Endorsed by our host institution, National Taiwan University, Con-API’s research on Multi-Granular Crew Activity Recognition for Construction Monitoring has been featured by Asia Research News, highlighting its contribution to advancing AI-driven productivity analysis in construction.
The featured work is based on our paper published in the 179th volume of Automation in Construction, which introduces a multi-granular framework that recognizes individual actions, collaborative crew behavior, and task-level activities from construction site imagery. By capturing how workers interact and collaborate on site, the method improves the accuracy and scalability of automated construction progress monitoring.
This study was authored by our team member and alumni Cheng Yun Tsai and Mik Wanul Khosiin, whose high-quality work demonstrates the practical potential of artificial intelligence in improving construction productivity, site monitoring, and decision-making. We are proud to see their work recognized internationally and shared with a broader audience through Asia Research News.
Cheng-Yun Tsai
(蔡承耘)
Master Graduate
Crew Productivity Analysis
Mik Wanul Khosiin
Doctorate Graduate
Human Object Interaction
Read the full Asia Research News feature here ❐, and explore the complete journal paper here ❐.