Lectori Salutem – What about climate resilience and adaptation, and how can Information Systems help?
Editie: 31 - Global vs. Local
Published on: 07 juli 2024
The topic for this year’s edition of the SERVICE Magazine and for this piece is the effect of globalization in the development of real estate. Globalization has fundamentally transformed the real estate sector, creating a landscape that is interconnected, dynamic, and increasingly complex. This transformation is driven by the rapid flow of capital, the mobility of populations and goods, and the integration of international markets, but unfortunately also has a close relationship with climate change.
The built environment has a major role in climate change as it is not only a significant contributor to this emergency, but also bears the brunt of climate change consequences. To mitigate future economic and human costs, it is crucial for the built environment to adapt to this new reality and reconsider the current ways of designing and planning buildings and cities. Even though in the Netherlands we are speaking of a housing crisis and the need for building many new homes in the coming decade, a focus on the refurbishment, adaptation, and reuse of existing building stock is locally and globally even more crucial.
We investigate the topic of climate resilience and adaptation in the built environment using a three-pronged viewpoint:
- The physical environment: The buildings and their materials and components, urban spaces and their materials and components, organizations, configurations, elements.
- Humans (and animals): The opinions, behaviors, movement patterns, appraisals of users of such spaces, and their interactions.
- Environment: The measurable environmental parameters in the physical environment, such as noise, light, air quality, air temperature, relative humidity, wind speed and direction, etc.
As a professor of information systems in the built environment, I focus on how technologies such as parametric modeling and design space exploration, advanced analytics, simulation, optimization, and artificial intelligence (AI) can be harnessed to help the stakeholders in the AEC industry. A synergistic integration of these technologies can drive innovation, efficiency, and quality, and support climate resilient advances in real estate. For instance, AI can enhance simulation models by providing real-time data analysis, while parametric modeling can optimize the design process based on simulation outcomes. These can be utilized for designing as well as supporting design and decision making.
In such data-driven, evidence based approaches, the integration of both building and urban scale data is necessary. Buildings and their data must be aggregated to inform decisions and policies on larger scales of neighborhoods and districts, and the effect of interactions that occur in urban spaces must be reflected back to processes in buildings. An investigation into complex issues requires the destruction of information silos, and benefits from an open data approach.
AI’s role in the retrofitting of buildings is pivotal. Parametric modeling tools, which have evolved from simple geometric configurations to complex, performance-optimized structures, are now used to optimize energy performance and structural resilience. Digital twins and Generative Adversarial Networks (GANs) further exemplify AI’s capacity to simulate climate scenarios and optimize building designs accordingly. These technologies allow for efficient exploration of design permutations, ensuring that retrofitting efforts maximize energy efficiency and climate resilience. They also offer valuable paths for enhancing inclusive and active citizen participation, which is a highly important topic of current investigation and development in liberal democracies.
Predictive machine learning models can be trained to tell us how to adapt buildings and neighborhoods to balance heating energy consumption and the increasing demand for indoor cooling, under several refurbishment scenarios. Transfer learning models can help us to implement such models in environments with different climatic conditions needing much less training data from these new environments.
University education is increasingly incorporating AI courses focused on generative design and decision support for climate adaptation. Although AI currently has limitations in creativity, its applications in enhancing building performance and resilience are significant. Educational programs are preparing future building industry professionals to leverage AI in design and decision support, ensuring they are equipped to address these issues effectively. This educational shift is crucial for developing a workforce capable of integrating computation driven solutions into practice.
The focus on promotion of certifications and adaptation measures that represent mere adjustments to existing urban and architectural design approaches fails to bring about fundamental shifts in the way design thinking is conducted. In some instances, this may lead to a superficial “greenwashing” attitude, rather than a radical and genuine commitment to sustainable and resilient design. This disconnect between the need for significant transformation of the built environment and the mainstream uptake of established knowledge and practices is a major stumbling block in the necessary transition to a climate resilient built environment. Such a transition will require more than policies, toolkits, and technological innovation. It requires the transformation of all actors responsible for the built environment. Therefore, we must scrutinize our educational program, and consciously develop valorization efforts, collaborating with other like-minded educational, public, and private institutes.
On the author: Bige Tuncer
| Prof. Dr. Bige Tunçer is a full professor and Chair of Information Systems in the Built Environment at the Department of Built Environment, Eindhoven University of Technology. She received her PhD in Architecture (design informatics) from Delft University of Technology (TU Delft), her MSc (computational design) from Carnegie Mellon University, and her BArch from Middle East Technical University. She was an an associate professor at Singapore University of Technology and Design (SUTD), assistant professor at TU Delft, junior faculty at ETH Zurich, a visiting professor at the Chair of Information Architecture at ETH Zurich, a visiting scholar at MIT, and a visiting professor at the Computer Engineering Department of University of Pavia, Italy. Her work focuses on data-driven and evidence-based methodologies for creating design and decision support tools and platforms from the building to the city scale that are used by designers, planners, policy makers, and other stakeholders within the built environment sector. She is currently building a research focus on climate adaptation and transformation with the help of advanced AI methods. |  |
