Kamalakanta Muduli – författare

This book addresses issues related to the integration of digital evolutionary technologies and provides solutions to various challenges encountered during the implementation process. With real-time case studies, the book explains the smart technologies available and their operational applications and benefits in the manufacturing sector. Smart Manufacturing Technologies for Industry 4.0: Integration, Benefits, and Operational Activities assists in the understanding of the shifting paradigm in the manufacturing sector towards smart manufacturing and spotlights these technologies and the effects they are having on existing industries. It showcases Industry 4.0 as a promising research area in its infancy and offers insights into the role smart technologies are playing now and into the future. The book focuses on smart technologies’ rudiments, implementation, and integration for organizational development and offers insights on how to achieve resiliency through and because of these technologies. This book presents real-time implementation discussions along with case studies that emphasize benefits and operational activities for engineers and managers. It’s also a very useful book for technology developers, academicians, data scientists, industrial engineers, researchers, and students interested in uncovering the latest innovations in a field that seeks current research on products and services.

This book addresses issues related to the integration of digital evolutionary technologies and provides solutions to various challenges encountered during the implementation process. With real-time case studies, the book explains the smart technologies available and their operational applications and benefits in the manufacturing sector. Smart Manufacturing Technologies for Industry 4.0: Integration, Benefits, and Operational Activities assists in the understanding of the shifting paradigm in the manufacturing sector towards smart manufacturing and spotlights these technologies and the effects they are having on existing industries. It showcases Industry 4.0 as a promising research area in its infancy and offers insights into the role smart technologies are playing now and into the future. The book focuses on smart technologies’ rudiments, implementation, and integration for organizational development and offers insights on how to achieve resiliency through and because of these technologies. This book presents real-time implementation discussions along with case studies that emphasize benefits and operational activities for engineers and managers. It’s also a very useful book for technology developers, academicians, data scientists, industrial engineers, researchers, and students interested in uncovering the latest innovations in a field that seeks current research on products and services.

The text comprehensively discusses computational models including artificial neural networks, agent-based models, and decision field theory for reliability engineering. It will serve as an ideal reference text for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, computer engineering, and materials science. Discusses the development of sustainable materials using metaheuristic approaches. Covers computational models such as agent-based models, ontology, and decision field theory for reliability engineering. Presents swarm intelligence methods such as ant colony optimization, particle swarm optimization, and grey wolf optimization for solving the manufacturing process. Include case studies for industrial optimizations. Explores the use of computational optimization for reliability and maintainability theory. The text covers swarm intelligence techniques including ant colony optimization, particle swarm optimization, cuckoo search, and genetic algorithms for solving complex industrial problems of the manufacturing industry as well as predicting reliability, maintainability, and availability of several industrial components.

The text comprehensively discusses computational models including artificial neural networks, agent-based models, and decision field theory for reliability engineering. It will serve as an ideal reference text for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, computer engineering, and materials science. Discusses the development of sustainable materials using metaheuristic approaches. Covers computational models such as agent-based models, ontology, and decision field theory for reliability engineering. Presents swarm intelligence methods such as ant colony optimization, particle swarm optimization, and grey wolf optimization for solving the manufacturing process. Include case studies for industrial optimizations. Explores the use of computational optimization for reliability and maintainability theory. The text covers swarm intelligence techniques including ant colony optimization, particle swarm optimization, cuckoo search, and genetic algorithms for solving complex industrial problems of the manufacturing industry as well as predicting reliability, maintainability, and availability of several industrial components.

This book discusses smart technologies and their influence in the field of manufacturing and industrial systems engineering, in the context of performability enhancement, and explores the development of the workforce for the execution of such smart and advanced technologies.Smart Technologies for Improved Performance of Manufacturing Systems and Services discusses the integration of smart technology into the production process and supply chain to enhance the overall performance of manufacturing industries. As well as emphasizing the fundamentals of smart technologies, such as artificial intelligence, big data, and cyber-physical systems, it highlights the role that machine learning plays along with other smart technologies. Real-time case studies highlight the applications of smart digital technologies, and research insights into the area of performability and overall sustainable development round out the great range of discussions this reference book has to offer.Managers and stakeholders seeking coverage on techniques and methods for integration into their organizations, as well as students and researchers in the field will find this book very useful.

This book discusses smart technologies and their influence in the field of manufacturing and industrial systems engineering, in the context of performability enhancement, and explores the development of the workforce for the execution of such smart and advanced technologies.Smart Technologies for Improved Performance of Manufacturing Systems and Services discusses the integration of smart technology into the production process and supply chain to enhance the overall performance of manufacturing industries. As well as emphasizing the fundamentals of smart technologies, such as artificial intelligence, big data, and cyber-physical systems, it highlights the role that machine learning plays along with other smart technologies. Real-time case studies highlight the applications of smart digital technologies, and research insights into the area of performability and overall sustainable development round out the great range of discussions this reference book has to offer.Managers and stakeholders seeking coverage on techniques and methods for integration into their organizations, as well as students and researchers in the field will find this book very useful.

This book presents cutting-edge findings that draw on the use of AI, the Industrial Internet of Things, Blockchain, and Co-Analytics for the development of Circular Economy (CE) models to make organizational activities more sustainable. A further goal is the development of Digital Technology (DT)–enabled support tools that can be used to further analyze the impact of DT and CE–enabled operational practices used to achieve resource and environmental sustainability.Digital Technology Enabled Circular Economy: Models for Environmental and Resource Sustainability discusses the integration of digital technology-enabledcircular economy models into the manufacturing industries and its advantages for sustainability. It emphasizes the fundamentals and applications and their enactment, as well as integration for the overall organizational development. The book explains the role of digital technologies in food supply chains and multi-life cycle materials for sustainable development and highlights the development of the workforce to facilitate the implementation of smart and advanced technologies. This book presents the development of DT–enabled support tools used to analyze the impact of DT and CE–enabled operational practices on an organization and efforts to achieve resource and environmental sustainability. Case studies that demonstrate how smart digital technology can help firms improve their long-term performance by embracing circular operation methods are also included.Students, academicians, and researchers, as well as managers and stakeholders who are interested in smart, sustainable production, and consumption, together with managers and stakeholders who are interested in ways of implementing them in their organizations, will find this book of interest. It will demonstrate, via the use of real-world case studies, how smart digital technology can help firms improve their long-term performance by embracing circular operating methods.

This book presents cutting-edge findings that draw on the use of AI, the Industrial Internet of Things, Blockchain, and Co-Analytics for the development of Circular Economy (CE) models to make organizational activities more sustainable. A further goal is the development of Digital Technology (DT)–enabled support tools that can be used to further analyze the impact of DT and CE–enabled operational practices used to achieve resource and environmental sustainability.Digital Technology Enabled Circular Economy: Models for Environmental and Resource Sustainability discusses the integration of digital technology-enabledcircular economy models into the manufacturing industries and its advantages for sustainability. It emphasizes the fundamentals and applications and their enactment, as well as integration for the overall organizational development. The book explains the role of digital technologies in food supply chains and multi-life cycle materials for sustainable development and highlights the development of the workforce to facilitate the implementation of smart and advanced technologies. This book presents the development of DT–enabled support tools used to analyze the impact of DT and CE–enabled operational practices on an organization and efforts to achieve resource and environmental sustainability. Case studies that demonstrate how smart digital technology can help firms improve their long-term performance by embracing circular operation methods are also included.Students, academicians, and researchers, as well as managers and stakeholders who are interested in smart, sustainable production, and consumption, together with managers and stakeholders who are interested in ways of implementing them in their organizations, will find this book of interest. It will demonstrate, via the use of real-world case studies, how smart digital technology can help firms improve their long-term performance by embracing circular operating methods.

Industry 4.0 and 5.0 applications will revolutionize production, enabling smart manufacturing machines to interact with their environments. These machines will become self-aware, self-learning, and capable of real-time data interpretation for self-diagnosis and prevention of production issues. They will also self-calibrate and prioritize tasks to enhance production quality and efficiency.Computational Intelligence in Industry 4.0 and 5.0 Applications examines applications that merge three key disciplines: computational intelligence (CI), Industry 4.0, and Industry 5.0. It presents solutions using Industrial Internet of Things (IIoT) technologies, augmented by CI-based techniques, modeling, controls, estimations, applications, systems, and future scopes. These applications use data from smart sensors, processed through enhanced CI methods, to make smart automation more effective.Industry 4.0 integrates data and intelligent automation into manufacturing, using technologies like CI, the IoT, the IIoT, and cloud computing. It transforms data into actionable insights for decision-making and process optimization, essential for modern competitive businesses managing high-speed data integration in production processes. Currently, Industries 4.0 and 5.0 are undergoing significant transformations due to advances in applying artificial intelligence (AI), big data analytics, telecommunication technologies, and control theory. These applications are increasingly multidisciplinary, integrating mechanical, control, and information technologies. However, they face such technical challenges as parametric uncertainties, external disturbances, sensor noise, and mechanical failures. To address these, this book examines such CI technologies as fuzzy logic, neural networks, and reinforcement learning and their application to modeling, control, and estimation. It also covers recent advancements in IIoT sensors, microcontrollers, and big data analytics that further enhance CI-based solutions in Industry 4.0 and 5.0 systems.

The Asia-Pacific region, home to some of the world’s fastest-growing economies, faces a range of complex challenges, including environmental degradation, the increasing frequency of natural hazards, and rapid urbanization. Addressing these issues, which many countries across the globe are facing, requires innovative, interdisciplinary approaches to promote sustainable development and enhance resilience. Geographic information systems (GIS), when combined with multi-criteria decision-making (MCDM) techniques and advanced technologies such as artificial intelligence (AI), offer powerful tools to tackle these multifaceted problems. AIGIS integrates AI with GIS to derive insights from geospatial data. The fusion of AI techniques with GIS enhances data analysis, visualization, and decision-making. Artificial Intelligence, Geographic Information Systems, and Multi-Criteria Decision-Making for Improving Sustainable Development explore how these integrated tools can support decision-making processes aimed at advancing sustainable development.Drawing on research and insights from diverse disciplines, the book looks at how GIS, MCDM, and AI can provide solutions for disaster risk reduction, environmental monitoring, urban planning, and natural resource management. Through diverse case studies and theoretical explorations, this book highlights the value of integrated geospatial tools in facilitating informed decision-making and fostering resilient societies in the face of evolving challenges. It covers a wide range of topics, including the following:Site-soil-geology assessments in FijiFlood risk analysis in Hong KongAir quality management in Delhi during the COVID-19 pandemicVegetation health monitoring in ThailandBringing together the work of academicians, practitioners, and decision-makers, the book reflects the growing recognition towards effective and sustainable solutions to complex problems, which require a multidimensional approach, integrating scientific, economic, and social considerations. By providing the latest research and practical applications of MCDM, AI, and GIS, it contributes to ongoing efforts to build a more sustainable and resilient future for the Asia-Pacific region, as well as for the world.

In an era where industries are tasked with addressing pressing global challenges, ranging from climate change and resource depletion to societal well-being, the fusion of AI and IoT emerges as a powerful catalyst for positive change. The synergistic collaboration between intelligent algorithms and interconnected devices not only enhances operational efficiency but also empowers industries to make informed decisions that align with ecological and social considerations.AIoT-Driven Sustainable Manufacturing and Operational Initiatives: A Smart Eco- Friendly Manufacturing System offers a comprehensive exploration of the integration of AI and IoT in the context of sustainable industry, covering foundational principles, practical applications, and real-world case studies. It provides practical insights into how AIoT solutions are currently being implemented, offering tangible examples and success stories that readers can relate to and draw inspiration from. Emphasis is placed on the significance of data-driven decision-making, showcasing how AIoT enables industries to harness the power of data for optimizing processes, reducing waste, and achieving sustainability goals. The book includes real-world case studies and examples illustrating the practical impact of AIoT, making complex concepts accessible and demonstrating the transformative potential of these technologies in actual industrial settings.Tailored to various industries, the book ensures relevance for a diverse audience, including manufacturing, energy, and environmental sectors, making it a versatile resource for professionals across different fields.

Industry 4.0 and Industry 5.0 applications will revolutionize production, enabling smart manufacturing machines to interact with their environments. These machines will become self-aware, self-learning, and capable of real-time data interpretation for self-diagnosis and prevention of production issues. They will also self-calibrate and prioritize tasks to enhance production quality and efficiency.Computational Intelligence for Analysis of Trends in Industry 4.0 and 5.0 examines the trends in applications that merge three key disciplines: Computational Intelligence (CI), Industry 4.0, and Industry 5.0. It presents solutions using industrial Internet of Things (IIoT) technologies, augmented by CI-based techniques, modeling, controls, estimations, applications, systems, and future scopes. These applications use data from smart sensors, processed through enhanced CI methods, to make smart automation more effective.Industry 4.0 integrates data and intelligent automation into manufacturing, using technologies like CI, Internet of Things (IoT), IIoT, and cloud computing. It transforms data into actionable insights for decision-making and process optimization, essential for modern competitive businesses managing high-speed data integration in production processes. Currently, Industry 4.0 and Industry 5.0 are undergoing significant transformations due to advances in applying artificial intelligence (AI), big data analytics, telecommunication technologies, and control theory. These trends are increasingly multidisciplinary, integrating mechanical, control, and information technologies. However, they face technical challenges such as parametric uncertainties, external disturbances, sensor noise, and mechanical failures. To address these issues, this book examines trends such as CI technologies as fuzzy logic, neural networks, and reinforcement learning and their application to modeling, control, and estimation. It also covers recent advancements in IIoT sensors, microcontrollers, and big data analytics that further enhance CI-based solutions in Industry 4.0 and Industry 5.0 systems.

Industry 4.0 and 5.0 applications will revolutionize production, enabling smart manufacturing machines to interact with their environments. These machines will become self-aware, self-learning, and capable of real-time data interpretation for self-diagnosis and prevention of production issues. They will also self-calibrate and prioritize tasks to enhance production quality and efficiency.Computational Intelligence in Industry 4.0 and 5.0 Applications examines applications that merge three key disciplines: computational intelligence (CI), Industry 4.0, and Industry 5.0. It presents solutions using Industrial Internet of Things (IIoT) technologies, augmented by CI-based techniques, modeling, controls, estimations, applications, systems, and future scopes. These applications use data from smart sensors, processed through enhanced CI methods, to make smart automation more effective.Industry 4.0 integrates data and intelligent automation into manufacturing, using technologies like CI, the IoT, the IIoT, and cloud computing. It transforms data into actionable insights for decision-making and process optimization, essential for modern competitive businesses managing high-speed data integration in production processes. Currently, Industries 4.0 and 5.0 are undergoing significant transformations due to advances in applying artificial intelligence (AI), big data analytics, telecommunication technologies, and control theory. These applications are increasingly multidisciplinary, integrating mechanical, control, and information technologies. However, they face such technical challenges as parametric uncertainties, external disturbances, sensor noise, and mechanical failures. To address these, this book examines such CI technologies as fuzzy logic, neural networks, and reinforcement learning and their application to modeling, control, and estimation. It also covers recent advancements in IIoT sensors, microcontrollers, and big data analytics that further enhance CI-based solutions in Industry 4.0 and 5.0 systems.

The International Conference on Sustainable Developments in Computer Engineering, Green Technology and Smart Systems (ICSDS 2025) brings together groundbreaking contemporary insights and intelligent technological solutions in the fields of computer engineering, green computing, smart systems, artificial intelligence, Internet of Things, data science and cybersecurity.The chapters in this volume provide an integrated analysis of energy-efficient, environmentally sustainable and technologically resilient building systems. Combining foundational principles with applied methodologies, the book addresses contemporary challenges in intelligent automation, sustainable communication networks, secure digital infrastructures and smart industrial applications.By integrating interdisciplinary research with real-world applications, this publication serves as a valuable resource for researchers, practitioners and policymakers committed to shaping sustainable technological ecosystems for the future.

The International Conference on Sustainable Developments in Computer Engineering, Green Technology and Smart Systems (ICSDS 2025) brings together groundbreaking contemporary insights and intelligent technological solutions in the fields of computer engineering, green computing, smart systems, artificial intelligence, Internet of Things, data science, and cybersecurity.The chapters in this volume provide an integrated analysis of energy-efficient, environmentally sustainable, and technologically resilient building systems. Combining foundational principles with applied methodologies, the book addresses contemporary challenges in intelligent automation, sustainable communication networks, secure digital infrastructures, and smart industrial applications.By integrating interdisciplinary research with real-world applications, this publication serves as a valuable resource for researchers, practitioners, and policymakers committed to shaping sustainable technological ecosystems for the future.

ICISAS 2025 is the leading research conference of Curtin University Dubai, bringing together experts who are shaping the future through innovation, sustainability, and applied sciences. The event provides a strong platform for sharing new knowledge that supports technological progress and sustainable development.The main purpose of the conference is to encourage collaboration across engineering, technology, management, and scientific fields. It connects researchers, industry leaders, policymakers, and students who are committed to creating solutions that address global challenges through responsible and forward-looking innovation.ICISAS 2025 aims to highlight research that can improve material performance, energy systems, sustainable design, and advanced manufacturing. This aligns closely with the book theme, which focuses on innovative engineering approaches that enhance durability, efficiency, and environmental responsibility.A major focus of the conference is on advanced materials, renewable energy technologies, and intelligent systems. Participants explore areas such as nanocomposites, eco-friendly concretes, solar and wind optimization, AI-driven monitoring, IoT-enabled engineering processes, robotics applications, and improved safety systems. The conference also features research on wastewater treatment, structural optimization, machining processes, geotechnical solutions, and sustainable industrial practices. These topics demonstrate how engineering innovations can reduce environmental impact and support sustainable infrastructure and industry.Over two days, the conference offers keynote talks, plenary sessions, poster and oral presentations, symposiums, networking activities, and exhibitor showcases. This diverse programme helps participants engage deeply with new technologies, practical solutions, and collaborative opportunities.ICISAS 2025 stands out for its strong participation from government leaders, eminent scientists, technologists, industry experts, and academics. By bringing together such a wide group, the conference creates a unique environment where cutting-edge engineering research meets real-world application and policy impact.

ICISAS 2025 is the leading research conference of Curtin University Dubai, bringing together experts who are shaping the future through innovation, sustainability, and applied sciences. The event provides a strong platform for sharing new knowledge that supports technological progress and sustainable development.The main purpose of the conference is to encourage collaboration across engineering, technology, management, and scientific fields. It connects researchers, industry leaders, policymakers, and students who are committed to creating solutions that address global challenges through responsible and forward-looking innovation.ICISAS 2025 aims to highlight research that can improve material performance, energy systems, sustainable design, and advanced manufacturing. This aligns closely with the book theme, which focuses on innovative engineering approaches that enhance durability, efficiency, and environmental responsibility.A major focus of the conference is on advanced materials, renewable energy technologies, and intelligent systems. Participants explore areas such as nanocomposites, eco-friendly concretes, solar and wind optimization, AI-driven monitoring, IoT-enabled engineering processes, robotics applications, and improved safety systems. The conference also features research on wastewater treatment, structural optimization, machining processes, geotechnical solutions, and sustainable industrial practices. These topics demonstrate how engineering innovations can reduce environmental impact and support sustainable infrastructure and industry.Over two days, the conference offers keynote talks, plenary sessions, poster and oral presentations, symposiums, networking activities, and exhibitor showcases. This diverse programme helps participants engage deeply with new technologies, practical solutions, and collaborative opportunities.ICISAS 2025 stands out for its strong participation from government leaders, eminent scientists, technologists, industry experts, and academics. By bringing together such a wide group, the conference creates a unique environment where cutting-edge engineering research meets real-world application and policy impact.

INTRELLIGENT MANUFACTURING MANAGEMENT SYSTEMS The book explores the latest manufacturing techniques in relation to AI and evolutionary algorithms that can monitor and control the manufacturing environment. The concepts that pertain to the application of digital evolutionary technologies in the sphere of industrial engineering and manufacturing are presented in this book. A few chapters demonstrate stepwise discussion, case studies, structured literature review, rigorous experimentation results, and applications. Further chapters address the challenges encountered by industries in integrating these digital technologies into their operational activities, as well as the opportunities for this integration. In addition, the reader will find: Systemic explanations of the unique characteristics of big data, cloud computing, and AI used for decision-making in intelligent production systems;Highlights of the current and highly relevant topics in manufacturing management;Structured presentations resolving the issues being faced by many real-world applications in a broad range of areas such as smart supply chains, knowledge management, intelligent inventory management, IoT adoption in manufacturing management, and more;Intelligent techniques for sustainable practices in industrial waste management.Audience The book will be used by researchers, industry engineers, and data scientists/AI specialists working in industrial engineering, mechanical engineering, production engineering, manufacturing engineering, and operations and supply chain management. The book will also be valuable to the service sector industry, such as logistics and those implementing smart cities.

This book highlights the important use of digital technologies and the latest developments in mechanical and industrial engineering to enhance environmental and resource sustainability. Sustainable Development Goals (SDGs) have as their overarching objective the reduction or eradication of a wide range of global problems, including, but not limited to poverty, climate change, environmental degradation, and inequality. Digital technologies (DTs) have the potential to be exploited to meet the goals associated with the circular economy (CE) and sustainable development. Additive manufacturing (AM), cyber-physical systems (CPS), and blockchain technology are examples of DT-enabled technologies that are helpful for businesses that seek to shift to a circular economic model. With the remanufacturing of products, applications that make use of virtual reality and augmented reality, in addition to the Internet of Things, simplify the construction of strategic decision models that reduce time and expense while simultaneously increasing productivity. In addition, the utilization of big data analytics helps businesses discover previously undisclosed trends and unlock numerous opportunities for environmental and resource sustainability. Employing analytics makes it feasible to collect helpful information regarding the socio-environmental impact of a product, as well as consumption factors over the entirety of a product’s life cycle. This book contains 44 comprehensive chapters and is divided into five parts. Part 1 delves deeply into sustainable operational practices and supply chain management. The impact that digital technology-enabled operational techniques have on product life cycles is investigated, as well as the design of efficient remanufacturing processes, environmentally friendly logistics and warehousing practices, sustainable designs for distributed energy supply systems, and efficient recycling procedures. Part 2 provides a perspective on advanced materials and developments for sustainable manufacturing. The chapters in this section address sustainable material development and its application in the circular economy concept. Included here is an in-depth exploration of cutting-edge technology for synthesis, processing, fabrication, process optimization, testing, and performance evaluation of advanced materials. Part 3 covers sustainable manufacturing practices and looks at the problems faced by the industry when using digital technologies in their operations, as well as the possible benefits. Part 4 examines sustainable innovation in mechanical design. It addresses all aspects of mechanical design that contribute to sustainable innovation for nation-building. Part 5 delves into heat transfer and fluid flow concepts for sustainable product development and applications. The chapters explain how to construct sustainable energy systems by reducing the total amount of energy that is utilized, enhancing the efficiency of the process of energy conversion, and making use of sources of energy that are renewable. Audience This book has a wide audience in academic institutions and engineers in a variety of manufacturing industries. It will also appeal to economists and policymakers working on the circular economy, clean tech investors, industrial decision-makers, and environmental professionals.

The book focuses on multiple areas of manufacturing, including cutting-edge material processing technologies, custom-made materials, metallic and non-metallic materials, new engineering experiments, contemporary machining, joining, surface modification, and process optimization techniques. Readers will find in this volume an extensive exploration of various advanced manufacturing and material engineering topics. It includes a detailed examination of aluminum grades and their applications, an overview of cold spray additive manufacturing, and a discussion on Gas Metal Arc Welding (GMAW) for cladding low-carbon steel plates. The volume also presents innovative approaches to brake pedal design using topology optimization, analysis of resistance-spot welding quality, and the impact of shot peening on the corrosion behavior of SiC Particle Reinforced Aluminum Composite. It highlights crucial factors in 3D printed component strength, reviews 3D milling operations with ABAQUS, and delves into the rare ferroelectric material Fresnoite. The book surveys visual sensing technologies for weld pool analysis, simulates Claus Sulfur Recovery Units with Aspen Plus, and discusses ultrasonic-assisted stir casting for metal matrix nanocomposites. It also covers the joining of dissimilar magnesium alloys, advancements in electrochemical surface coatings, unconventional machining techniques, surface coating processes using pulsed power systems, natural fiber-reinforced composite fabrication, and process parameter optimization in laser beam welding using NSGA-II. Audience The book will interest researchers in academia and industry engineers in advanced manufacturing, materials science, surface science, adhesion and coatings, production engineering, civil engineering, and welding.

With a need to find alternatives to the traditional face-to-face teaching and learning during the pandemic, this topical volume discusses the best use of technologies in higher education, addressing the growing role of AI in the digital transformation of higher education systems. With chapters from eminent professors, researchers, and others involved in higher education from a selection of different countries, the volume looks at blockchain and IoT technologies to create smart universities now and for the future.

Some of the topics covered include Heat transfer, fluid dynamics, multiphase flow, flow diagnostics using artificial neural network, aerodynamics, high-speed flows, sustainable energy technology, propulsion and emissions, Eco-friendly manufacturing, Coating Techniques and Supply chain management etc.