-driving cars and remote surgery in uRLLC use case have stringent requirements on availability, latency and reliability. The applications like e-health and public safety in mMTC use case bring additional challenges on supporting a large number of Internet of Things (IoT) connections within a coverage area. In order to make 5G a big success and support the added value of 5G over previous generation networks by enabling various vertical services, many challenges still need to be investigated in terms of algorithms, architecture, and collaboration with other contributors over the end-toend path.

This Special Session is devoted to the most recent developments and research outcomes addressing the related theoretical and practical aspects on 5G for supporting various vertical services. It also aims to provide worldwide researchers and practitioners an ideal platform to innovate new solutions targeting at the corresponding key challenges.

Topics under this track include (but not limited to):

  • Enhanced Mobile Broadband (eMBB)
  • Ultra-Reliable and Low-Latency Communication (uRLLC)
  • Massive Machine-Type Communications (mMTC)
  • Vertical Applications and Services in Industry, Healthcare and Smart Environments
  • Large-scale mMTC deployments
  • Enabling Technologies for 5G Vertical Industries
  • Architecture, Standards and Business Models for 5G Vertical Industries
  • Security, trust and privacy for 5G Vertical Industries
  • Simulations, Testbeds and Experimentations

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SS08 - Practical and theoretical aspects of social and economic foundations of cyber-physical systems and Industry 4.0

Special Session Organized by

Juho Mäkiö, University of Applied Sciences Emden / Leer, Germany; Jolanta Kowal, University of Wroclaw, Poland; Rafał Maciąg, Jagiellonian University, Poland;

Cyber-physical systems (CPS) and Industry 4.0 become nowadays pervasive providing solutions to multiple domains having a simultaneous impact both on the business and on the society. This impact can be seen in multiple fields. Some of them are obvious, like for example, the impact on the human capital development and socioeconomic growth and novel business models taking advance from the new technological approaches. The ongoing development is strongly influenced by enterprises developing novel digital solutions that apply novel technical and organizational innovations. However, the solutions require continuous development of human capital as high innovation capability is required on organizational and on individual levels.

However, a deeper theoretical analysis of the essence of CPS and Industry 4.0 makes indispensable also the need to rethink some basic phenomena building up the foundations for the further social and economic analyses. The shift of understanding concerns issues like the role of the human in the context of the development of technologies like Artificial intelligence (AI) making urgent such problems as privacy, subjectivity, legal responsibility, etc. Knowledge is a further issue demanding rethinking in the light of the artificial cognitive systems. Technologies like blockchain put in question traditional flows of goods. Such issues and changes create unprecedently new foundations for our societies and their organizations and thus demand fundamental scientific reflection.

This Special Session is initiated with the aim to connect researchers, practitioners and industrialists to discuss the extended and deeper foundations of the social and economic aspects and issues related with the recent technical development containing such fields as data understanding and usage, artificial cognitive systems and their influence, human in the loop with the different systems and many others.

Topics under this track include (but not limited to):

  • Innovative Business Models
  • Industry 4.0
  • CPS and Entrepreneurs
  • Human Capital Development
  • Social, humanistic and economic aspects of digitization, human in the loop, artificial cognitive systems, new definitions and approaches

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SS09 - Distributed architectures in electric power systems: the key components

Special Session Organized by

Dmitry Kholkin, Center for Strategic Research North-West, Russia; Asya Tertyshnaya, Center for Strategic Research North-West, Russia;

Distributed energy, including small-scale power generation, energy storage systems, adjustable load on the side of end users will play the crucial role in upcoming development of power industry. These solutions, being interconnected and integrated into the centralized grid represent an untapped resource for raising the electrical efficiency of power systems and thus have a potential to address the challenges of Energy Transition.

This special session is aimed to determine key technologies and components that are crucial for designing the distributed architectures of electric power systems.

Topics under this track include (but not limited to):

  • Transaction platforms and services in distributed architectures of electric power systems
  • Energy routers and hubs
  • Distributed ledger technologies in architectures of electric power systems
  • Ontological services for digital environment in energy sector
  • Virtual Synchronous Machines
  • Dynamic and static stability maintenance in electric energy systems

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SS10 - Integration of Software Agents and Low-Level Automation Functions

Special Session Organized by

Paulo Leitao, Instituto Politécnico de Braganca, Portugal; Thomas I. Strasser, AIT Austrian Institute of Technology, Austria; André Rocha, Uninova, Portugal;

Industrial agent-based solutions allow the distribution of intelligence supporting the design of complex large scale Cyber-Physical Systems (CPS) by decentralizing the control system by autonomous and cooperative entities, differing from the conventional approaches due to its inherent capabilities to adapt to emergence without external intervention. These solutions expand the potential application domains of Multi-Agent Systems (MAS) and at the same time adds the required flexibility, robustness and responsiveness to industrial automation systems.

In this CPS context, the deployment of industrial agents, i.e., software agents connected to the physical world, follows the conventional practice that suggests a two-layered approach, where the agents are responsible to provide intelligence and adaptation features, and a low level control layer is responsible to provide the realtime control operation, typically executed in small embedded control devices, e.g., industrial PCs or Programmable Logic Controllers (PLCs). A key aspect in such two-layer architecture is the interaction interface between the software agents and the low-level automation devices. There is no universal and standardized way to interconnect these two layers, and the IEEE P2660.1 Working Group is being work in defining recommended practices to solve the interface problem when applying industrial agents in the context of CPS.

In this context, the objective of this special session is to provide an open discussion forum where researchers and industrial partners can share their own perspective, visions and experiences on developing interface practices to integrate industrial software agents with low-level automation functions, in the CPS context. Papers (4-6 pages) reporting experiences, demonstrations and best practices are welcome to support the discussion and assess the applicability of these interface practices for fulfilling the above requirements (it is strongly advisable to have a video or live demo for each paper in order to support a posterior discussion and exchange of experience/knowledge).

Topics under this track include (but not limited to):

  • Integration of software agents in industrial low-level automation functions
  • Interoperability in industrial agent-based CPS solutions
  • Assessment of industrial agent-based CPS solutions
  • Evaluation metrics for assessing the integration of software agents in industrial environments
  • Performance measurement in industrial agent-based CPS solutions
  • Experiences from agent integration in various applications fields like manufacturing, power and energy systems, building automation, etc.

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SS11 - Low Power Smart Sensing for the Industry 4.0

Special Session Organized by

António Espírito-Santo, University of Beira interior, Dep. Eng. Electromechanical, Institute of Telecomunications, Portugal; Vincenzo Paciello, University of Cassino and Southern Lazio, Italy; Reza Abrishambaf, Miami University, Dep. of Engineering Technology, USA; Victor Huang, Sage Technologies, USA;

Low power wireless sensor networks are essential to the industry's 4.0 operability. These infrastructures, associated with concepts such as the Internet of Things and the Cyber-Physical Systems, make the smart factory a reality. This is a multidisciplinary research field, through which it is possible to achieve significant progress. Through low power intelligent sensor networks, it is possible to acquire the necessary information for the collaboration in the production process. In this scenario, the adoption of low power wireless networks with a high number of nodes, some of them with energy restrictions, has given rise to the developed of new energy harvesting methods and associated energy management mechanisms. On the other hand, the cooperation of the various elements of the network is only possible if standards are adopted to promote integration and, simultaneously, interoperability mechanisms are provided, allowing the co-habitation of different standards. At the same time, new development platforms are available to test and validate aspects such as: power consumption, communication management schemes, wake-up radios energy performance, or, standard certification.

This special session aims to provide a forum for discussion that will attract scholars and industry practitioners for sharing and discussing the latest advances in this scientific field. Participants will have space to demonstrate, in the room, remotely, or offline, the operation of solutions developed by them.

Topics under this track include (but not limited to):

  • Low power wireless sensors
  • Energy harvesting mechanisms
  • Hardware/software design and implementation of low power smart sensors
  • Security issues under low power operation
  • Parallel vs distributed systems
  • New educational technologies for low power smart sensors in Industry 4.0
  • Standards, test, and certification of low power smart sensors

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SS12 - Innovative Technologies and Methods for Zero Defect Manufacturing on Industrial Cyber-Physical Systems Context

Special Session Organized by

Paulo Leitao, Instituto Politécnico de Braganca, Portugal; Christian Eitzinger, PROFACTOR GmbH, Austria; Salvador Izquierdo Estallo, ITAINNOVA, Spain;

The quality of products is a key factor for success in manufacturing industry along with the reduction of material waste, re-works, rejects and stocks, leading to a demand for the development of zero-defect manufacturing (ZDM) strategies at system level.

Under the umbrella of the 4ZDM cluster, several European research projects, aligned with the Industry 4.0 principles, are making efforts for the integration and convergence of technologies for measurement and quality control, for data collection, storage and analysis, at single process and at factory level, aiming to guarantee high quality of products without interfering, actually improving, the production efficiency of the entire system.

In this context, the objective of this special session is to provide an open discussion forum where researchers and industrial partners can share their own perspective and visions on developing methodologies, designs and roadmaps to address innovative technologies and methods for ZDM on the industrial cyberphysical systems context. This special session is organized under the scope of the 4ZDM cluster, and particularly involving the following 3 European projects: GO0DMAN (aGent Oriented Zero Defect Multi-stage mANufacturing; http://go0dman-project.eu/), STREAM-0D (Zero Defect Manufacturing Solution;http://www.stream-0d.com/) and ZAero (Zero-defect manufacturing of composite parts in the aerospace industry; http://www.zaero-project.eu/).

Topics under this track include (but not limited to):

  • Multi-agent systems architectures for ZDM environments
  • Big data analytics for ZDM environments
  • Artificial intelligence methods for intelligent predictive maintenance in ZDM
  • Real-time machine condition monitoring & diagnostic for single and multistage environments
  • Smart inspection systems for smart manufacturing environments
  • Advanced knowledge representation methodologies and ontologies
  • Self-adaptive and self-reconfiguration methods for smart multi-stage manufacturing environments
  • Virtual modelling and simulation (Digital Twins) for ZDM scenarios
  • Assistance systems (non-robotic) for manual production tasks
  • Computer-Aided Engineering (CAE) for manufacturing
  • Reduced Order Modelling (ROM) methodologies focused on manufacturing processes
  • Dynamic Data Driven Application Systems (DDDAS) for improved quality control and ZDM
  • Model-based control for ZDM

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SS13 - Team autonomous robots coordination control and navigation

Special Session Organized by

Prof. Guo-Shing Huang, National Chin-Yi University of Technology, Taiwan; Prof. Cheng-Siong Lee, Monash University, Melbourne, Australia;

Multiple autonomous robots working in parallel can provide more efficient performance for an assigned task than a single robot. For this reason, it has become a high potential applications in industry. However, the first challenge for this issue is to assign actions to robots under team coordination simultaneously. The environment mapping for robots navigation and path planning under unknown environments is considered as the second chanllenge. To resolve these problems, a self-organizing map based feature achieving a real-time collision-free robot path from the dynamic task assignment of multi-robot may give a good solution. Accordingly, it is an important mission to develop algorithms to incorporate task assignment, path planning, and multi-robot control approaches for autonomous robots.

The coordination communication in multi-robots should be able to escape individual robot ollision when planned in a decentralized manner. The algorithm should also place the different robots judiciously for avoiding near-optimal collision. The time consuming and completion efficiency should be taken account for a good coordination strategy, where it should not overly depend on a robot. At the same time, autonomous navigation for team mobile robots can not be ignored. Some tasks by a set of autonomous robots such as material transportation, exploration or mapping reconstruction should be realized. Additionally, some topics should be studied further, for example, probabilistic localization, environment recognition, sensor based mapping, global wireless sensor systems, vision-based strategies, energy converter and control systems, biomedical engineering, etc.

This session is looking forward to innovative techniques for team robots to explore environments more efficiently. All related research outcomes are welcome.

Topics under this track include (but not limited to):

  • Autonomous robots’ coordination and navigation
  • Signal Processing in Mechatronics and Robotics Control
  • Environment recognition for multi-robot navigation and path planning Robot path planning
  • Strategies of multi-robot task allocation and implementation
  • Machine-learning approaches to multi-robot coordination
  • Tracking control of a multi-robot system
  • Simultaneous localization and mapping (SLAM) for mobile robots
  • Deep learning in robot path planning and control
  • Remote robot monitoring and control
  • Sensors measurement technology
  • Image measurement and control technology
  • Sensors measurement technology
  • Optimal control and system management
  • Vision-based recognition
  • Wearable exoskeleton robot
  • Biomedical measurement engineering
  • Energy converter and control systems
  • Other automation control methods and applications

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SS14 - Holistic approach to control and analysis of complex systems with data mining methods

Special Session Organized by

Prof Gennady E. Veselov, Institute of Computer Technologies and Information Security of the Southern Federal University, Russia; Prof Andrés Montoyo Guijarro, University of Alicante, Spain; Dr. Juan José Domínguez Jiménez, High School of Engineering, University of Cadiz, Spain;

According to modern system engineering concepts, the world around us is holistic and indivisible. However, in order to study individual phenomena of the world around, separation into its constituent parts is performed, i.e. its structuring. This process leads to the representation of the system as a set of hierarchically located interacting subsystems. Meanwhile, both vertical and horizontal structured ordering of these subsystems is possible. The behavior of each subsystem, regardless of the type of structuring, is described by a corresponding model with variables and parameters immanent to a particular level of abstraction.

It should be noted that while controlling complex dynamic systems, internal contradictions and competitive physical processes may arise. At the same time, the existing methods of system analysis do not allow fully taking into account such contradictions. The concept of control in complex systems is inseparably connected with the concepts: information, organization of functioning, and purpose. However, there is not always a clear understanding of the essence of information processes associated with control. In this regard, it is necessary to emphasize that information should be considered as a means of achieving the goal, while mandatory considering its value in the information analysis of control processes. It is due to the fact that only specifically useful information applied to achieve the goal is important for control. Data mining is of particular importance for such systems, since they consist of a combination of the large number of hierarchically dependent local subsystems that have a certain degree of autonomy and are interconnected by means of organization, based on the current hierarchy of goals.

Properly constructed, mutually agreed purposeful control of subsystems, based on data mining of information received from the system and the external environment, will ensure the specified properties of the technological homeostasis of the entire system.

Topics under this track include (but not limited to):

  • Holistic modelling of complex systems
  • Control of complex industrial systems
  • Intelligent control of complex industrial systems
  • Clustering and unsupervised learning
  • Knowledge processing
  • Building recommendation systems
  • Pattern recognition
  • Classification
  • Feature extraction
  • Search of associative rules
  • Genetic algorithms
  • Fuzzy modelling and control, etc.
  • Text and web mining
  • Bioinformatics
  • Intelligent transportation systems
  • Robotics and mechatronics
  • Electric power systems
  • Telecommunication systems

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SS15 - Smart Automation, Control, and ICT Concepts applied to Power and Energy Systems

Special Session Organized by

Marco Cupelli, E.ON Energy Research Center, RWTH Aachen University Germany; Thomas Strasser, Center for Energy, AIT Austrian Institute of Technology;

The power and energy systems domain is experiencing a major change in terms of operation and planning. The advancement into a so called smart energy system or a smart grid produces new challenges. With the introduction of distributed, renewable generation (e.g., solar, wind, small hydro power) and controllable loads (e.g., electric vehicles, energy storage systems) new and advanced automation, control, and Information and Communication Technology (ICT) concepts and corresponding methods are required in order to cope with these new challenges. This special session targets this challenging, interdisciplinary field.

Topics under this track include (but not limited to):

  • Advanced information and communication systems
  • Distributed automation concepts
  • Distribution automation and SCADA systems
  • Demand-side management concepts
  • Holonic, multi-agent and service-oriented concepts
  • Self-healing systems covering fault location, isolation, service restoration, etc.
  • Application of smart grid related automation standards (e.g., CIM, IEC 61850, OPC UA, IEC 61499)
  • Modelling, simulation and validation concepts for cyber-physical energy systems

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SS16 - Workers’ safety, health and well-being in Industry 4.0

Special Session Organized by

Beatrice Lazzerini, Department of Information Engineering, University of Pisa, Pisa, Italy; Francesco Pistolesi, Department of Information Engineering, University of Pisa, Pisa, Italy;

Every day, just under 900 people die in the workplace as a consequence of an occupational accident. Non-fatal accidents yearly involve 317 million workers. But there is one more silent killer today: work-related stress. Stress affects almost 30% of workers, and can cause serious consequences, such as depression, panic, anxiety, and can increase up to 23% the risk of heart attack. The total number of working days lost due to work-related stress in 2017/18 was 15.4 million days.

Sensor networks and wearable devices, together with artificial intelligence (AI) technologies, are pervasive in Industry 4.0 to control and optimize many industrial processes. But in the next-generation industry, these technologies should also play a key role to monitor: i) the workers’ behavior; ii) the workers’ psychological state, and their stress level.

Continuously monitoring the workers’ behavior can prevent the injuries and, what is more important, can save the workers’ lives. The data collected by wearable sensors (e.g., accelerometers, gyroscopes) can be processed by AI techniques and systems to detect whether a worker performs a task safely or unsafely. Risk managers can thus identify the workers at risk—who need immediate safety training—, and teachers can adapt the safety training to each worker’s needs, and then measure the learning effectiveness in terms of the resulting increase in risk awareness.

On the other hand, wearable sensors can also measure various physiological signals (galvanic skin response, heart rate and so on) that AI-based systems can use to constantly monitor the workers’ psychological state and stress level. This is crucial to detect the workers that are stressed or that probably will, thereby preventing stress-related ill states.

Topics under this track include (but not limited to):

  • Wearable sensors and smart technologies for work-related stress detection, prediction and prevention
  • Wearable sensor data analytics for workers’ risk and stress management
  • Sensor network-based solutions to monitor the workers’ stress and risk awareness
  • (Multi-criteria) decision making and decision support systems for sensorbased risk management and stress management

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SS17 - Intelligent Application of Consumer Wireless Technologies for Industry

Special Session Organized by

Adnan M. Abu-Mahfouz, Council for Scientific and Industrial Research, South Africa; Dong Yue, Nanjing University of Posts and Telecommunications, China; Gerhard P. Hancke, University of Pretoria, South Africa;

There are a number of new wireless technologies aimed primarily at connecting consumers and creating commercial networks, such as LoRa, Sigfox, LTE-M and NB-IoT, but these technologies can also be applied to existing and new industrial applications and Industrial Internet of Things (IIoT). However, to do so would require systems to ensure network performance, such as reliable connectivity and latency, appropriate intelligent information processing, in addition to device management. The main objective of this special session is to provide a forum to share and discuss new ideas, use cases and research results on all aspects of industrial wireless.

Topics under this track include (but not limited to):

  • Intelligent and innovative applications for consumer wireless in industrial applications
  • Intelligent information processing for these application
  • Software defined networking, network functions virtualization and network slicing for IIoT
  • Edge, fog and cloud computing for IIoT
  • Energy efficiency and energy harvesting for LoRa, Sigfox, LTE-M and NB-IoT
  • Simulation, testbeds, prototypes, field trails, and other performance analyses
  • Channel characterisation and modelling in industrial environments

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SS18 - Communications and Computing for Fog Based Control Systems

Special Session Organized by

Kan Yu, La Trobe University, Australia; Michele Luvisotto, ABB Corporate Research, Sweden; Guodong Zhao, University of Glasgow, UK; Federico Tramarin, University of Padova, Italy; Zhibo Pang, ABB Corporate Research, Sweden, and Royal Institute of Technology (KTH), Sweden;

To meet the critical requirement in latency, reliability, safety, and security, fog/edge-based deployment of industrial cyber physical systems is demanded. The emerging higher performance wired and wireless communications, fog/edge computing, hardware and software virtualization are the fuels of this trend. This special session is targeted at researchers and industrialists to present and discuss research work related to innovative approaches, theory and methodology of applying the above advancing technologies in industrial domains.

Topics under this track include (but not limited to):

  • Concepts, modeling, simulation and validation for fog-based control systems
  • High performance industrial wireless and wired communications
  • Emerging cellular networks for critical control systems
  • Convergence of industrial wired and wireless networks
  • Integration of cellular networks with industrial ethernet
  • Resource allocation in fog computing for industrial controls
  • Cross layer design of communications and computing with enhanced performances
  • Real-time data storage, distribution, and analytics
  • Virtualization of communication and computing resources
  • Downloading application from cloud to fog/edge platforms
  • Container technologies with short latency
  • Security solutions for fog-based control systems
  • Machine learning techniques in hard real-time closed loop control
  • Partitioning of machine learning frameworks over fog/edge infrastructure
  • Emerging applications of fog-based control systems in healthcare, mining, logistics, transportation, energy, manufacturing, etc.
  • Interoperability and standardization for fog-based control systems

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SS19 - Innovative Service Life Cycle Management and Applications in Cloud Manufacturing

Special Session Organized by

Yongkui Liu, Xidian University, China; Lin Zhang, Beihang University, China; Lihui Wang, KTH Royal Institute of Technology, Sweden; Xun Xu, The University of Auckland, New Zealand; Lei Ren, Beihang University, China;

Cloud manufacturing is a novel advanced manufacturing paradigm that encapsulates distributed resources into cloud services and provides them to consumers over the Internet through centralized management and operation. Service is a core concept in cloud manufacturing, and innovative, effective management of services in different stages throughout the entire life cycle (ranging from service creation, service application, service evolution, to service demise) is critical for the successful implementation and operation of cloud manufacturing. During the past years, many new technologies such as deep learning and its fusion with reinforcement learning, block chain, big data analytics, digital twin were growing at an unprecedented pace, which provides new enabling technologies for innovative service life cycle management and applications. In this context, this special session aims to provide a forum for people from academia and industry to share their innovative research outcomes on service life cycle management and applications in cloud manufacturing using the above-mentioned new technologies.

Topics under this track include (but not limited to):

  • Data collection, processing and analysis
  • Precise control based on edge intelligence
  • Service digital twin modeling and digital description
  • Service big data analysis
  • Service searching, matching, selection, composition and scheduling
  • Service transaction
  • Service evolution
  • Service-based supply chain management
  • Service safety, security, and trust management
  • Machine learning and block chain for service life cycle management
  • Block chain-based service management architecture
  • Knowledge graph-based service knowledge management
  • Service-based creation of APPs for manufacturing
  • Machine learning and block chain-based service life cycle applications

Complete Details

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