  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.
