When considering the design of buildings and land use planning for urban development, traditional processes result in a number of constraints. First of all, data-driven design is challenging, since there are so many factors to consider, including economics, feasibility, social governance, land use and capital investment. Secondly, the planning output represents a fixed-state based on current problems, while development might take years. This makes it more vulnerable to shifts in the market or changes to the environmental and social context. Finally, it takes a lot of effort to make a plan, inhibiting our ability to quickly generate alternative scenarios or pivot our approach.
Urban and development planning is currently undergoing a massive upgrade, taking a data-centric approach to design that leverages the power of AI and analytics. In so doing, it introduces an agile approach to master-planning, creating a centralized digital twin to manage an urban ecosystem in operations.
Traditional processes for the design of buildings and land use planning for urban development render a number of constraints. A data-centric approach to design, based on the power of AI and data analytics, could enhance a massive upgrade of urban and development planning. Here’s why and how.
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