Deep Learning for the Internet of Things

How can the advantages of deep learning be brought to the emerging world of embedded IoT devices? The authors discuss several core challenges in embedded and mobile deep learning, as well as recent solutions demonstrating the feasibility of building IoT applications that are powered by effective, ef...

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Bibliographic Details
Published inComputer (Long Beach, Calif.) Vol. 51; no. 5; pp. 32 - 41
Main Authors Yao, Shuochao, Zhao, Yiran, Zhang, Aston, Hu, Shaohan, Shao, Huajie, Zhang, Chao, Su, Lu, Abdelzaher, Tarek
Format Journal Article
LanguageEnglish
Published New York IEEE 01.05.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Computational modeling
Deep learning
embedded learning
Embedded systems
Feature extraction
Internet of Things
IoT
Machine learning
mobile and embedded deep learning
Neural networks
Task analysis
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Summary:How can the advantages of deep learning be brought to the emerging world of embedded IoT devices? The authors discuss several core challenges in embedded and mobile deep learning, as well as recent solutions demonstrating the feasibility of building IoT applications that are powered by effective, efficient, and reliable deep learning models.
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ISSN:0018-9162
1558-0814
DOI:10.1109/MC.2018.2381131