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The Symbiosis of Distributed Ledger and Machine Learning as a Relevance for Autonomy in the Internet of Things

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Title:The Symbiosis of Distributed Ledger and Machine Learning as a Relevance for Autonomy in the Internet of Things
Authors:Burkhardt, Daniel
Frey, Patrick
Lasi, Heiner
Keywords:Distributed Ledger Technology, The Blockchain
Internet and the Digital Economy
Internet of Things, Autonomous Assets, Distributed Ledger, Artificial Intelligence, Machine Learning
Date Issued:08 Jan 2019
Abstract:The Internet of Things (IoT) describes the fusion of the physical and digital world which enables assets on the edge to send data to a platform where it gets analyzed. Defined actions are then triggered to influence cross-functional edge activities. Furthermore, on the platform tier functionalities and relations need to be identified and implemented to realize assets operating autonomously and ubiquitously. The exploration of this paper results in the identification of autonomous characteristics and shows functional components to implement autonomous assets on the edge. Distributed Ledger Technology (DLT) and its fusion with Machine Learning (ML) as an area of Artificial Intelligence (AI) provides an integral part to realize the described outline. Thus, the recognition of DLT’s and ML’s usage in the IoT and the evaluation of the relevance as well as the synergies build the main focus of this paper.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/59900
ISBN:978-0-9981331-2-6
DOI:10.24251/HICSS.2019.559
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Distributed Ledger Technology, The Blockchain


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