Research and development

The SmartMet Lab at OsloMet specializes in smart infrastructure monitoring and maintenance, employing cutting-edge technologies like drones, robotics, AI, digital twins, and advanced cameras. 

The lab focuses on enhancing the safety, resilience, and sustainability of infrastructure such as bridges, tunnels, roads, and buildings, including underwater structures. It drives innovation in sustainable infrastructure through advanced technology, interdisciplinary research, and practical applications.

Key Focus Areas

• Smart Monitoring: Utilizing different types of drones and robotics for inspections, including aerial drones for structural assessments and underwater robotics for submerged infrastructure.
• AI and Predictive Maintenance: Machine learning models to identify and predict issues for efficient maintenance planning.
• Digital Twin Technology: Virtual models to analyze and forecast infrastructure performance.
• Collaboration: Partnering with industry, academia, and public stakeholders to deliver practical solutions.

Facilities and Technology

• High-Performance Computers: Powerful computing systems designed for simulation, modeling, and data analysis.
• Advanced Sensors and Cameras: Including LiDAR, strain gauges, accelerometers, and imaging tools for precise monitoring and data collection.
• Drones and Robotics: A range of aerial drones and underwater robotics tailored for over- and underwater infrastructure inspections.
• Collaborative Spaces: Dedicated areas for brainstorming and interdisciplinary research.
  For Students and Researchers
• Hands-on experience with drones, robotics, and advanced data collection tools.
• Opportunities for interdisciplinary research in civil engineering, AI, and environmental monitoring.

Location

Room: PI 847, Pilestredet 35

Contact

Email to SmartMet Lab

The Smart Mobility Lab at OsloMet specializes in developing innovative solutions for sustainable urban transport, with a focus on intelligent transportation systems, shared mobility, active mobility, and data-driven decision-making tools to support smart and sustainable cities.

The lab focuses on enhancing the safety, resilience, and sustainability of urban transport networks by integrating advanced technologies, promoting multimodal mobility, and leveraging real-time data analytics.

Through interdisciplinary research and close collaboration with public and private sector stakeholders, the lab aims to address pressing mobility challenges and contribute to the transition toward low-carbon, inclusive urban environments.

Key Focus Areas

• Active Mobility: Promotion of walking and cycling through infrastructure design, safety analysis, and behavioural studies to support healthier and more sustainable travel modes.
• Data-Driven Mobility Planning: Application of big data, AI, and simulation models to inform transport policies, optimize operations, and support scenario-based planning for future mobility systems.
• Sustainability and Emissions Reduction: Assessment of environmental impacts from transport activities and development of low-emission strategies in collaboration with local authorities and industry partners.
• Multimodal Transport Planning: Development of integrated mobility strategies that connect various modes of transport – such as walking, cycling, public transport, and shared mobility – into seamless, user-centred travel chains.
• Transport Poverty and Equity: Research and interventions aimed at identifying and addressing transport-related social exclusion, ensuring equitable access to mobility services for underserved communities, and reducing barriers related to cost, availability, and physical accessibility.

Facilities and Technology

• Simulation and Testing Platforms: Software and hardware setups for virtual testing of mobility scenarios, agent-based models, and traffic simulations in controlled environments.
• Advanced Sensors and Cameras: Including LiDAR, Eye Tracker, accelerometers, and imaging tools for precise monitoring and data collection.
• Comprehensive Data Sets: Access to diverse datasets covering mobility patterns, transport infrastructure, emissions, accessibility, and user behaviour. These datasets are collected via sensors, surveys, APIs, and open data portals, and are used to support data-driven research, modelling, and policy development.

Contact