Abstract: Embodiments include a system and method for detecting and identifying wetness in a washroom or other facility using thermal sensing. A thermal sensor collects data on surface temperatures in an area such as a washroom. The data is analyzed to identify differences and/or deviations from baseline temperatures. Wetness can be identified based on the differences and/or deviations. The data can be further analyzed to identify the source and/or type of wetness. A cleaner or stakeholder can be contacted for cleaning and/or maintenance if wetness levels exceed a threshold level.

Abstract: Embodiments include a system and method for a virtual cleaning supervisor (VCS) for monitoring the cleanliness of a washroom, alerting cleaners and/or stakeholders and predicting cleaning schedules. Sensors are installed within a washroom at various locations that measure its cleanliness in real time. Sensors can measure patterns of use, wetness on floors, indoor air quality by detecting concentrations of gases and receive input from users. The sensor network does not rely on the use of a camera or other image based system. Artificial intelligence (AI) based machine learning algorithms on cloud servers can match the observed values with historical values to detect anomalies and send alerts if cleaning or a check is required. The system can also generate reports for facility managers to track cleaning operations and cleaning companies to evaluate their workforce using a time to service parameter.