Sidewalk Labs is an innovation company which focuses on the urban sector and to make cities more sustainable and an affordable living for all. The company creates new products, invests in companies, and plans innovative places around the world.
Architecture and Urban planning are getting more complex by the day. To cater to this complexity Delve is a new generative design tool that has been designed by Sidewalk Labs which empowers urban development using cloud computation and machine learning in order to design better cities in less time and risk. The tool uses machine learning to reveal optimal design options from a series of core components which includes buildings, open spaces, amenities, streets and energy infrastructure. Other data that is stored in the tool is the geographical area, physical or regulatory qualities of the place and existing development plans of the place if available. Since the tool is used for exploring design possibilities for a given project it also measures the impact of design choices.
Delve is a tool which can be used in the development phase of the project i.e., from the pre-feasibility phases to having a permitted master plan. Utilities and infrastructure are important features to an urban design and are thus integrated by the tool along with the financial aspect.
Before experimenting on the actual project an experiment was performed on a two by two block in an urban setup. The baseline of the study was the area’s existing planning framework. The study developed a plan with 45% open space, 49% daylight access and 1.5 million square feet of gross floor area. This baseline was done on the two by two block urban area. This baseline was done in order to look into future developments.
The tool provided simulations with marginal changes to the baseline plan. The first simulation was made by removing a few buildings and adding height to a few others. This combination created more open spaces and density and a large increase in daylight access. The second combination consisted of a simulation which altered built form in each block which led to the preservation of open space. This led to a small increase in open spaces and a medium increase in density. The third simulation made significant changes in the baseline plan by adding significant heights to some buildings and removing heights in some to free up space. This in turn led to increase in daylight access and a large increase in open space and density. This kind of simulation would lead to creation of more interactive neighbourhood spaces .
The design considerations that the architects included were regulatory concerns, street layouts, block orientations, real estate, weather and building height which cater to the quality of life. The design that was created was in order to create a little open space and reduce the density which can cause traffic. The tool was used to create multiple possibilities of the design and guide the architects on the same. It was generated in order to reduce the disconnect between the software and the user group.
Delve is a tool which helps in the design process. The tool helps in providing different iterations. Delve can be utilised in future as it provides possible solutions and be helpful for the community in the long run as the decision taken is the most informed decision and the iterations reflect the needs and priorities of the community they serve. The real time assessment and transparency is also provided with the help of the tool.
References:
- https://www.sidewalklabs.com/blog/a-first-step-toward-the-future-of-neighborhood-design/
- https://www.archdaily.com/949392/sidewalk-labs-reimagines-urban-planning-with-new-delve-generative-design-tool
- https://www.lifecycleinsights.com/resource-library/empowering-engineers-with-generative-design-and-facet-modeling/
- https://hello.delve.sidewalklabs.com/
- https://www.archpaper.com/2020/01/sidewalk-labs-using-machine-learning-neighborhood-design-smoother/
