IoT Gas Sensors Array for Unobtrusive Tracking of Cooking Activity

Recent research on remote tracking environments has strengthened smart home IoT ecosystems by the integration of multiple sensing tools that capture not only contextual data in a private setting, but also information about its residents. This shift paves the way for remote health industries, as information traditionally out of reach is available 24/7. Gas sensing, moving away from privacy-invasive tracking paradigms, emerges within this context, inspiring the monitoring of activities of daily living (ADLs) that could facilitate the remote healthcare supervision of the elderly. In this paper, we present how a gas sensing array based on low-cost commercial metal oxide (MOX) gas sensors has been assembled for the development of Principal Component Analysis (PCA) model which detects cooking activity within a household. Our resulting unobtrusive tracking system requiring no user input and posing no privacy concerns, suitable to other ADL use cases, highlights how AI-equipped IoT cloud infrastructures and accurate gas sensors are called to revolutionise remote healthcare.