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IIoT and AI continue to evolve, but they often remain theoretical or just marketing concepts. At sAInce.io, we take pride in going beyond ideas. We have developed an AIoT solution (Artificial Intelligence of Things) that makes a real impact in hospitals. A concrete example of industrial AI in action, delivering tangible results that benefit both individuals and organizations.
Energy savings: Less energy required for ventilation, heating, cooling, humidification, and dehumidification in operating rooms, resulting in lower gas and electricity consumption.
Improved air quality: Optimal conditions for both surgeon and patient, leading to increased safety, greater comfort, and improved quality.
Fewer postoperative wound infections (POWI’s): Thanks to a controlled, stable, and guaranteed airflow, the risk of postoperative infections is drastically reduced.
Improved maintenance planning: Smarter maintenance strategies based on filter saturation and the economic breakpoint.
Great benefit for the environment: A significant reduction in CO2 emissions through more efficient energy use and less waste.
Traditionally, a large, heavily oversized air handling unit is installed on the roof. This unit is regulated by dampers until validation shows that the air velocity under the plenum meets the standard (0.25 – 0.30 m/s according to the Advice of the High Health Council no. 8573). This is checked statically once or twice a year.
This is very energy inefficient. The dampers cause significant losses, and the air must be continuously heated or cooled, and humidified or dehumidified. Moreover, the air velocity remains a fixed setting, while in practice it is known that this velocity can fluctuate greatly due to various factors.
The day and night regime is often a problem as well. These are set statically, or worse, people forget to manually adjust the regime during a night-time emergency.
This is the current situation in our country and, by extension, throughout Western Europe. An approach that is outdated and urgently in need of renewal.
The problem was tackled scientifically as well as in terms of hardware and software. Work was done on three pillars:
Above the ceiling of the operating room we have placed large, frequency-controlled fans. These ensure efficient air recirculation: 20% fresh air and 80% recirculated air from the operating room itself.
This ensures an energetically optimal solution in which even the Pareto rule is visible.
The core of this innovation is our Smart IIoT Controller. It serves not only as the brain (AI models and PID control) but also as the muscle of the system. It combines intelligent decision-making with powerful control to ensure maximum efficiency and safety.
Measurements in the operating room: Beneath the plenum, an air velocity sensor measures the speed with an accuracy of up to 0.01 m/s. In addition, various sensors monitor essential parameters such as the differential pressure across the inlet and outlet filters, CO2 levels, temperature, and relative humidity.
AI-driven image analysis: In the operating room, we installed an IP camera with dual imaging functionality: both optical and thermal. The Smart IIoT Controller analyzes these images to determine how many people are present under the plenum. This is crucial, as the more people under the plenum, the higher the risk of infections. The fans increase the airflow velocity to minimize the risk of postoperative wound infections (POWIs).
Stable and rapid control: The fans respond within 10 seconds to fluctuations in the air velocity from the air handling unit, ensuring an extremely stable airflow. Even in the event of a complete failure of the air handling unit (no fresh air), the fans maintain 100% of the airflow velocity.
Smart day-and-night responses: Outside of operating hours, the system reduces the ventilation rate and maintains only a slight overpressure across the filters. When switching to the daytime regime, the system increases the fan speed to quickly achieve the required air exchange rate. Once the nominal regime is reached, the system reverts to its normal settings.
Automatic response in emergencies: If someone stands briefly under the plenum at night or during the weekend, the system detects this as a potential emergency. It immediately increases the airflow speed to meet the required air exchange rate as quickly as possible. This eliminates the risk of forgetting to activate the system manually.
Predicting filter replacement: The system continuously monitors the differential pressure across the filters and can accurately predict when they need to be replaced. At a certain point, it becomes economically viable to replace the filters to avoid excessive electricity consumption required to push air through them. By precisely forecasting this point, maintenance can be planned preventively, saving both costs and energy.
Data storage in the cloud: All measurements are stored in our cloud system, allowing us to gain deeper insights afterward. This enables us to analyze trends, optimize performance, and continuously innovate based on real data.
Digital sensors for efficient calibration: All sensors used in the system are fully digital, eliminating the need for in-loop calibration. These calibrations can be performed entirely off-site under laboratory conditions. By simply replacing sensors with pre-calibrated units, there is no downtime required for calibration. This process can be carried out at any time, such as in the evening, and the replacement is both quick and straightforward. This ensures increased operational availability for operating room staff over the course of a year, without compromising the quality or accuracy of the system.
The number of people does not need to be the only factor considered. In our latest test setup, we are already combining data on particle counts and CO2 levels to make even more precise decisions about airflow. This opens up new possibilities for further optimizing air quality and energy efficiency.