Machine and Deep Learning Model for Industrial Iot Applications

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Dr. Komala C. R., Dr. R. G. Vidhya, Dr. Varalatchoumy M., Dr. R. Aruna, Prof. Sipra Panigrahi, Prof. Sonia Maria D’Souza

Abstract

Smart connectivity with existing networks and context-aware computation using networkresources is an indispensable part of IoT. With the growing presence of Wi-Fi and 4G-LTEwireless Internet access, the evolution towards ubiquitous information and communicationnetworks is already evident. However, for the Internet of Things vision to successfully emerge, the computing paradigm will need to go beyond traditional mobile computing scenarios that use smartphones and portables, and evolve into connecting everyday existing objects and embeddingintelligence into our environment. For technology to disappear from the consciousness of the user,the Internet of Things demands: a shared understanding of the situation of its users and theirappliances, software architectures and pervasive communication networks to process and conveythe contextual information to where it is relevant, and the analytics tools in the Internet of Thingsthat aim for autonomous and smart behavior. With these three fundamental grounds in place, smartconnectivity and context- aware computation can be accomplished.

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