Welcome to SMART-X Lab.

At SMART-X Lab, we aim to revolutionize the future of energy and resources engineering through the convergence of artificial intelligence, robotics, and digital technologies.

Located at Sejong University, our interdisciplinary team develops intelligent systems for smart mining, renewable energy applications, space resource exploration and extraction, and sustainable operations in energy and resource systems.

We collaborate with academic, industrial, and public partners to conduct impactful research, contribute to policy and innovation, and train the next generation of engineers and researchers.

Join us as we advance the frontier of SMART energy and resource technologies.

🏆 What We Do

At SMART-X Lab, we pursue convergence research to innovate the future of energy and resources engineering by integrating AI, robotics, and digital technologies.

Design AI-powered smart mining systems that optimize the entire value chain of critical minerals—from exploration and drilling to hauling and shipment—enhancing safety, efficiency, and autonomy in both open-pit and underground mines.
Advance autonomous and robotic technologies, including drones, unmanned loaders, automated haulage systems, and collaborative robots, to support unmanned and intelligent operations in mining and energy fields.
Develop digital twin models for mining operations, underground infrastructure, and renewable energy systems to enable real-time monitoring, predictive maintenance, and intelligent control.
Build renewable energy solutions through the integration of solar, wind, and energy storage systems, with a focus on vehicle-integrated PV, energy-sharing systems, and sustainable infrastructure for remote or off-grid mining sites.
Promote sustainable system operation through the convergence of smart energy, clean resource utilization, and carbon-neutral technology deployment.
Apply GIS, remote sensing, and IoT technologies for smart geospatial analysis, environmental monitoring, and intelligent resource management.
Explore and simulate space resource utilization, including lunar and asteroid mining scenarios, by developing AI-driven prospecting, autonomous excavation, and in-situ resource utilization (ISRU) technologies for future extraterrestrial infrastructure and energy systems.

Our lab’s work spans multiple domains—from Earth to space—contributing to sustainable development, digital transformation, and the future of clean energy and resource systems.

⚡ Recently Added

☀️ Pioneering the Future of Energy and Resources Engineering

This illustration captures the vision of next-generation energy and resources engineering. It features a smart mining engineer utilizing digital tools such as AI, drones, and IoT in a sustainable landscape powered by renewable energy. From autonomous mining trucks to wind turbines and solar panels, the image symbolizes the integration of green technologies, digital transformation, and carbon-neutral practices. The Korean phrase "새로운 길을 열다" at the top translates to "Opening New Paths," representing innovation, sustainability, and progress.

📰 SMART-X Lab at the 2025 KSMER Spring Conference in Jeju

Members of the SMART-X Lab participated in the 124th Spring Conference of the Korean Society of Mineral and Energy Resources Engineers (KSMER) held in Jeju from May 28–30, 2025. Our team proudly presented six oral papers covering topics in smart mining, renewable energy systems, and AI-based resource technologies. This group photo captures our commitment to academic excellence and innovation in energy and resources engineering.

🔋 On-grid Wind–Flow Battery Energy System for Sustainable EV Charging

Published in Sustainable Cities and Society, Vol. 128, June 2025

Authors: Yosoon Choi, Shubhashish Bhakta

This study explores the integration of wind energy and zinc-bromine flow battery (ZBFB) storage into grid-connected electric vehicle (EV) charging stations. Using HOMER Grid simulation, the research evaluates optimal system configurations under Korean energy pricing policies and EV charging tariffs.

⚡ Real-World Performance of Bifacial PV–Flywheel Hybrid System for EV Charging

Published in: Applied Thermal Engineering, Vol. 229, September 2025
Authors: Yosoon Choi, Shubhashish Bhakta

This study evaluates the field performance of a grid-connected electric vehicle charging system that integrates bifacial photovoltaic (PV) panels with flywheel energy storage. Installed on a university campus parking lot in South Korea, the system was analyzed using both real-time data and HOMER Grid simulations. The results show that the bifacial PV modules enhanced solar energy yield by capturing reflected light, while the flywheel stabilized output for intermittent charging loads. The system demonstrated a cost-effective and technically reliable approach to sustainable EV charging under real-world urban conditions.

📊 A New KPI for Evaluating Haulage Systems: Integrated Insights from the Open-Pit Mining Frontier

Published in: Ain Shams Engineering Journal, Vol. 16, June 2025

Authors: Sebeom Park, Dahee Jung, Yosoon Choi

This study introduces a novel integrated Key Performance Indicator (KPI) framework designed to evaluate the operational efficiency of open-pit mine haulage systems more holistically. By incorporating nine standardized KPIs developed by the Global Mining Guidelines Group (GMG), the researchers aimed to overcome the limitations of individual performance indicators—such as uptime, utilization, or production efficiency—by synthesizing them into a single, intuitive benchmark. The proposed integrated KPI enables mine operators to assess system performance more clearly, supporting better real-time decision-making, maintenance scheduling, and long-term asset management strategies.

🚘 Smart Parking Assistance for Solar EVs: Merging 360° VR Imaging with Real-Time Solar Forecasting

Published in: Applied Energy, Vol. 397, November 2025
Authors: Jimin Hong, Yosoon Choi

In a step toward smarter solar EV usage, this study introduces a novel parking assistance system that helps drivers choose parking spots with the best solar exposure. The system uses a 360° VR camera mounted on the vehicle to capture hemispherical sky images, which are analyzed to detect shading. It also integrates real-time solar radiation forecasting based on meteorological data and deep learning models.

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