Towards Intelligent Facility Management: Autonomous Robotic Sensing for Enhanced Indoor Environmental Quality

Optimizing indoor air quality (IAQ) requires continuous monitoring of environmental factors to meet or exceed established standards. Automated sensing has emerged as a transformative solution, leveraging advanced robotic capabilities to overcome the limitations of static sensor networks. This study presents an innovative framework for intelligent IAQ monitoring, utilizing autonomous robotic sensing. A TurtleBot 4 equipped with a Greywolf IAQ sensor was developed and tested, enabling seamless navigation of indoor spaces while collecting spatial and temporal data, including location coordinates, timestamps, and temperature, humidity, and CO2 readings. Data collected in real time are transmitted to a processing unit for analysis and visualized as dynamic real-time heatmaps, providing an evolving snapshot of indoor conditions. The framework was tested in a small residential building to validate its capability to effectively monitor and analyze IAQ conditions. By integrating these components, the study demonstrates the potential of autonomous robotic systems to revolutionize facility management practices.