{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/towards-an-ai-enabled-connected-industry-agv","title":"Toward an AI-enabled Connected Industry: AGV Communication and Sensor Measurement Datasets","arxiv_id":"2301.03364","date":"2022-12-20","proceeding":null,"authors":["Rodrigo Hernangómez","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"],"abstract":"This paper presents two wireless measurement campaigns in industrial testbeds: industrial Vehicle-to-vehicle (iV2V) and industrial Vehicle-to-infrastructure plus Sensor (iV2I+), together with detailed information about the two captured datasets. iV2V covers sidelink communication scenarios between Automated Guided Vehicles (AGVs), while iV2I+ 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 Machine Learning (ML) for tasks such as fingerprinting, line-of-sight detection, prediction of quality of service or link selection. Moreover, the datasets are publicly available, labelled and prefiltered for fast on-boarding and applicability.","url_abs":"https://arxiv.org/abs/2301.03364v5","url_pdf":"https://arxiv.org/pdf/2301.03364v5.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"towards-an-ai-enabled-connected-industry-agv","repo_url":"https://github.com/fraunhoferhhi/ai4mobile-industrial","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[{"method_slug":null,"method_name":null}],"datasets_introduced":[{"slug":"iv2v-and-iv2i","name":"iV2V and iV2I+","full_name":"AI4Mobile Industrial Wireless Datasets: iV2V and iV2I+"}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}