Linked data-based Digital Twins for increasing the Indoor Environmental Quality (IEQ) of individuals working from home

This research aims to explore the possibility of using linked data-based Digital Twins for the Indoor Environmental Quality (IEQ). This is achieved through a proof-of-concept (PoC) case set in a working from home (WFH) environment. The IEQ is made measurable by using the IEQ parameters: temperature, humidity, light intensity, sound pressure level, and indoor air quality (IAQ) level. The emphasis of this PoC is placed on the individual’s comfort as objective, with the integration of personal preference. Since the IEQ of a WFH environment is currently designed to facilitate leisure tasks, this now pressures the at-home environment to conform to both the needs of leisure and work tasks. This use was never the aim of the at-home environment and thus poses challenges aligned with the required shift of working from office (WFO) to WFH. A hybrid linked data and relational database approach have been used to facilitate the Digital Twin. Attached to this Digital Twin an application has been made in order to communicate with the occupants. This application provides the occupants with IEQ information or request prompts and receives direct input about their current discomfort, current tasks, and daily parameters. Combining measurement and direct input, which are then linked to a task activity level. The result is a response to help the occupants better their IEQ. To test this approach a case study has been done, spanning five days and covering two rooms. These are a hybrid leisure and work environment (living room), and a dedicated work environment (a bedroom converted into an at-home office). These results have thereafter been analyzed providing insights about IEQ in a WFH environment and the applicability of linked data-based Digital Twins, resulting in a proof-of-concept.