A data-driven design framework for greater compatibility of large-scale housing projects with user diversity and resource scarcity: a case study in Peru

The objective of this study is the development and application of a data-based optimization framework that aims to increase large-scale affordable housing projects' design effectiveness in unpredictable scenarios with diverse users. It is based on an analysis methodology that incorporates data analytics in the design process seeking to define a concerted quality benchmark based on the identification of Key Quality Indicators (KQI's) to be considered in order to deliver more contextually compatible and resilient housing projects. Through the identification of technical and conceptual gaps within the current housing regulations in Peru, this study aims to address their impact on design innovations and adequacy to the needs and resources of the population, focusing especially on the Housing Consolidation Processes over time. In order to provide insights that contribute to complement and update the current Design Guidelines, a PRISMA Systematic Review has been performed, obtaining 92 KQI's of 77 Scientific Articles Reviewed, being classified in 10 Compatibility and Contemporaneity Categories. To be subsequently subjected to a Correlational Analysis with the Peruvian Housing Design Guidelines, obtaining revealing findings that were then translated into 10 General Design Premises that aim to visualize a new approach to Affordable Housing Development. To validate the applicability of the 10 General Design Premises in a real-life scenario, these premises were applied in the Design process of a prototype presented in the VIII National Housing Competition (Peru) in a Large-Scale Housing Project located in Talara, Piura under the required regulatory standards. For the purpose of incorporating inputs from the local reality in the theoretical framework developed, a mapping process of similar pre-existing projects in the context has been made under quantitative metrics of Consolidation, Materiality and Growth Rates over the self-build and habitability processes patterns. To be then subjected to a Correlational Analysis with the 10 General Design Premises, validating its compatibility and materialized in an Affordable Housing Prototype that is a precedent of the usage of the data-based design optimization frameworks for more effective future developments.