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As we know, indoor air quality (IAQ) has a direct impact on our health and well-being. Exposure to elevated levels of pollutants can lead to negative effects that could be prevented with a more advanced approach. In this context, artificial intelligence (AI) emerges as a key tool to shift from monitoring to predictive solutions.
At inBiot, we are researching and developing AI-based technologies that not only analyze air quality data but also anticipate potential problems and propose measures before they arise. While our devices do not yet incorporate these advanced capabilities, we are actively working to integrate them in the future.
The shift from traditional methods to AI-based predictive models is one of the major challenges we are tackling. Until now, IAQ data analysis has largely relied on classical statistical models, which are useful but limited when dealing with the complexity of indoor environments.
By using Deep Learning algorithms, such as recurrent and convolutional neural networks, we have begun investigations that enable us to identify complex patterns between variables and predict future behaviors. For instance, we are exploring how to anticipate increases in CO₂ levels in enclosed spaces like classrooms, allowing ventilation to be implemented before harmful levels are reached. While promising, these capabilities are still in development and validation stages.
AI also opens opportunities to broaden the scope of IAQ-related solutions. We are conducting a pilot study using environmental data collected by our devices to estimate space occupancy levels without relying on invasive physical sensors like cameras or radars. This approach leverages patterns in environmental variables, such as CO₂, to provide an efficient and non-intrusive tool for occupancy management.
From devices that automatically optimize air quality to comprehensive management systems for smart buildings, AI has the potential to revolutionize how we manage indoor environments.
At inBiot, we are committed to this long-term vision. Thanks to the support of the Government of Navarra through the "Industrial Doctorates 2021" program, and the work of our colleague and PhD candidate Peio García Pinilla, we continue advancing our research to turn these ideas into practical solutions. This work positions us at the intersection of science, technology, and sustainability, aiming to lay the foundation for a healthier and smarter future.
