/5. Smart Building Orange

Design Brief

As part of the Orange smart Building competition: we were asked to develop innovative concepts with an emphasis on the implementation of existing Internet of objects technologies in a mixed-use building, on the one hand, while offering new solutions embodied in our own vision of the building of the future.

The architectural form is inspired by the movement of people to sculpt the outer form while providing panoramic visual fields.

The mixed-use building is separated according to these functions, a commercial ground floor; two floors serving as office space; two residential blocks, and finally a green terrace.

About

Year : 2018

Authors: EL Forsi Mhamed EL Yacoubi Abderrahmane

Location : Rabat, Morocco

Type : Competition

Softwares : Rhinoceros, Grasshopper, Archicad, Adobe Photoshop & illustrator

ASE Optimization

By analyzing the annual sun exposure, we can simulate the impact of solar radiation on a space, enabling us to predict the level of user comfort. The first image depicts the sun exposure on a bare facade, while the second image demonstrates the effect of a kinetic facade and a green terrace.

Office workspace layout

Final result

As part of the smart buildings competition, our goal was to establish a harmonious relationship between natural and artificial elements. Drawing inspiration from nature, we aimed to emulate the efficient functioning of trees in our building design. Specifically, we focused on replicating their ability to provide shade and harness solar energy through photosynthesis. By translating this concept into our architectural approach, we developed an innovative intelligent kinetic facade. This facade dynamically adjusts its shape based on the sun’s position and user comfort, shielding occupants from direct radiation. Moreover, we integrated advanced photovoltaic cells into the facade, enabling it to generate electricity from sunlight. This unique combination of design and technology creates a sustainable and user-friendly environment, exemplifying the potential of smart buildings.

Design Brief

Artificial Intelligence (AI) has emerged as a transformative force across various industries, and its potential impact on architecture is profound. Rapid advancements in AI present a range of opportunities to revolutionize the field. My work focuses specifically on the design exploration phase within architectural practice and highlights the application of generative AI. Generative AI has the remarkable ability to augment human creativity by expediting the generation of multiple design alternatives while seamlessly navigating through different architectural styles. To achieve this, I employed two sub-branches of generative AI: Large Language Models (LLMs) and diffusion models for image generation. By combining these AI models with existing tools, innovative use cases emerged. For instance, it became possible to transform a raw sketch into a realistic visual representation or parametrically convert a mass model into a rendered view. Moreover, by harnessing the power of LLMs, I explored the fascinating realm of AI-assisted conversation to collaboratively create buildings with parametric facades.

About

Year : 2023

Authors: EL Forsi Mhamed EL Yacoubi Abderrahmane

Location : Le Mans, France

Type : Academic

Softwares : Stable Diffusion, BingChat, Python,Rhinoceros, Grasshopper,Sketch

One of the primary objectives of my experiments is to create user-friendly interfaces that allow individuals to interact with AI in architectural practice, even without prior knowledge of the program’s backend. To achieve this, I developed two plugins—one focused on interior design and the other on massing studies and form exploration.

The first plugin is designed for interior design purposes. It generates layouts based on user-input dimensions and captures a screenshot of the interior. This screenshot is then processed using stable diffusion, guided by user prompts, to provide a realistic visualization of the space. The second plugin serves as an interface for parametrizing towers. Users can input various parameters to define the tower’s characteristics, and based on an architectural style prompt, the plugin generates visual outputs that align with the specified style.

In my exploration of interconnections between different AI models for architectural project generation, I chose to utilize the LLM, specifically BingChat, which is similar to ChatGPT but with access to the internet. I employed this model to generate a Python code for a parametric facade. The resulting facade screenshot was then processed through stable diffusion to produce a realistic render. Additionally, I utilized another AIbased plugin called PlanFinder, which takes the building dimensions as input and generates floor plans. Although the generated plans may not be perfect, often with multiple overlays, and synchronization challenges between the BingChat-generated facade and PlanFinder-generated plans, these obstacles are expected to be overcome in the future as AI progresses towards general AI capabilities.