European Research Center for Social Development

Tag: Energy Efficiency

  • Application and Characterization of Metamodels based on Artificial Neural Networks for Building Performance Simulation: A Systematic Review

    Application and Characterization of Metamodels based on Artificial Neural Networks for Building Performance Simulation: A Systematic Review

    As the global demand for energy-efficient buildings grows, traditional simulation tools are becoming too slow to keep up with the complexity of sustainable design.

    This research presents a comprehensive review of Artificial Neural Networks (ANNs) as a high-speed solution for Building Performance Simulation (BPS). By acting as “metamodels” (or digital proxies) ANNs can predict a building’s energy consumption and comfort levels almost instantaneously, allowing architects to test thousands of design variations in seconds.

    The study explicitly details the entire lifecycle of creating these AI models, from data pre-processing to final testing.

    While acknowledging that ANNs require significant initial data to “learn,” the authors demonstrate that the trade-off is worth it: the resulting models are powerful enough to guide both the design of new structures and the retrofitting of old ones.

    For the engineering community, this paper serves as a technical manual for integrating AI into the heart of sustainable urban development.

    Learn more about this study here: https://doi.org/10.1016/j.enbuild.2020.109972

    Reference

    Roman, N. D., Bre, F., Fachinotti, V. D., & Lamberts, R. (2020). Application and characterization of metamodels based on artificial neural networks for building performance simulation: A systematic review. Energy and Buildings, 217, 109972

  • Building Sustainable Smart Cities for Energy Efficiency and CO2 Emission Reduction: Insights from Europe

    Building Sustainable Smart Cities for Energy Efficiency and CO2 Emission Reduction: Insights from Europe

    As we look toward a future where more than 70% of global CO2 emissions come from our urban centers, the pressure to redesign how cities function has never been higher.

    This research explores the “Sustainable Smart City” (SSC) as a vital framework for breaking our dependence on fossil fuels and fixing deep-seated energy inefficiencies.

    By examining successful models across Europe, the study investigates how the digital and physical worlds can merge to create urban environments that are both high-tech and low-impact.

    The methodology focuses on the integration of “triple-threat” technologies: the Internet of Things (IoT), Artificial Intelligence (AI), and smart grids. These tools are analyzed for their ability to revolutionize renewable energy distribution, streamline transportation, and automate waste management.

    While the study draws its primary lessons from the European experience, it specifically aims to create a blueprint for nations like Sri Lanka to meet their own climate goals.

    The findings suggest that technological innovation alone isn’t enough; the true catalyst for change is a combination of stakeholder collaboration and robust policy reform.

    Ultimately, the research concludes that by adopting this research-driven framework, developing urban centers can successfully transition into sustainable hubs that enhance the quality of life without exhausting the planet’s resources.

    Learn more about this paper here: https://link.springer.com/chapter/10.1007/978-981-96-9551-5_11

    Reference

    Udayantha, U.L.I., Dias, S.N.C.M. (2025). Building Sustainable Smart Cities for Energy Efficiency and CO2 Emission Reduction: Insights from Europe. In: Dissanayake, R., De Alwis, A., Bekchanov, M., Gajanayake, P., Gunawardhana, S. (eds) Proceedings of the International Conference on Resource Efficiency Towards Sustainability. ICRES 2025. Proceedings in Technology Transfer. Springer, Singapore