Gamifying City Decarbonisation
Researchers at Future Resilient Systems (FRS) build interactive learning and AI-driven insights to drive decarbonisation in the built environment.
Project Summary
- Reducing emissions through an app: FRS has developed the "GHG App" to assist users in assessing and reducing greenhouse gas emissions in buildings through interactive simulations.
- AI-powered education: The app includes a serious game and an AI chatbot called "ChatGHG," which offers users practical learning and valuable insights into emissions.
- Supporting decarbonisation: By integrating AI and gamification, the app boosts public involvement in sustainability initiatives and educates future urban policy.
Exposition
We need innovative solutions to fight the issues of urbanisation, climate change, and environmental degradation. As an emerging concept, Urban Digital Twins (UDTs) provide a simplified representation of real-world systems but often struggle to connect theoretical insights with real actions. Without effective engagement and interaction, UDTs' full potential remains untapped. Educating a broad audience on greenhouse gas (GHG) emissions requires accessible and inventive methods. Data collection and the effective use of Artificial Intelligence (AI) within UDTs are crucial for turning insights into actionable strategies, but how can users be fully engaged in this process?
Conflicts & Actions
To address these gaps, FRS researchers have developed the "GHG App," an open-access, web-based platform designed to assess and potentially reduce operational GHG emissions in the built environment of Singapore. This app serves as a cutting-edge tool for addressing the complex issue of decarbonisation, integrating both AI and UDTs to provide users with practical, real-world applications. Within the GHG App, two powerful tools are embedded: a serious game and an AI-powered chatbot, "ChatGHG."
The serious game transforms the challenge of GHG mitigation into an interactive, play-based experience. By simulating real-world scenarios, users are tasked with reducing emissions through actions like retrofitting building energy systems, installing solar panels, or managing the increased demand for electric vehicle energy. These scenarios give users hands-on learning opportunities, making them active participants in decarbonisation efforts rather than passive observers. The serious game allows users to visualise the direct consequences of their actions, helping them understand the importance of sustainable practices.
Complementing this, ChatGHG, a custom-built conversational AI developed using FRS BounceBack, engages users with tailored information about GHG emissions specific to Singapore’s context. It guides users through complex topics, from understanding GHG data to exploring strategies for reducing emissions. As an open-access tool, it bridges the gap between research and public engagement, providing decision-makers and citizens alike with critical insights into energy use and emission reduction.
Resolutions
These innovative features are not only helping users learn but also actively shaping the future of public engagement in environmental issues. Feedback from GHG App users has demonstrated the effectiveness of digital tools in educating and engaging the public in Singapore. By leveraging AI and gamification, FRS researchers are driving meaningful change in the way we approach urban sustainability and policymaking.
Future research will continue to enhance these tools, improving their functionality and expanding their use cases. As more AI-driven technologies are integrated into UDTs, the potential for city-wide decarbonisation becomes increasingly achievable. Through the GHG App, FRS aims to make climate action engaging and impactful for all, positioning itself as an urban sustainability innovator.
Further reading
- Alva, P., Mosteiro-Romero, M., Miller, C., & Stouffs, R. (2024). Mitigating operational greenhouse gas emissions in ageing residential buildings using an Urban Digital Twin dashboard. Energy and Buildings, 322. external page https://doi.org/10.1016/j.enbuild.2024.114681
- Alva, P., Biljecki, F., and Stouffs, R.: USE CASES FOR DISTRICT-SCALE URBAN DIGITAL TWINS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4/W4-2022, 5–12, external page https://doi.org/10.5194/isprs-archives-XLVIII-4-W4-2022-5-2022, 2022.