  A dataset of street light images is presented. Our dataset consists of
$\sim350\textrm{k}$ images, taken from 140 UMBRELLA nodes installed in the
South Gloucestershire region in the UK. Each UMBRELLA node is installed on the
pole of a lamppost and is equipped with a Raspberry Pi Camera Module v1 facing
upwards towards the sky and lamppost light bulb. Each node collects an image at
hourly intervals for 24h every day. The data collection spans for a period of
six months.
  Each image taken is logged as a single entry in the dataset along with the
Global Positioning System (GPS) coordinates of the lamppost. All entries in the
dataset have been post-processed and labelled based on the operation of the
lamppost, i.e., whether the lamppost is switched ON or OFF. The dataset can be
used to train deep neural networks and generate pre-trained models providing
feature representations for smart city CCTV applications, smart weather
detection algorithms, or street infrastructure monitoring. The dataset can be
found at \url{https://doi.org/10.5281/zenodo.6046758}.
