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Lighting preference profiles of users in an open office environment

机译:开放办公室环境中用户的照明偏好配置文件

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Offices are transforming into multi-user, open space environments to stimulate interaction between people and optimize the usage of space. Due to design practices, lighting systems in these multi-user environments are implemented as a regular grid of luminaires that often does not match the furniture layout. Consequently, purely personal control over general lighting is not achievable in most cases. As a result, a single luminaire affects several neighbouring desks, creating shared lighting controls and conditions. Therefore, providing satisfying lighting conditions to everyone becomes a challenge. This paper proposes a first method for modelling lighting preference profiles of users based on their control behaviour and preference information. Based on objective measurements and subjective data obtained in two field studies, users can be profiled based on their control behaviour, regarding characteristics as activeness, dominance, lighting tolerance, and diniming level preference. The results show significant differences between lighting preference profiles of users. This paper also proposes a first method for discovering and triggering submissive users to express their preferences in order to derive their profiles as accurate as possible. This will help to secure users' comfort by offering satisfying lighting conditions to their preference. By knowing the lighting preference profiles of users, the probability of conflict between users can be predicted and minimized. (C) 2017 The Authors. Published by Elsevier Ltd.
机译:办公室正在转变为多用户的开放空间环境,以刺激人与人之间的互动并优化空间的使用。由于设计实践,这些多用户环境中的照明系统被实现为通常与家具布局不匹配的常规照明设备网格。因此,在大多数情况下,无法实现对一般照明的纯粹个人控制。结果,一个照明器会影响多个相邻的桌子,从而创建共享的照明控件和条件。因此,向所有人提供令人满意的照明条件成为挑战。本文提出了一种基于用户的控制行为和偏好信息来建模用户的照明偏好配置文件的第一种方法。基于在两次现场研究中获得的客观测量结果和主观数据,可以根据用户的控制行为(包括活动性,优势,照明容忍度和餐位偏好)对用户进行配置。结果表明,用户的照明偏好配置文件之间存在显着差异。本文还提出了一种发现和触发顺从用户表达自己偏好的第一种方法,以便尽可能准确地得出其个人资料。通过为用户提供令人满意的照明条件,这将有助于确保用户的舒适度。通过了解用户的照明偏好配置文件,可以预测用户之间发生冲突的可能性并将其最小化。 (C)2017作者。由Elsevier Ltd.发布

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