Engineering of Software Products for Industry

Special Session Organized by

Narayan C. Debnath, Eastern International University, Vietnam and  Anirban Sarkar, National Institute of Technology, India

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Focus

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, titled “Engineering of Software Products for Industry”, 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 focus, but not limited to, will be formal modelling, 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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Tolerant Control, Condition Monitoring and Diagnosis for Industrial Systems

Special Session Organized by

Zhiwei Gao, University of Northumbria at Newcastle, UK and  Xiaoxu Liu, Shenzhen University of Technology, China

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Focus

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 high-level system reliability and safety for practical engineering systems by implementing real-time monitoring, fault diagnosis, prognosis and tolerant 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, tolerant control and their applications.

Topics under this track include (but not limited to):
  • Machine-learning based monitoring and fault diagnosis
  • Signal-based monitoring and fault diagnosis
  • Model-based monitoring and fault diagnosis
  • Prognosis methods and remaining use life prediction
  • Resilience of safety-critical systems
  • Health monitoring and management for industrial systems
  • Real-time implementation of diagnosis, prognosis and tolerant control in engineering applications

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Time-sensitive Computing and Communications for Future Industrial Systems

Special Session Organized by

Dave Cavalcanti, Intel Corporation, USA and  Iñaki Val, IKERLAN, Spain and  Raheeb Muzaffar, Silicon Austria Labs, Austria

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Focus

Recent advances in computing, artificial intelligence, and wireless communications are enabling a digital transformation in industrial systems. More and more applications will require synchronous and real-time computing and communications. Future autonomous mobile robots, smart manufacturing, autonomous vehicles, AR/VR experiences are expected to leverage virtualized computing across wireless and wired networks with deterministic low latency and high reliability. This special session aims to enable a discussion on research challenges, new paradigms and novel solutions involving edge computing, AI, communication technologies to enable future time-critical applications and experiences in industrial environments.

Topics under this track include (but not limited to):
  • Time-critical industrial applications, robotics, and autonomous systems
  • Time-sensitive networking (TSN) and Deterministic Networking
  • Wireless TSN
  • Low latency and high reliability with Wi-Fi, Wi-Fi 6/6E, Wi-Fi 7
  • 5G and 6G Ultra-reliable Low Latency Communications
  • Compute-Communication Co-design
  • Orchestration and resource allocation for Edge computing and networks
  • AI techniques for optimization of time-critical computing and communication resources
  • Performance evaluation, measurement methodologies, and testbeds for time-sensitive systems

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Internet of Things (IoT) for Prognostics & System Health Management (PHM) in Industrial Applications

Special Session Organized by

Tangbin Xia, Shanghai Jiao Tong University, China and  Dong Wang, Shanghai Jiao Tong University, China

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Focus

As an emerging field in industrial applications, Internet of Things (IoT) and Prognostics & Health Management (PHM) are gaining interest from academia and industry. An effective PHM framework integrating with IoT techniques such as real-time monitoring, automotive detection and preventive maintenance is facing the challenges from the Industrial Internet, artificial intelligence and advanced manufacturing paradigms. The special session on the Internet of Things (IoT) and Prognostics & Health Management (PHM) in Industrial Applications invites original papers dealing with prognosis, operation, maintenance, reliability and IoT-based systems of the typical industrial application scenarios. The topic has become a mainstream research direction during the last decade. The special issue aims to present recent developments and achievements of this topic in new hybrid industrial technologies such as Industry 4.0, cyber-physical systems and intelligent manufacturing systems. This special issue aims at presenting the state-of-the-art theoretical development and applications in this area and bringing academic and industrial practitioners to tackle difficult problems of international concerns. Submissions of real-world case studies are strongly encouraged. Application areas of interest will include but will not be limited to intelligent prognosis, maintenance policies, operation analysis, digital twins and Industrial Internet of Things (IIoT). We welcome both original research articles and review articles.

Topics under this track include (but not limited to):
  • IoT Infrastructures and technologies for industrial applications
  • Model-driven or data-driven approaches in PHM
  • Advanced signals processing techniques
  • Artificial intelligence in real-time prognosis
  • Fault detection, classification and location
  • Intelligent maintenance policies in industrial applications
  • Industrial internet of services and service-oriented architectures
  • PHM applications of advanced manufacturing paradigms
  • Industrial digitalization, digital twins in industrial applications
  • Challenges, visions and roadmaps in the context of IoT and PHM

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Informatics Methods in Internet of Things (IoT) enabled Healthcare

Special Session Organized by

Po Yang, University of Sheffield, UK and  Jun Qi Xi’an JiaoTong , Liverpool University, Suzhou, China and  Khan Muhammad , Sejong University, Seoul, Republic of Korea and  Yun Yang, Yunnan University, Kunming, China

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Focus

The aim of this Track is to gather researchers and practitioners to report on recent achievements and requirements in the development of Robotics and Mechatronics systems in the industrial context, comprising control, path planning, sensing, manipulation and mobile robotics issues.

Topics under this track include (but not limited to):
  • Smart sensing technologies for IoT enabled healthcare: Submissions that address issues around the collection, observation and recording of IoT enabled healthcare information, in an automatic, intelligent, unobtrusive, non-invasive and cost-effective way, are sought
  • Network communication for IoT enabled healthcare: Papers that study problems on how to interconnect large-scale heterogeneous network elements and transmit healthcare Information efficiently in an IoT environment are solicited
  • IoT healthcare data exploration and management: Articles that concern issues on managing, extracting, analyzing, visualising and communicating complex and diverse IoT healthcare data and how to convert data into knowledge for clinic decision support and disease management.
  • Innovative IoT healthcare systems and technologies: Submissions that concentrate on using interdisciplinary knowledge for the design, modelling, development and evaluation of innovative IoT healthcare system framework, architecture and applications

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Modelling and Simulation for Smart Manufacturing

Special Session Organized by

Yongkui Liu, Xidian University, China and  Lin Zhang, Beihang University, China and  Jamal Deen, Mcmaster University, Canada and  Longfei Zhou, Duke University, USA and  Lei Ren, Beihang University, China

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Focus

Modelling and simulation is the use of models (e.g., physical, mathematical, or logical representation of a system, entity, phenomenon, or process) and simulations for managerial or technical decision making. The great value of M&S in manufacturing has long been recognized. Over the last decade, the advent of information and communication technology such as smart sensors, Internet of Things, cloud computing, big data, artificial intelligence, cyber-physical systems have been shaping many fields, including manufacturing. In line with this trend, smart manufacturing emerged. As a comprehensive information technology that integrate computer, model theory, and scientific computing, modelling and simulation have been widely applied in all stages of product life cycle covering design, production, testing, maintenance, procurement, and sales. In the context of smart manufacturing, modelling and simulation has been revived and found many new applications, such as modelling and simulation-based system of system engineering and digital twin, which enable the digitalization, normalization, traceability, high efficiency, low cost, and intelligence of the lifecycle of manufacturing.

Topics under this track include (but not limited to):
  • Theories, techniques, and applications of modelling and simulation for smart manufacturing systems, including cloud manufacturing
  • Industry 4.0, Industrial Internet, etc.
  • Theories, techniques, and applications of emerging technologies such as AI, blockchain, and big data integrated with modelling and simulation for smart manufacturing (including cloud manufacturing, Industry 4.0, and Industrial Internet)
  • Theories, techniques, and applications of modelling and simulation in product design, manufacturing, testing, operation and maintenance
  • Digital twin in smart manufacturing systems
  • Modelling and simulation-based system of system engineering
  • Model engineering for smart manufacturing
  • Modelling and simulation languages
  • Agent-based modelling and simulation in manufacturing
  • Semantic modelling of smart manufacturing equipment, systems, and processes
  • Simulation optimization methods in and its applications to smart manufacturing
  • Modelling and simulation for smart robotics and 3D printing
  • Modelling and simulation for smart factory

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Industry 4.0 in Agriculture

Special Session Organized by

Lei Shu, Nanjing Agricultural University/University of Lincoln, China/UK and  Gerhard Petrus Hancke, City University of Hong Kong, Hong Kong, China and  Adnan Abu-Mahfouz , Council for Scientific and Industrial Research , South Africa and  Ye Liu, Nanjing Agricultural University, China

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Focus

The three previous industrial revolutions (from Industry 1.0 to Industry 3.0) gradually modified the form of agricultural activities. The traditional labor-intensive agriculture has been replaced by industrial agriculture through the adoption of industrial production patterns, industrial production processes, and industrial supply chain management in agriculture. Currently, industrialized food production and distribution dominates the global agriculture industry because this method is more productive and cost-effective. However, there still exist several issues that need to be addressed in the current status of industrial agriculture, such as ecological problems, lack of digitization, food safety issue, and inefficient agri-food supply chain. The fourth industrial revolution (Industry 4.0) is ongoing, and is characterized by a fusion of emerging technologies such as the Internet of Things (IoT), robotics, Big Data, Artificial Intelligence (AI), and blockchain technology. At present, industrial production processes and supply chains have become more autonomous and intelligent. Correspondingly, the integration of Industry 4.0 and agriculture provides the opportunity to transform industrial agriculture into the next generation, namely, Agriculture 4.0. In this context, sustainable and intelligent industrial agriculture would be achieved through real-time variable fine-grained collection, processing, and analyzing of spatio-temporal data in all aspects of the agricultural industry, from food production, processing, distribution to consumer experience. Such a smart industrial agriculture ecosystem with real-time farm management, a high degree of automation, and data-driven intelligent decision-making would greatly improve productivity, agri-food supply chain efficiency, food safety, and the use of natural resources.

Topics under this track include (but not limited to):
  • Internet of Things for smart agriculture
  • Robotics and autonomous systems for smart agriculture
  • Artificial intelligence for smart agriculture
  • Big data analytics for smart agriculture
  • Blockchain for smart agriculture
  • Edge computing for smart agriculture
  • Unmanned aerial vehicle for smart agriculture

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Recent trends of wireless communications for industrial IoT/CPS systems

Special Session Organized by

Emiliano Sisinni, University of Brescia, Italy and  Tommaso Fedullo, University of Padova/University of Modena Reggio Emilia, Italy and  Alberto Morato, University of Padova/CMZ Sistemi Elettronici, Italy

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Focus

The latest generation of wireless technologies, as the LPWANs, WiFi6, 5G etc, are profoundly changing the Factory Communication area, especially after the advent of the Industrial Internet of Things in the automation domain. Field devices are evolving into smart things, able to communicate on both local and geographical scale. Wireless technologies solve scalability and flexibility issues in many industrial applications and offer ever increasing performance thanks to enhancements borrowed from the consumer market. However, requirements of the industrial domain pose additional constraints in terms of reliability and real-time performance, just to mention a few, which require solutions yet to come. Research activity in the industrial wireless communication domain is continuously evolving, aiming at the optimization of the overall network performance, for instance in terms of timeliness, determinism, energy consumption, and data extraction rate. For instance, innovative machine learning (ML) techniques, possibly applied to cognitive radios, can be exploited for an adaptive adjustment of communication parameters. On the other hand, the demand in terms of seamless, standardized, transparent and secure device integration is increasing and has a larger and larger impact. This special session aims to bring together academic and industry professionals to a session where the most recent studies, implementations, and proposals about the issues mentioned above can be presented.

Topics under this track include (but not limited to):
  • Communication Systems and Technologies for industrial applications
  • Protocols and Standards for Networked Embedded and Cyber-Physical Systems
  • Real-time, Safety, Security and Maintenance of Automation Systems and Networks
  • Artificial Intelligence and Machine Learning applications to enhance and Communication Technologies for Industry 4.0
  • Low-power and Green Communication in Industry
  • Recent advances in research domains with similar communication requirements
  • Wireless sensor/actuator networks for Industrial Internet of Things
  • Short-range wireless technologies measurements and applications for Industrial Internet of Things
  • Bluetooth and BLE technologies measurements and applications to Industrial Internet of Things
  • 5G/4G technologies measurements and applications to Industrial Internet of Things
  • LPWAN technologies measurements and applications for Industrial Internet of Things
  • Distributed mobile IIoT wireless systems

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Recent Deep Learning Methods for Biomedical Image Analysis

Special Session Organized by

Yu-Dong Zhang, University of Leicester, UK and  Yi Chen, Nanjing Normal University, China and  Juan M. Gorriz, University of Granada, Spain and  Shui-Hua Wang, University of Leicester, UK

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Focus

With advances in biomedical imaging, the amount of data generated is increasing in biomedical engineering. For example, data can be generated by multimodality image techniques, e.g. ranging from Optical Imaging, Infrared thermography, Computed Tomography, Magnetic Resonance Imaging, Ultrasound, Single Photon Emission Computed Tomography, and Positron Emission Tomography, to Magnetic Particle Imaging, EE/MEG, Bioluminescence imaging, Optical Microscopy and Tomography, Photoacoustic Tomography, Non-contact thermography, Electron Tomography, and Atomic Force Microscopy, etc. This poses a great challenge on how to develop new computational models for efficient data processing, analysis and modelling in clinical applications and in understanding the underlying biological process. Deep learning (DL) is a rapidly advancing computational model 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 share research/review articles which focus on the biomedical image analysis via the recent Deep learning methods. This Special Session also intends to bring new DL algorithm with innovative ideas and find out the core problems in biomedical image analysis.

Topics under this track include (but not limited to):
  • Application of recent deep learning methods in biomedical engineering
  • Transfer learning and multi-task learning
  • Joint Semantic Segmentation, Object Detection and Scene Recognition on biomedical images
  • Explainable AI in biomedical image analysis
  • Visualization of deep learning methods
  • Attention network for biomedical image analysis
  • Improvising on the computation of a deep network; exploiting parallel computation techniques and GPU programming
  • New Model of New Structure of convolutional neural network and graph neural network in biomedical image analysis

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Industrial Electronics Trends in Interoperability, Systems integration and Standards

Special Session Organized by

Allen Chen, Innovatech Solutions, USA and  Dietmar Bruckner, B&R Industrial Automation, Austria and  Victor Huang, Sage Technological Resources, USA

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Focus

In today’s high technology advances in industrial society, the international scientific community focuses on a rich set of industrial electronics fields of interest, delving into applications verticals such as Internet of Things, cyber- physical systems, advanced industrial automation, autonomous transportation, smart cities, smart power grids and many more, that is ripe for cross disciplinary technologies, interoperability and integration systems. From these inter- disciplinary approaches, standards are often generated to assist with ease of use, standard methodologies and reduced costs. It is with this focus that this special session will cover these areas of development within the technological realm of industrial electronics. This special session is seeking practitioners and scholars to share present developments in standards within industrial electronics and practical compliance platforms that seeks to provide standards compliance service offerings to industry for development in interoperability, systems compliance and compatibility.

Topics under this track include (but not limited to):
  • Recommended practices and developments in standards and interoperability in the industrial electronics fields of interest
  • Verifiable approaches in standards development and services to potential industrial partners for conformance testing and interoperability for product development and systems integration
  • Standards, test, and certification
  • Embedded systems and hardware/software design and implementation
  • Security issues
  • System integration and interoperability
  • New educational technologies for standards development

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Holistic Approach to Control and Analysis of Complex Systems with Data Mining Methods

Special Session Organized by

Gennady Veselov, Southern Federal University, Russia and  Valeriy Vyatkin, Aalto University, Finland and  Piotr Cho?da, Institute of Telecommunications, AGH University of Science and Technology, Poland

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Focus

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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