Data-Driven Methodology for Coliving Spaces and Space Profiling Based on Post-Occupancy Evaluation through Digital Trail of Users

Sustainable spaces are those that are optimized, accessible, promote user experience and aim to reduce CO<sub>2</sub> emissions while enhancing users’ well-being and comfort. The purpose of this paper is to present a methodology that was developed during the COVID-19 pandemic to understa...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Alicia Regodon, Maxime Armand, Carmen Lastres, Jose De Pedro, Alfonso García-Santos
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
Acceso en línea:https://doaj.org/article/710a4128ef1641f59d694bf588f82885
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:Sustainable spaces are those that are optimized, accessible, promote user experience and aim to reduce CO<sub>2</sub> emissions while enhancing users’ well-being and comfort. The purpose of this paper is to present a methodology that was developed during the COVID-19 pandemic to understand and improve the use of coliving spaces based on remote Post-Occupancy Evaluation (POE) analysis of the digital trail generated by the users. Applying the POE methodology based on data collection from IT infrastructure enabled to identify opportunities to improve the future design of human-centered spaces. The residential market, design-wise traditional for centuries, is now facing a high-speed adaptation to the changing needs, accelerated by the COVID-19 crisis. New ways of living and shared spaces like Coliving are escalating. Technology is both an enabler of this shift in housing and the solution to operating and managing these new buildings. This paper demonstrates, through the case study of a Coliving space located in Madrid, Spain, the benefits of implementing data analysis of the digital trail collected from in-built IT systems such as smart locks, Wi-Fi networks and electric consumption devices. The conclusion is that analysing the available data from the digital infrastructure of coliving buildings can enable practitioners to improve the future design of residential spaces.