Deep Learning: A Predictive Iot Data Analytics Method

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2020 by IJETT Journal
Volume-68 Issue-7
Year of Publication : 2020
Authors : Ayushi Chahal, Preeti Gulia
DOI :  10.14445/22315381/IJETT-V68I7P205S

Citation 

MLA Style: Ayushi Chahal, Preeti Gulia  "Deep Learning: A Predictive Iot Data Analytics Method" International Journal of Engineering Trends and Technology 68.7(2020):25-33. 

APA Style:Ayushi Chahal, Preeti Gulia. Deep Learning: A Predictive Iot Data Analytics Method  International Journal of Engineering Trends and Technology, 68(7),25-33.

Abstract
IoT provides a platform for sensor devices enabling information sharing across the platforms. IoT allows these devices to communicate without any interruption within a smart environment in convenient manner. In this digital era, correlation of data and Internet of Things (IoT) is red-hot area for data analysts. Amalgamation of Big data analytics with machine learning concepts has engendered interest of many researchers. Any IoT framework produces gigantic amount of data. This data is of no use if not analyzed and reviewed properly. This study is focusing on predictive analytics techniques that can be used in an IoT enabled environment. Paper sheds light on various data analytical methodologies. Brief introduction to architecture of deep learning is given. There are different intelligent machine learning algorithms elucidated in this study and deep learning is also one of them. Deep Learning is considered as the advanced artificial intelligence technology, which can be used in analytics and learning process of IoT data. It expounds the reasons of using deep learning for predictive IoT data analytics. Besides, introducing readers to different algorithms of deep learning which can be helpful in predictive analytics, it also elaborates their working in detail with the help of their architectures.

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Keywords
Deep Learning, Internet of Things (IoT), Machine Learning, Neural Networks, Predictive analytics.