Massive Online Analytics for the Internet of Things (IoT)

Abstract :

Big Data and the Internet of Things (IoT) have the potential to fundamentally shift the way we interact with our surroundings. The challenge of deriving insights from the Internet of Things (IoT) has been recognized as one of the most exciting and key opportunities for both academia and industry. Advanced analysis of big data streams from sensors and devices is bound to become a key area of data mining research as the number of applications requiring such processing increases. Dealing with the evolution over time of such data streams, i.e., with concepts that drift or change completely, is one of the core issues in stream mining. In this talk, I will present an overview of data stream mining, and I will introduce some popular open source tools for data stream mining.

Document type :
Conference papers
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https://hal.telecom-paristech.fr/hal-02287774
Contributor : Telecomparis Hal <>
Submitted on : Friday, September 13, 2019 - 5:20:32 PM
Last modification on : Thursday, October 17, 2019 - 12:36:55 PM

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  • HAL Id : hal-02287774, version 1

Citation

Albert Bifet. Massive Online Analytics for the Internet of Things (IoT). The 6th Brazilian Conference on Intelligent Systems (BRACIS 2017), Oct 2017, Uberlandia, Brazil. ⟨hal-02287774⟩

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