A real-time occupancy detection system for unoccupied, normally and abnormally occupied situation discrimination via sensor array and cloud platform in indoor environment

Dynamic ventilation certificate for smart universities using artificial intelligence techniques

“…Regardless of its basic benefits and based on prior studies [ 19 , 20 , 34 ], the number of occupants of given enclosed premises can also be predicted via CO 2 readings, along with other related variables, such as the room's volume or the age of the people present.…”

“…Various studies [19] , [20] , [21] have focused on finding suitable methods to obtain CO 2- based occupancy control, in order to estimate the number of occupants present in a room. Most of them take into account the amount of CO 2 generated by a person.…”

An AI-Based Ventilation KPI Using Embedded IoT Devices

“…It is important to note, however, that human breathing CO2 emissions are linked to that of other human metabolism. A range of works [6] have searched for adequate methods to obtain a CO2-based occupancy control, in order to estimate the number of people present in a room. Most of them consider a person's individually-generated CO2 level.…”

“…In addition, the CO2 concentration value helps to estimate the number of people sharing the room (#Personco2) following previous studies that controlled presence based on CO2 concentration [6]. To determine the number of occupants, we also proposed to use the room's dimensions, broken down into surface area by height, type of degree, season in the year, type of subject and the academic year of the students present.…”

“…Regardless of their basic advantages, taking into account the previous studies [6,8], the number of occupants of a given space (#Personco2) can also be predicted based on CO2 readings, along with other related variables (g()), such as the volume of the premises or the age of the attendees (eq. 3).…”