Название: System Design Using the Internet of Things with Deep Learning Applications
Автор: Arpan Deyasi, Angsuman Sarkar, Soumen Santra
Издательство: Apple Academic Press, CRC Press
Год: 2024
Страниц: 282
Язык: английский
Формат: pdf (true)
Размер: 24.9 MB
This new volume aims to find real-world solutions to present-day problems by using IoT and related technologies. The volume explores the diverse applications of the Internet of Things in diverse areas―in healthcare, the construction industry, in wildlife monitoring, in home security systems, in agriculture, in cryptology, in hospitality employment, in data security, and more. The chapters illustrate the aspects of defining the architecture, product design, modules, interfaces, and data for a system to satisfy specified requirements of the IoT applications discussed. The chapters show the novel results that can safely be applied in their respective domains. In this context, the editors expect that the present solutions can meet the ever-increasing demand of industries. With chapters from both academics and industry professionals involved in IoT/AI solutions, System Design Using Internet of Things with Deep Learning Applications will be a valuable resource for students in this area as well as for those working in novel architecture design and system implementation.
Автор: Arpan Deyasi, Angsuman Sarkar, Soumen Santra
Издательство: Apple Academic Press, CRC Press
Год: 2024
Страниц: 282
Язык: английский
Формат: pdf (true)
Размер: 24.9 MB
This new volume aims to find real-world solutions to present-day problems by using IoT and related technologies. The volume explores the diverse applications of the Internet of Things in diverse areas―in healthcare, the construction industry, in wildlife monitoring, in home security systems, in agriculture, in cryptology, in hospitality employment, in data security, and more. The chapters illustrate the aspects of defining the architecture, product design, modules, interfaces, and data for a system to satisfy specified requirements of the IoT applications discussed. The chapters show the novel results that can safely be applied in their respective domains. In this context, the editors expect that the present solutions can meet the ever-increasing demand of industries. With chapters from both academics and industry professionals involved in IoT/AI solutions, System Design Using Internet of Things with Deep Learning Applications will be a valuable resource for students in this area as well as for those working in novel architecture design and system implementation.