Deep learning in the fog - Publikacja - MOST Wiedzy


Deep learning in the fog


In the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high computing capabilities. Processing all the data in the cloud may not be sufficient in cases when we need privacy and low latency, and when we have limited Internet bandwidth, or it is simply too expensive. It poses a challenge for creating a new generation of fog computing that supports artificial intelligence and selects the architecture appropriate for an intelligent solution. In this article, we show from four perspectives, namely, hardware, software libraries, platforms, and current applications, the landscape of components used for developing intelligent Internet of Things solutions located near where the data are generated. This way, we pinpoint the odds and risks of artificial intelligence fog computing and help in the process of selecting suitable architecture and components that will satisfy all requirements defined by the complex Internet of Things systems.


  • 1 0


  • 6

    Web of Science

  • 1 0


Słowa kluczowe

Informacje szczegółowe

Publikacja w czasopiśmie
artykuły w czasopismach
Opublikowano w:
International Journal of Distributed Sensor Networks nr 15, strony 1 - 19,
ISSN: 1550-1477
Rok wydania:
Opis bibliograficzny:
Sobecki A., Szymański J., Gil D., Mora H.: Deep learning in the fog// International Journal of Distributed Sensor Networks -Vol. 15,iss. 8 (2019), s.1-19
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1177/1550147719867072
Politechnika Gdańska

wyświetlono 77 razy

Publikacje, które mogą cię zainteresować

Meta Tagi