The building sector is facing a digital revolution that is bringing new opportunities towards smart and sustainable buildings. New technical features, such as increased computational power, improvements in machine learning, and sensor availability in buildings, have enabled a paradigm shift in the role of building occupants. Occupants are no longer seen as mere recipients of the indoor climate but as active agents in the optimal operation of buildings to achieve better indoor climate and improved energy efficiency.

Digitalization enables a better understanding of occupancy and behavioral patterns and their impact on energy use, but many challenges are still unsolved. The DOCENT project will address them and develop occupant-centric control systems through an innovative hybrid research approach, using data-driven tools and digital twins. The project will demonstrate environmental, societal, and economic benefits on both standard and state-of-the-art smart building testbeds.

The aim of DOCENT is to improve the energy efficiency of buildings and the well-being of the building occupants by addressing critical features of building smartness. The project will achieve this with three main objectives:
• advance the knowledge of the complex interaction between building systems and building occupants with scalable and generalizable data-driven behavioral models
• integrate behavioral models into innovative adaptive control approaches tailored to the needs of the occupants; this minimizes the risk of energy-inefficient behaviors and interference with optimal operation and control
• develop incentives to increase the energy-awareness of building users.

Target groups for the scientific results are primarily control, energy technology, and social sciences communities. Economic outcomes will benefit building operators, technicians, and managers. Societal impacts of the project will assist building users, policymakers and building regulatory bodies.