This book comprises select peer-reviewed proceedings of the 6th International Conference on Innovative Computing (IC 2023). The contents focus on communication networks, business intelligence and knowledge management, web intelligence, and fields related to the development of information technology. The chapters include contributions on various topics such as databases and data mining, networking and communications, web and Internet of Things, embedded systems, soft computing, social network analysis, security and privacy, optical communication, and ubiquitous/pervasive computing. This volume will serve as a comprehensive overview of the latest advances in information technology for those working as researchers in both academia and industry.

This book comprises select peer-reviewed proceedings of the 6th International Conference on Innovative Computing (IC 2023). The contents focus on communication networks, business intelligence and knowledge management, web intelligence, and fields related to the development of information technology. The chapters include contributions on various topics such as databases and data mining, networking and communications, web and Internet of Things, embedded systems, soft computing, social network analysis, security and privacy, optical communication, and ubiquitous/pervasive computing. This volume will serve as a comprehensive overview of the latest advances in information technology for those working as researchers in both academia and industry.

Digital Transformation in Education and Artificial Intelligence: Emerging Markets and Opportunities aims to shed light on the various advantages and drawbacks of the same along with the opportunities and markets that are emerging because of digital transformation. This volume encompasses diverse perspectives on the digital landscape for Small and Medium Enterprises (SMEs). It delves into the use of digital tools like Big Data, IoT, AI, and ML in Chapter 1, followed by an exploration of factors influencing online shopping adoption in SMEs in Ghana (Chapter 2). Chapter 3 sheds light on the digital transformation of African SMEs, while Chapter 4 offers insights into the consequences of digitalization for SMEs in Sub-Saharan Africa. The subsequent chapters cover topics such as the impact of Big Data on SMEs' performance, digitization initiatives for African telecom service providers, the role of social media as a promotional tool for SMEs in Ghana, and the utilization of Artificial Intelligence by SMEs in Africa, addressing both benefits and challenges. The chapters provide information for educators at all levels to obtain a complete understanding of the technology-based environment that impacts teaching and commerce. It also serves as a resource for policymakers, entrepreneurs, researchers, and students interested in digital transformation in Africa.

The concept of concurrent engineering (CE) was first developed in the 1980s. Now often referred to as transdiciplinary engineering, it is based on the idea that different phases of a product life cycle should be conducted concurrently and initiated as early as possible within the Product Creation Process (PCP). The main goal of CE is to increase the efficiency and effectiveness of the PCP and reduce errors in later phases, as well as incorporating considerations – including environmental implications – for the full lifecycle of the product. It has become a substantive methodology in many industries, and has also been adopted in the development of new services and service support. This book presents the proceedings of the 25th ISPE Inc. International Conference on Transdisciplinary Engineering, held in Modena, Italy, in July 2018. This international conference attracts researchers, industry experts, students, and government representatives interested in recent transdisciplinary engineering research, advancements and applications. The book contains 120 peer-reviewed papers, selected from 259 submissions from all continents of the world, ranging from the theoretical and conceptual to papers addressing industrial best practice, and is divided into 11 sections reflecting the themes addressed in the conference program and addressing topics as diverse as industry 4.0 and smart manufacturing; human-centered design; modeling, simulation and virtual design; and knowledge and data management among others. With an overview of the latest research results, product creation processes and related methodologies, this book will be of interest to researchers, design practitioners and educators alike.

The book is a collection of high-quality peer-reviewed research papers presented at the Fifth International Conference on Innovations in Computer Science and Engineering (ICICSE 2017) held at Guru Nanak Institutions, Hyderabad, India during 18-19 August 2017. The book discusses a wide variety of industrial, engineering and scientific applications of the engineering techniques. Researchers from academic and industry present their original work and exchange ideas, information, techniques and applications in the field of Communication, Computing and Data Science and Analytics.

Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science mainly focuses on the techniques of artificial intelligence (AI), Internet of Things (IoT) and data science for future communications systems. The goal of AI, IoT and data science for future communications systems is to create a venue for industry and academics to collaborate on the development of network and system solutions based on data science, AI and IoT. Recent breakthroughs in IoT, mobile and fixed communications and computation have paved the way for a data‐centric society of the future. New applications are increasingly reliant on machine‐to‐machine connections, resulting in unusual workloads and the need for more efficient and dependable infrastructures. Such a wide range of traffic workloads and applications will necessitate dynamic and highly adaptive network environments capable of self‐optimization for the task at hand while ensuring high dependability and ultra‐low latency. Networking devices, sensors, agents, meters and smart vehicles/systems generate massive amounts of data, necessitating new levels of security, performance and dependability. Such complications necessitate the development of new tools and approaches for providing successful services, management and operation. Predictive network analytics will play a critical role in insight generation, process automation required for adapting and scaling to new demands, resolving issues before they impact operational performance (e.g., preventing network failures and anticipating capacity requirements) and overall network decision‐making. To increase user experience and service quality, data mining and analytic techniques for inferring quality of experience (QoE) signals are required. AI, IoT, machine learning, reinforcement learning and network data analytics innovations open new possibilities in areas such as channel modeling and estimation, cognitive communications, interference alignment, mobility management, resource allocation, network control and management, network tomography, multi‐agent systems and network ultra‐broadband deployment prioritization. These new analytic platforms will aid in the transformation of our networks and user experience. Future networks will enable unparalleled automation and optimization by intelligently gathering, analyzing, learning and controlling huge volumes of information.