Dorokhova, MarinaBallif, ChristopheWyrsch, Nicolas2020-09-162020-09-162020-09-162020-08-3110.1016/j.egyai.2020.100022https://infoscience.epfl.ch/handle/20.500.14299/171697Heating, ventilation and air conditioning systems represent considerable potential for energy savings, which can be realized through intelligent occupancy-centered control strategies. In this work, both supervised and unsupervised algorithms to forecast occupancy are proposed with the highest accuracies of 98.3% and 97.6%, respectively. Building on their output, a rule-based air conditioning scheduling technique is developed. As an example, a potential of 15.4% of energy savings is calculated using a dataset collected in a mid-size (4000 m2) building in Portugal.AutomationEnergy savingsHVAC controlOccupancy forecastingThermal comforttext::journal::journal article::research article