Eye in the Sky Detection and Compliance Monitoring of Brick

Deep Learning
Object Detection
Author

Suraj Jaiswal

Published

May 24, 2024

Paper accepted in ACM Compass (Conference on Computing and Sustainable Societies) 2024 Poster track.

Live Streamlit Demo App: link

Keywords:

Object Detection, Satellite Imagery, Deep Learning, Transfer Learning

Abstract:

  • 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 YOLOv8 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.

  • In addition, we have deployed our model as a web application for automatically identifying brick kilns given a specific area by the user.

To know more check: Paper