An innovative user feedback system for sustainable buildings

SUSTAINABLE BUILT ENVIRONMENT D-A-CH CONFERENCE 2019

生态环境科学

Monsberger, M.^1 ; Koppelhuber, D.^1 ; Sabol, V.^2 ; Gursch, H.^2 ; Spataru, A.^2 ; Prentner, O.^2

Graz University of Technology, Institute of Construction Management and Economics, Lessingstraße 27/I, Graz

8010, Austria^1

Know-Center - Research Center for Data-Driven Business and Big Data Analytics, Inffeldgasse 13/6, Graz

8010, Austria^2

关键词: Automatic adjustment;    Building operations;    Building services;    Facility management;    Feedback systems;    Non-ideal operating conditions;    Sustainable building;    User requirements;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/323/1/012123/pdf
DOI  :  10.1088/1755-1315/323/1/012123

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

A lot of research is currently focused on studying user behavior indirectly by analyzing sensor data. However, only little attention has been given to the systematic acquisition of immediate user feedback to study user behavior in buildings. In this paper, we present a novel user feedback system which allows building users to provide feedback on the perceived sense of personal comfort in a room. To this end, a dedicated easy-to-use mobile app has been developed; it is complemented by a supporting infrastructure, including a web page for an at-a-glance overview. The obtained user feedback is compared with sensor data to assess whether building services (e.g., heating, ventilation and air-conditioning systems) are operated in accordance with user requirements. This serves as a basis to develop algorithms capable of optimizing building operation by providing recommendations to facility management staff or by automatic adjustment of operating points of building services. In this paper, we present the basic concept of the novel feedback system for building users and first results from an initial test phase. The results show that building users utilize the developed app to provide both, positive and negative feedback on room conditions. They also show that it is possible to identify rooms with non-ideal operating conditions and that reasonable measures to improve building operation can be derived from the gathered information. The results highlight the potential of the proposed system.