DCDC – Design for Complex and Dynamic Contexts
![DCDC24_EmissionVision](http://idlabb.blogs.dsv.su.se/files/2024/06/DCDC24_EmissionVision.jpg)
EmissionVision
Emission Vision is a digital twin implemented in mixed reality and designed to provide an interactive and collaborative way of analyzing global CO2 emissions data and each country’s contribution. Over the years, CO2 emissions have steadily climbed and continue to rise. Consequently, it is crucial for policymakers and environmental analysts to provide accurate projections based on data patterns. By integrating real-world environmental data into a 3D visualization, Emission Vision enables users to better explore, analyze, and compare the complex trends of CO2 emissions ratio around the world over time. Users can easily compare countries’ contributions, gain insights from the data, and collaborate in real-time, allowing analysts to work together to address global environmental challenges.
![DCDC24_TwinTurbine](http://idlabb.blogs.dsv.su.se/files/2024/06/DCDC24_TwinTurbine.jpg)
Twin Turbine
Welcome to TwinTurbine, a cutting-edge digital twin project designed to let you experience the operation of a wind turbine in a mixed reality (MR) environment. MR enables multi-user collaboration, allowing multiple users to monitor and control the wind turbine’s operations from remote locations. By leveraging MR, users can visualize the wind turbine and its real-time data in a Mixed reality environment, receive immediate feedback, and interact dynamically with the physical turbine throughout the experience. As accessing a real physical turbine was not feasible, we used a scaled physical turbine model to accurately emulate the behavior of a real wind turbine.