GEMINI: DiGital twin for Emission MonItoring aNd predIction – Kista Case
The commitment to decarbonization and positive energy district (PED) is driving cities and service providers to leverage emerging techniques to promote sustainability that could improve or innovate conventional practices in all fields. To support policy decisions, the project proposes a Digital Twin model, named GEMINI, for emission monitoring and prediction in cities. The GEMINI brings together multisource data into a single platform and uses data/AI analytics and simulation techniques to holistically create system understanding and knowledge (what was or is …). It also connects IoT sensor data as the basis for knowledge-based decision-making targeting different aspects of sustainability and policy interventions in cities (what if …). The project will prototype and demonstrate the GEMINI platform in Kista and also with the intention to scale up to the City of Stockholm. The GEMINI platform is designed in a general and modular way that could be extended for applications beyond the project, such as energy consumption and noise emissions.
PI: Zhenliang Ma, KTH. PI: Paolo Santi, MIT