AIoT for Smart Construction (AISC)

The construction industry is rapidly evolving toward sensor-driven, data-centric, and automation-ready workflows, where IoT becomes the “nervous system” of jobsites and built assets. By connecting heterogeneous sensors with BIM and digital twins, IoT enables real-time situational awareness, proactive safety and quality control, and lifecycle optimization.

This special session provides a focused forum on IoT-enabled construction intelligence, emphasizing (i) end-to-end sensing-to-decision pipelines, (ii) trustworthy data management and interoperability, and (iii) validated deployment in real projects or public benchmarks. The session welcomes both foundational research and applied case studies on smart construction and smart buildings.

Topics of interest:
The special section seeks original contribution in, but not limited to, the following topics:

• AIoT-enabled jobsite sensing and real-time decision support
• BIM and digital twin grounded monitoring, reasoning, and automation
• Multimodal intelligence for construction (LLM, VLM, VQA) for reporting and field assistance
• Edge AI and on-device inference for low-latency construction applications
• Low-altitude economy for construction: UAV inspection, mapping, progress tracking, and aerial IoT
• UAV–BIM or UAV–digital twin integration for defect localization and asset traceability
• Safety and risk analytics using AIoT (fall from height, PPE, hazardous zones)
• Quality and defect inspection (crack, surface damage, MEP issues) with automated documentation
• Predictive maintenance and asset health monitoring for equipment and building systems
• Interoperability, data governance, security, privacy, and trustworthy AI for AIoT systems

Session Co-chairs:

• Dr. Hai Chien Pham (Ton Duc Thang University, Vietnam)
• Dr. Nghia Hoai Nguyen (International University, Vietnam National University–HCMC, Vietnam)
• Dr. Quang Tuan Le (Saigon University, Viet Nam)
• Dr. Akeem Pedro, (Sogang University, Republic of Korea)
• Prof. Duc-Kien Thai (Sejong University, Republic of Korea)

Important dates: As of the main tracks
Contact: Dr Hai Chien Pham (phamhaichien@tdtu.edu.vn)