54317OptimisAir - Air quality control combined with behaviourial scienceClosedFeasibility StudiesInnovate UKOccupants' daily activities make up 35% of the factors leading to indoor air-pollution \[UCL,2018\]. In the face of COVID-19 we are expecting people to spend much more time in their homes which has two serious knock-on effects: 1) occupants experience longer exposure to indoor pollutants, increasing the risk of respiratory illnesses; 2) Poor IAQ is linked to COPD, asthma, stroke & heart diseases -- all of which are underlying health conditions, increasing the risk of severe illness from covid-19, putting further pressure on the NHS. To address this challenge we are now developing OptimisAir: an integrated 'Indoor air quality management system' that helps Registered Social Landlords reducing their maintenance costs through automated airflow control combined with AI-based activity-recognition and nudge-techniques to reduce the root cause of poor indoor air quality. It uses IoT-enabled sensors to monitor indoor pollutants and utilises game-changing technologies (machine-learning, activity-recognition, 'nudge'/behavioural sciences) to tackle an age-old problem: poor indoor air quality, dampness and draughts in homes. The outcome of the project creates a novel, patented system at an extremely competitive cost.