OCCUPANCY ESTIMATION USING NON INTRUSIVE SENSORS IN ENERGY EFFICIENT BUILDINGS

Abhay Arora , Manar Amayri (1) , Venkataramana Badarla , Stéphane Ploix (1) , Sanghamitra Bandyopadhyay (2)

1 G-SCOP_GCSP - Gestion et Conduite des Systèmes de Production
2 STICERD

A general approach is proposed to estimate the number of occupants in a zone using different kinds of mea- surements such as motion detection, power consump- tion or CO2 concentration. The proposed approach is inspired from machine learning. It starts by deter- mining among different measurements those that are the most useful by calculating the information gains. Then, an estimation algorithm is proposed. It relies on a C4.5 learning algorithm that yields human read- able decision trees using measurements to estimate the number of occupants. It has been applied to an office setting.

Mots clés: office buildings; building performance; machine leaning and data mining; human behavior

Domaines: Intelligence artificielle [cs.AI]

Abhay Arora, Manar Amayri, Venkataramana Badarla, Stéphane Ploix, Sanghamitra Bandyopadhyay. OCCUPANCY ESTIMATION USING NON INTRUSIVE SENSORS IN ENERGY EFFICIENT BUILDINGS. 14th Conference of International Building Performance Simulation Association, Hyderabad, India, Dec. 7-9, 2015., Dec 2015, Hyderabad, India. ⟨hal-01864941⟩