The Role of AI in Indoor Environmental Quality Over the Next Decade

Indoor Environmental Quality (IEQ)—encompassing air quality, thermal comfort, lighting, and acoustics—is a critical determinant of health, productivity, and comfort. With humans spending over 90% of their time indoors (EPA, 2023), managing these variables in dynamic environments requires more than manual control. Over the next decade, artificial intelligence (AI) is expected to play a transformative role in designing and operating healthier, more adaptive indoor spaces.

AI's Role in a New Paradigm of Healthy Building Design

Traditional HVAC and building automation systems rely on fixed schedules and static control logic. AI, by contrast, enables data-driven adaptive control, allowing systems to respond in real time to occupant behavior, weather conditions, pollutant concentrations, and energy constraints.

This shift is particularly relevant in the context of post-pandemic expectations, where demand for enhanced air exchange, airborne pathogen mitigation, and personalization of comfort has accelerated.

Scientific Research and Technical Foundations

AI applications in IEQ are grounded in well-defined computational methods, including:

• Reinforcement Learning (RL): Enables systems to learn optimal HVAC setpoints by balancing thermal comfort with energy consumption.

• Neural Networks and Deep Learning: Used to predict indoor pollutant dynamics (e.g., CO₂, PM2.5) based on real-time sensor data.

• Bayesian Optimization and Model Predictive Control (MPC): Support anticipatory control actions by forecasting occupancy, external temperature, and indoor air quality.

Real-World Tools and Applications

Several commercial and research-grade platforms already implement AI for IEQ control:

• BrainBox AI: Integrates deep learning and cloud computing to optimize HVAC operations. Deployed in 100M+ sq ft globally, it reports up to 25% HVAC energy reduction and better CO₂ control in occupied zones.

• KGS Buildings (Clockworks Analytics): Uses diagnostic AI to detect faults in ventilation and air distribution systems that could impair indoor air quality.

• Siemens Desigo CC and Honeywell Forge: Combine AI with digital twins for real-time monitoring and predictive control in large commercial buildings.

• Cognitive Buildings: Research platforms integrating AI with occupant feedback loops (e.g., via smartphone apps) to enable “human-in-the-loop” environmental control.

AI can also support multi-objective optimization: for instance, maintaining PM2.5 <10 μg/m³, CO₂ <800 ppm, and thermal comfort within the ASHRAE-55 comfort zone, all while minimizing HVAC energy use.

Projected Impact on Human Health and Performance

Improved IEQ, enabled by AI, has measurable physiological and cognitive effects. Harvard’s COGfx studies found that reduced indoor CO₂ and VOCs significantly increase cognitive scores. AI systems enable these gains by ensuring stable indoor conditions that manual systems often fail to maintain.

Furthermore, exposure modeling suggests that AI-based systems can reduce total time spent in sub-optimal air conditions by 60–80%, especially in high-occupancy environments like classrooms and hospitals.

Future Outlook: Integration and Equity

By 2035, AI is expected to become integral to WELL, RESET, and LEED certification paths, particularly in post-occupancy performance verification. However, challenges remain in data privacy, algorithm transparency, and affordability for small-scale residential applications.

The future of AI in IEQ isn’t just about automation—it’s about creating personalized, data-responsive indoor ecosystems that actively promote human health.

References

1. U.S. Environmental Protection Agency (2023). Indoor Air Quality. https://www.epa.gov/indoor-air-quality-iaq

2. BrainBox AI. (2024). Case Studies and Global Deployment. https://www.brainboxai.com

3. ASHRAE. (2022). Standard 62.1 – Ventilation for Acceptable Indoor Air Quality.

4. Honeywell Forge. https://www.honeywell.com/us/en/solutions/honeywell-forge

5. Siemens Desigo CC. https://www.siemens.com/global/en/products/buildings/desigo-building-automation/building-management/desigo-cc.html

6. Harvard T.H. Chan School of Public Health – Healthy Buildings Program. https://forhealth.org