Special Session 6

Chairs

Shouzhong FENG, Professor, School of Civil Engineering and Architecture, Anhui University of Science and Technology

Antonio Peña-García, Professor, Department of Civil Engineering, University of Granada

Yi SHEN, Associate Researcher, College of Civil Engineering, Tongji University

The Digital Green Tunnel represents a next-generation infrastructure that integrates sensing technologies, data analytics, and automated systems to enhance the performance, sustainability, and operational intelligence of tunnel environments. This session focuses exclusively on the technological and data-driven aspects of these advanced systems, moving beyond traditional engineering to explore how digital integration and green solutions can be systematically optimized. It aims to address key challenges in real-time decision-making and resource allocation, establishing a green framework for intelligent, self-adapting tunnel systems. By fostering collaboration across disciplines such as data science, environmental engineering, and intelligent systems, this session seeks to define the future standards for data-driven management in green and digital infrastructure.

We invite contributions on the development and application of sensing, modeling, and management frameworks for Digital Green Tunnels. Abstracts should emphasize technical methodologies, data fusion, and system-level outcomes. Topics of interest include, but are not limited to:

(1)     Multi-Modal Sensing & Data Acquisition

• Integration of IoT sensors, computer vision, and  wireless signals for monitoring environmental and structural conditions.

• Deployment of non-intrusive sensing networks for real-time tracking of green infrastructure performance (e.g., plant health, air quality).

• Use of VR/AR and digital simulation for modeling tunnel systems and automated responses.

(2)     Data Analytics & Model Development

• Data fusion and machine learning for predicting environmental dynamics and system behavior.

• Pattern recognition in operational data to optimize energy use, airflow, and lighting systems.

• Development of digital twin frameworks for scenario testing and predictive control.

(3)     Intelligent Design & Automated Management

• Data-informed strategies for integrating renewable energy, adaptive lighting, and green infrastructure.

• Algorithms for automated operation, maintenance scheduling, and resource allocation.

• System architectures enabling real-time control and optimization of tunnel environments.