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Project # 66
AI-assisted Automatic Construction Activity Detection and Classification Using Computer Vision for Environmental Impact Assessment
| Team Lead: | Justine Talia Gacho |
| Other Team Members: | Tingkai Wang |
| Faculty Advisor(s): | Dr. Xinbao Yu |
| Department: | CE |
| Project Type: | REU |
| Title: | AI-assisted Automatic Construction Activity Detection and Classification Using Computer Vision for Environmental Impact Assessment |
| Abstract: | Construction activities (CA) alter the natural state of surface soils, significantly impacting urban environments by generating large amounts of sediment and increasing air and water pollution levels. Monitoring construction activities is crucial to studying their environmental impact and implementing control measures to improve safety and sustainability. Conventional CA monitoring methods only provide data with instruments installed at limited locations with limited data collection, usually insufficient to quantify the impact at a large watershed scale. The recent rapid growth in aerial imagery and AI in computer vision (CV) makes it possible to conduct spatiotemporal watershed-level studies of construction activities. This research uses high-resolution orthoimagery of the DFW area to develop an AI-assisted computer algorithm to automatically detect and classify construction activities. The classified construction activity dataset is combined with other relevant datasets on water turbidity, precipitation, and soil properties to create a curated database quantifying soil-based environmental impact. |
| Poster: | View Poster #66 (PDF) |
| Judges Scoring: | Submit Evaluation (judges only) |