Название: Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs: Methods, technologies and applications
Автор: Amit Kumar Tyagi, Ajith Abraham, Arturas Kaklauskas
Издательство: The Institution of Engineering and Technology
Год: 2022
Страниц: 679
Язык: английский
Формат: pdf (true)
Размер: 37.0 MB
We are moving into a smart era where Internet of Things (IoTs) and smart devices will be used at a large scale. In fast-developing applications such as healthcare, transportation, education, retail, etc., the storing of information (generated by IoT devices) and its access will require secure mechanisms. Blockchain is designed specifically to accelerate and simplify the process of how transactions are made without any intermediary. They can be recorded transparently as a completely decentralized system. Blockchain technologies and concepts will help support decentralized services to end users by providing reliable, full-proof services using ledger functionality, and it will likely be used in many future applications. Moreover, both industry and academic researchers are now looking at transforming applications into automated applications using Machine Learning and Deep Learning.
Автор: Amit Kumar Tyagi, Ajith Abraham, Arturas Kaklauskas
Издательство: The Institution of Engineering and Technology
Год: 2022
Страниц: 679
Язык: английский
Формат: pdf (true)
Размер: 37.0 MB
We are moving into a smart era where Internet of Things (IoTs) and smart devices will be used at a large scale. In fast-developing applications such as healthcare, transportation, education, retail, etc., the storing of information (generated by IoT devices) and its access will require secure mechanisms. Blockchain is designed specifically to accelerate and simplify the process of how transactions are made without any intermediary. They can be recorded transparently as a completely decentralized system. Blockchain technologies and concepts will help support decentralized services to end users by providing reliable, full-proof services using ledger functionality, and it will likely be used in many future applications. Moreover, both industry and academic researchers are now looking at transforming applications into automated applications using Machine Learning and Deep Learning.