Context-aware lighting for office lounge with simple algorithm

Abstract

This study proposes context-aware lighting presets for the office lounge based on user behaviour. We explored five kinds of optimised light scenarios: empty, relaxation, discussion, chatting and party, while matching them with patterns of user behaviours. Firstly, we designed lighting solutions for each context through expert interviews. Using these, we developed an algorithm that detects the number of users, their movement and their sound volume using a camera and microphone and suggests appropriate lighting settings based on this data. Then, we implemented the algorithm in two types of office lounges. Finally, user assessments and interview results confirmed that the adaptive lighting preset enriched users’ experience. We also discussed the challenges for better implementation.