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Toward an AI-Enabled Connected Industry: AGV Communication and Sensor Measurement Datasets

Rodrigo Hernangόmez, Alexandros Palaios, Cara Watermann, Daniel Schäufele, Philipp Geuer, Rafail Ismayilov, Mohammad Parvini, Anton Krause, Martin Kasparick, Thomas Neugebauer, Oscar D. Ramos-Cantor, Hugues Tchouankem, Jose Leon Calvo, Bo Chen, Gerhard Fettweis, Sławomir Stańczak

Year
2024
Citations
15
Access
Open access

Abstract

This article presents two wireless measurement campaigns in industrial testbeds: industrial vehicle-to-vehicle (iV2V) and industrial vehicle-to-in-frastructure plus sensor (iV21+), with detailed information about the two captured datasets. iV2V covers sidelink communication scenarios between moving and stationary robots, while iV21+ is conducted at an industrial setting where an autonomous cleaning robot is connected to a private cellular network. The combination of different communication technologies within a common measurement methodology provides insights that can be exploited by ML for tasks, such as fingerprinting, line-of-sight detection, prediction of quality of service, or link selection. Moreover, the datasets are publicly available, labeled, and pre-filtered for fast on-boarding and applicability.

Keywords

Computer scienceWireless sensor networkComputer networkReal-time computingArtificial intelligenceEmbedded system

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