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Deep Learning-Enabled Edge Computing and IoT
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Author(s): Amuthan Nallathambi (AMC Engineering College, Visvesvaraya Technological University, India)and Kannan Nova (Microsoft, USA)
Copyright: 2023
Pages: 25
Source title:
Convergence of Deep Learning and Internet of Things: Computing and Technology
Source Author(s)/Editor(s): T. Kavitha (New Horizon College of Engineering (Autonomous), India & Visvesvaraya Technological University, India), G. Senbagavalli (AMC Engineering College, Visvesvaraya Technological University, India), Deepika Koundal (University of Petroleum and Energy Studies, Dehradun, India), Yanhui Guo (University of Illinois, USA)and Deepak Jain (Chongqing University of Posts and Telecommunications, China)
DOI: 10.4018/978-1-6684-6275-1.ch004
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Abstract
Deep learning is a new approach to artificial intelligence that enables edge-computing systems to learn from data and take decisions without human intervention. Edge computing is a technique for coping with the increasing demand for streaming data. This is especially important in the case of applications that involve computationally intensive tasks such as driverless cars, autonomous drones, and smart cities. Edge computing is the provision of computing, big data analytics, and storage in such a way that the data comes to the processing power and not vice versa. It relies on a decentralized approach where computational resources are provided at the edge of networks. Edge computing is an emerging field that's getting attention from many vendors and researchers. The data generated by IoT devices is usually too large and complex for cloud-based storage and processing. That's why edge computing can handle data at the source of generation in real time, which speeds up the process of decision making.
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