Sumit Kumar Rana – författare

By enabling the conversion of traditional manufacturing systems into contemporary digitalized ones, Internet of Things (IoT) adoption in manufacturing creates huge economic prospects through reshaping industries. Modern businesses can more readily implement new data-driven strategies and deal with the pressure of international competition thanks to Industrial IoT. But as the use of IoT grows, the amount of created data rises, turning industrial data into Industrial Big Data.

Internet of Things and Big Data Analytics-Based Manufacturing shows how Industrial Big Data can be produced as a result of IoT usage in manufacturing, considering sensing systems and mobile devices. Different IoT applications that have been developed are demonstrated and it is shown how genuine industrial data can be produced, leading to Industrial Big Data. This book is organized into four sections discussing IoT and technology, the future of Big Data, algorithms, and case studies demonstrating the use of IoT and Big Data in a variety of industries, including automation, industrial manufacturing, and healthcare.

This reference title brings all related technologies into a single source so that researchers, undergraduate and postgraduate students, academicians, and those in the industry can easily understand the topic and further their knowledge.

By enabling the conversion of traditional manufacturing systems into contemporary digitalized ones, Internet of Things (IoT) adoption in manufacturing creates huge economic prospects through reshaping industries. Modern businesses can more readily implement new data-driven strategies and deal with the pressure of international competition thanks to Industrial IoT. But as the use of IoT grows, the amount of created data rises, turning industrial data into Industrial Big Data.

Internet of Things and Big Data Analytics-Based Manufacturing shows how Industrial Big Data can be produced as a result of IoT usage in manufacturing, considering sensing systems and mobile devices. Different IoT applications that have been developed are demonstrated and it is shown how genuine industrial data can be produced, leading to Industrial Big Data. This book is organized into four sections discussing IoT and technology, the future of Big Data, algorithms, and case studies demonstrating the use of IoT and Big Data in a variety of industries, including automation, industrial manufacturing, and healthcare.

This reference title brings all related technologies into a single source so that researchers, undergraduate and postgraduate students, academicians, and those in the industry can easily understand the topic and further their knowledge.

The book covers the role of emerging technologies such as blockchain technology, machine learning, IoT, cryptography, etc., in digital asset management. It further discusses digital asset management applications in different domains such as healthcare, travel industry, image processing, and our daily life activities to maintain privacy and confidentiality.

This book:

• Discusses techniques for securing and protecting digital assets in collaborative environments, where multiple organizations need access to the same resources.

• Explores how artificial intelligence can be used to automate the management of digital assets, and how it can be used to improve security and privacy.

• Explains the role of emerging technology such as blockchain technology for transforming conventional business models.

• Highlights the importance of machine learning techniques in maintaining the privacy and security of data.

• Covers encryption and decryption techniques, their advantages and role in improving the privacy of data.

The text is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer science and engineering, information technology, and business management.

The book covers the role of emerging technologies such as blockchain technology, machine learning, IoT, cryptography, etc., in digital asset management. It further discusses digital asset management applications in different domains such as healthcare, travel industry, image processing, and our daily life activities to maintain privacy and confidentiality.

This book:

• Discusses techniques for securing and protecting digital assets in collaborative environments, where multiple organizations need access to the same resources.

• Explores how artificial intelligence can be used to automate the management of digital assets, and how it can be used to improve security and privacy.

• Explains the role of emerging technology such as blockchain technology for transforming conventional business models.

• Highlights the importance of machine learning techniques in maintaining the privacy and security of data.

• Covers encryption and decryption techniques, their advantages and role in improving the privacy of data.

The text is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer science and engineering, information technology, and business management.