Node and block-based development tools for distributed systems with AI applications

  • Internet of Things (IoT) and Artificial Intelligence (AI) are one of the most promising and disruptive areas of current research and development. However, these areas require deep knowledge in multiple disciplines such as sensors, protocols, embedded programming, distributed systems, statistics and algorithms. This broad knowledge is not easy to acquire and the software used to design these systems is becoming increasingly complex. Small and medium-sized enterprises therefore have problems in developing new business ideas. However, node- and block-based software tools have also been released and are freely available as open source toolboxes. In this paper, we present an overview of multiple node- and block-based software tools to develop IoT- and AI-based business ideas. We arrange these tools according their capabilities and further propose extension and combinations of tools to design a useful open-source library for small and medium-sized enterprises, that is easy to use and helps with rapid prototyping, enabling new business ideas to be developed using distributed computing.

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Author:Marcel Hauck, Rüdiger Machhamer, Levin Czenkusch, Klaus-Uwe Gollmer, Guido Dartmann
Parent Title (English):IEEE Access
Document Type:Article (specialist journals)
Date of OPUS upload:2022/11/08
Date of first Publication:2019/10/15
Release Date:2022/11/08
Tag:Internet of Things; distributed computing; machine learning; rapid prototyping; visual programming environments
GND Keyword:Internet der Dinge; Künstliche Intelligenz; Maschinelles Lernen; Verteiltes System; Rapid Prototyping; Programmierumgebung
Page Number:11
First Page:143109
Last Page:143119
Departments:Institute / ISS - Institut für Softwaresysteme in Wirtschaft, Umwelt und Verwaltung
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International