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6G Connectivity-Systems, Technologies, and Applications
This book covers need for 6G connectivity arising from the pursuit of higher data speeds, ultra-low latency, massive IoT connectivity, enhanced spectral efficiency, and the facilitation of new and transformative applications. By addressing these drivers and expectations, 6G aims to revolutionize wireless communication, opening up a realm of possibilities for industries, societies, and individuals. Technological improvements and evolutions are required beyond fifth-generation (5G) networks for wireless communications as well as in the industry where the involvement of collaborative robots (COBOT) will satisfy the personal needs of human beings as and when required leading to human–machine interactions. A considerable amount of effort has been devoted, both in industry and academia, towards the performance modelling, evaluation and prediction of convergent multi-service heterogeneous, future-generation networks such as 6G. Technical topics discussed in the book include: Network security and attacks 6G applications and Industry 5.0 Human centric interface Green computing in wireless cellular networks Next generation networks (IOT, Cloud Computing, Big Data, etc.)
App and Website Accessibility Developments and Compliance Strategies
In the present digital world, the growing number of internet users has made web quality an important factor for accessing online services and increasing the customer base of an organization. The advances in information technology and the internet have opened new dimensions in many different industries. Currently, accessibility research is an active area of research. Specifically, access for everyone regardless of disability has become an essential aspect of web development. As webpages will be used by both nondisabled and disabled individuals, web pages must be designed with a technical criterion that fits universal needs. The ambition to make websites barrier-free is not limited to standard...
Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics
The internet of things (IoT) has emerged to address the need for connectivity and seamless integration with other devices as well as big data platforms for analytics. However, there are challenges that IoT-based applications face including design and implementation issues; connectivity problems; data gathering, storing, and analyzing in cloud-based environments; and IoT security and privacy issues. Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics is a critical reference source that provides theoretical frameworks and research findings on IoT and big data integration. Highlighting topics that include wearable sensors, machine learning, machine ...
Integration and Implementation of the Internet of Things Through Cloud Computing
The internet of things (IoT) has drawn great attention from both academia and industry, since it offers a challenging notion of creating a world where all things around us are connected to the internet and communicate with each other with minimal human intervention. Another component for helping IoT to succeed is cloud computing. The combination of cloud computing and IoT will enable new monitoring services and powerful processing of sensory data streams. These applications, alongside implementation details and challenges, should also be explored for successful mainstream adoption. IoT is also fueled by the advancement of digital technologies, and the next generation era will be cloud-based ...
IoT Protocols and Applications for Improving Industry, Environment, and Society
"This book studies how daily life operates using many objects with Internet connections such as smartphones, tablets, Smart TVs, micro-controllers, Smart Tags, computers, laptops, cars, cheaper sensors, and more, commonly referred to as the Internet of Things. To accommodate this new connected structure, readers will learn how improved wireless strategies drive the need for a better IoT network"--
Design Innovation and Network Architecture for the Future Internet
For the past couple of years, network automation techniques that include software-defined networking (SDN) and dynamic resource allocation schemes have been the subject of a significant research and development effort. Likewise, network functions virtualization (NFV) and the foreseeable usage of a set of artificial intelligence techniques to facilitate the processing of customers’ requirements and the subsequent design, delivery, and operation of the corresponding services are very likely to dramatically distort the conception and the management of networking infrastructures. Some of these techniques are being specified within standards developing organizations while others remain perceive...
Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media
Opinion mining and text analytics are used widely across numerous disciplines and fields in today’s society to provide insight into people’s thoughts, feelings, and stances. This data is incredibly valuable and can be utilized for a range of purposes. As such, an in-depth look into how opinion mining and text analytics correlate with social media and literature is necessary to better understand audiences. The Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media introduces the use of artificial intelligence and big data analytics applied to opinion mining and text analytics on literary works and social media. It also focuses on theories, methods, and approaches in which data analysis techniques can be used to analyze data to provide a meaningful pattern. Covering a wide range of topics such as sentiment analysis and stance detection, this publication is ideal for lecturers, researchers, academicians, practitioners, and students.
Examining the Impact of Deep Learning and IoT on Multi-Industry Applications
Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for compl...
