Crowdsourced AI-Supported IoT Data-Modeling (IM2021)
This research is presented at the IFIP/IEEE International Symposium on Integrated Network Management (IM), 17-21 May 2021 in Bordeaux, France that is held as a virtual event.
The paper is a follow-up from the paper M.-O. Pahl and G. Carle, “Crowdsourced Context-Modeling as Key to Future Smart Spaces,” in Network Operations and Management Symposium (NOMS), May 2014.
Abstract
A central challenge of today’s Internet of Things (IoT) remains interoperability. The IoT consists of entities that federate dynamically. Their software stacks interact by exchanging data. Data representations vary heavily between scenarios, domains, and vendors.
Interoperability requires common standards in data representation. Classical standardization typically takes time, and is domain-specific. This opposes the IoT with it various domains, vendors, and use cases.
This paper shows how Artificial Intelligence can help unifying IoT data models during creation. The solution consists of an open repository, an Eclipse-based editor frontend, syntax and semantics validation, and machine-learning supported tagging and completion of data models.
Different machine-learning algorithms are evaluated for their fit. The evaluation data set contains 1200 automatically converted data models from today’s most relevant IoT data modeling initiatives: Project Haystack, IoTSchema, and BrickSchema.
Marc-Oliver is Vice President of the German Chapter of the Association for Computing Machinery (ACM) (https://germany.acm.org/), he leads the axis Future Education of the German-French Academy for the Industry of the Future (https://future-industry.org/). He is continuously co-organizing scientific conferences since 2015. Until 2/2021, Marc-Oliver was co-leading a research team of more than 20 permanent researchers in the CNRS UMR LAB-STICC at IMT Atlantique. Until 10/2019, he headed a research team with 5 PhD students at Technical University of Munich.
Marc-Oliver’s research domains are cybersecurity, distributed networked systems, Internet of Things, data and service management. In addition to ethical aspects of computer science, Marc-Oliver promotes continuous exchange between business, academia and the public in the field of cybersecurity (https://future-iot.org/, https://talk.cybercni.fr/, https://being-human-with-algorithms.org/).
Besides his research around the Internet of Things and cybersecurity, Marc-Oliver loves teaching for a living. He has been continuously teaching Computer Networks and Distributed Systems at German and French universities since 2003. His biggest course is the freely available Massive Open Online Course (MOOC) "iLabX - The Internet Masterclass" (https://ilabx.ilabxp.com/).
Marc-Oliver is the recipient of numerous prestigious teaching awards. Among them the Ernst Otto Fischer Teaching Award 2013 and the PhD Supervisory Award 2020 of the Technical University of Munich.
Marc-Oliver conducts research in the national and international arena and has successfully acquired numerous research grants in the millions.
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