PPIEM provides the first generation of privacy-aware indoor environment sensors.
The poor air quality of our indoor environment can have significant short and long term health consequences. Organisations monitor indoor environments, using for instance sensors for CO2, temperature, and humidity. However, such measurement can cause privacy concerns. It is possible to infer occupancy within a space using environmental data. Although occupants might be willing to see their environment improve, they are less likely to use a space where their employers or friends can infer sensitive data about them, such as where they are and who they are interacting with. It is crucial to take into account and address these privacy concerns while monitoring indoor environment.
PPIEM is building sensors by establishing a baseline of occupancy detection in the Urban Sciences Building at Newcastle University, with environmental sensors in every office. The team then applies data anonymisation techniques and builds a machine learning predictor for operational building controls. These new techniques are then implemented in proof-of-concept privacy-aware indoor environment sensors.