  Modern telescope facilities generate data from various sources, including
sensors, weather stations, LiDARs, and FRAMs. Sophisticated software
architectures using the Internet of Things (IoT) and big data technologies are
required to manage this data. This study explores the potential of sensor data
for innovative maintenance techniques, such as predictive maintenance (PdM), to
prevent downtime that can affect research. We analyzed historical data from the
ASTRI-Horn Cherenkov telescope, spanning seven years, examining data patterns
and variable correlations. The findings offer insights for triggering
predictive maintenance model development in telescope facilities.
