  Air pollution kills 7 million people annually. The brick manufacturing
industry accounts for 8%-14% of air pollution in the densely populated
Indo-Gangetic plain. Due to the unorganized nature of brick kilns, policy
violation detection, such as proximity to human habitats, remains challenging.
While previous studies have utilized computer vision-based machine learning
methods for brick kiln detection from satellite imagery, they utilize
proprietary satellite data and rarely focus on compliance with government
policies. In this research, we introduce a scalable framework for brick kiln
detection and automatic compliance monitoring. We use Google Maps Static API to
download the satellite imagery followed by the YOLOv8x model for detection. We
identified and hand-verified 19579 new brick kilns across 9 states within the
Indo-Gangetic plain. Furthermore, we automate and test the compliance to the
policies affecting human habitats, rivers and hospitals. Our results show that
a substantial number of brick kilns do not meet the compliance requirements.
Our framework offers a valuable tool for governments worldwide to automate and
enforce policy regulations for brick kilns, addressing critical environmental
and public health concerns.
