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Abstract Energy efficiency in buildings is a key issue in the current energy transition. In order to reduce building energy consumption, users' behaviour and the perception of indoor environmental comfort must be taken into account; these aspects are inextricably linked to energy demand, consumption and related costs. In this paper, we present the methodological framework, technological solutions and outcomes of the ComfortSense project. ComfortSense aimed at decoupling energy demand from indoor comfort. We focused on Heating, Ventilating and Air Conditioning (HVAC) systems in buildings, on users' behaviour and on comfort perception by treating buildings as socio-technical systems. Our approach - which was multidisciplinary and included the contribution of sociologists, physicists and computer scientists - was based on Internet of Things technologies, on a Living Lab design and testing process and on a Crowdsensing approach. Physical parameters (objective variables), such as temperature, CO 2 concentration and relative humidity, were measured by a Wireless Sensor Network and by wearable devices, while the users' perception of comfort (subjective variables) were recorded as real-time feedback through a Mobile App in three pilot buildings of the University of Turin, engaging about a thousand buildings' users (professors, researchers, students and employees). Objective and subjective variables were correlated through an ad-hoc Direct Virtual Sensor. Thanks to the Direct Virtual Sensor forecasting we demonstrated that, adopting an adaptive indoor comfort management, users' comfort can be remarkably improved while reducing the energy consumption of HVAC systems. [ABSTRACT FROM AUTHOR]