On the use of IoT Sensors for Indoor Conditions Assessment and Tuning of Occupancy Rates Models

In the last years, the energy savings policies are affecting several aspects of the everyday life, from the introduction of renewables and the use of Electric Vehicles, down to the adoption of more efficient lightening systems. Considering a typical building, one of the most energy consuming plant is the Heating, Ventilation and Air Conditioning (HVAC) system. This consideration is especially true for large public-access buildings, such as schools, universities and public administrations. In these cases, the energy saving of buildings depends on the capability to optimize the behavior of the HVAC. Typically, the HVAC control system is based on static models of the building, which consider an average occupancy rate of each of the rooms. On the contrary, in this research work, a Cognitive Building approach has been considered. The Energy Management System (EMS) is able to control and to regulate the HVAC system, considering an occupancy rate model able to take into consideration user' habits and the indoor air quality (IAQ), provided in near real-time by IoT sensors. This approach has been applied to the eLUX lab building of the campus of the University of Brescia, Italy. Data provided by IAQ sensors (temperature, relative humidity, CO2) are used to refine the results of occupancy rate models of rooms of this building. The experimental results show as in the 22.15 % of the samples, the CO2 concentration overcame the 1000 ppm threshold of perception of fresh air and good condition.