Smart sensing supporting energy-efficient buildings: On comparing prototypes for people counting

The wide diffusion of smart objects and Internet of Things (IoT) is making available sensing applications that can support citizens' smart moving in outdoor contexts, as well as indoor ones. Detecting people presence and monitoring their flows could be strategic in public buildings, including shopping centers, administration offices, schools and universities. Having information about the actual occupancy of rooms in specific hours could provide useful insights for smart buildings management, that could be exploited in adequately setting the Heat, Ventilation and Air Conditioning (HVAC), the alarm, the lighting systems, and also other management issues (such as classrooms or labs assignment for different didactic activities, on the basis of the students frequency, in a smart campus). In this context, different approaches can be adopted, different technologies and sensors equipment can be installed, implying different requirements (in terms of budget), with different accuracy. In this paper, we present a preliminary experiment aiming to detect and count people in small indoor crowded environments (such as students in a classroom). The paper describes a prototype we have designed and developed, by exploiting two different low-budget cameras. The results of an evaluation assessment are reported, by comparing the two cameras outcomes and discussing the obtained accuracy