An RL-Based Approach for IEQ Optimization in Reorganizing Interior Spaces for Home-Working

Indoor Environmental Quality (IEQ) is a very important aspect in the design of spaces. It depends on fundamental requirements, and it aims to improve living quality ensure high well-being for occupants. Poor IEQ has significant health consequences as people spend considerable portion their time indoors. The restrictions imposed by current SARS-CoV-2 pandemic have worsened this situation requiring more at home adopt home-working primary work model. Such requires individuals reconfigure interior spaces adapting new emerging needs. This paper proposes an approach based reinforcement learning support rearrangement indoor maximizing environmental index terms thermal, acoustic visual comfort furniture layout scheme.