The urban environment requires areas for people to socialise which includes certain communal areas and most importantly having areas where people relish solitude. This paper explores the delicate balance between privacy and social interaction in public spaces through the lens of proxemics. This paper aims to explore the concepts of private spaces/privacy in the public realm in order to analyse the way in which people relate to their environments. The research makes use of proxemic zones—intimate, personal, social, and public in order to create environments that balance the need for privacy whilst promoting social interaction. The qualitative data for this research was extracted by administering questionnaires to respondents to gain an understanding of varied proxemic preferences along with an ethnographic study. Based on the acquired results a Weighted Comfort score (WCS) quantitative model formulae is developed. The study employs a dual method approach: Firstly utilizing sensor driven systems to monitor real time environmental data like crowd density, noise levels and personal boundaries; secondly, the paper proposes the creation of a mobile application that works in synergy with sensor driven technology to provide users with real time space recommendations respecting their proxemic preferences.

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Spatial Algorithms for Urban Comfort: Balancing Proxemic Zones in Public Spaces

  • Valli Ramanathan,
  • Tarun Kumar

摘要

The urban environment requires areas for people to socialise which includes certain communal areas and most importantly having areas where people relish solitude. This paper explores the delicate balance between privacy and social interaction in public spaces through the lens of proxemics. This paper aims to explore the concepts of private spaces/privacy in the public realm in order to analyse the way in which people relate to their environments. The research makes use of proxemic zones—intimate, personal, social, and public in order to create environments that balance the need for privacy whilst promoting social interaction. The qualitative data for this research was extracted by administering questionnaires to respondents to gain an understanding of varied proxemic preferences along with an ethnographic study. Based on the acquired results a Weighted Comfort score (WCS) quantitative model formulae is developed. The study employs a dual method approach: Firstly utilizing sensor driven systems to monitor real time environmental data like crowd density, noise levels and personal boundaries; secondly, the paper proposes the creation of a mobile application that works in synergy with sensor driven technology to provide users with real time space recommendations respecting their proxemic preferences.