What are the key determinants and effects of occupants' behaviour on energy use for space heating? Statistical analyses were carried out on energy use and self-reported behaviour data from a household survey in the Netherlands. Results showed that the number of usage hours for the heating system have a stronger effect on energy consumption than temperature setting. Small correlations were found between energy use and the ventilation system, since most households barely use the ventilation system. The main building characteristic determining behaviour is the type of temperature control. Households with a programmable thermostat were more likely to keep the radiators turned on for more hours than households with a manual thermostat or manual valves on radiators. In relation to household characteristics, the presence of elderly persons in the household proved to be a determining factor in the use of the heating system and ventilation. As a result of wide variations in preferences and lifestyle, occupant behaviour has emerged as an important contributor to energy use in dwellings. The results indicate that the type of heating and ventilation system has an influence on occupant behaviour. Quels sont les principaux déterminants et effets du comportement des habitants en matière d'utilisation d'énergie pour le chauffage des locaux ? Des analyses statistiques ont été réalisées sur l'utilisation de l'énergie et sur les données comportementales autodéclarées issues d'une enquête menée aux Pays-Bas auprès des ménages. Les résultats ont montré que le nombre d'heures d'utilisation du système de chauffage a un effet plus important sur la consommation énergétique que le réglage de la température. Il n'a été trouvé que peu de corrélations entre l'utilisation d'énergie et le système d'aération, dans la mesure où la plupart des ménages utilisent très peu le système d'aération. La principale caractéristique des bâtiments qui détermine le comportement est le type de réglage de la température. Les ménages équipés d'un thermostat programmable étaient plus susceptibles de maintenir les radiateurs allumés pendant davantage d'heures que les ménages équipés d'un thermostat manuel ou de robinets manuels sur les radiateurs. S'agissant des caractéristiques des ménages, il a été démontré que la présence de personnes âgées dans le ménage est un facteur déterminant dans l'utilisation du système de chauffage et du système d'aération. Du fait des grandes variations existant dans les préférences et les modes de vie, le comportement des occupants est apparu comme étant un facteur important dans l'utilisation de l'énergie dans les habitations. Les résultats indiquent que le type de système de chauffage et d'aération a une influence sur le comportement des occupants. Mots clés: comportement, confort, demande énergétique, ménage, logement, comportement des habitants, parc de logements résidentiels, chauffage des locaux

This research explores current strategies and approaches directed to integrate innovative technologies in the home modification process to support independent living and ageing in place. The systematic review considered studies conducted from the perspective of architecture, smart technology, and gerontology. Scientific databases of related disciplines (e.g. Scopus, Web of Science, Engineer village, Google Scholar, Crossref) were searched and supplemented by hand search method. Thirty-three out of 2594 articles were analysed from three perspectives: the framework of the smart home environment for ageing in place, the smart home modification process, and problems and countermeasures of independent living. The result shows that both home modification and smart technologies can support older adults’ independent living, especially with fall prevention and indoor accessibility. Technologies deployed in older adults’ homes are transiting from manual assistive technology to more intelligent devices, and the notion of the robotic home has emerged. According to existing practices, universal design is an extensively adopted strategy for smart home design and modification. However, in most cases, universal design is used as a retrofitting guideline for general home settings rather than specifically for smart homes. The fundamental requirements in smart home modification phases are customisation, minimum life interference, and extensible technologies to cope with the ageing process.

Building simulations are often used to predict energy demand and to determine the financial feasibility of the low-carbon projects. However, recent research has documented large differences between actual and predicted energy consumption. In retrofit projects, this difference creates uncertainty about the payback periods and, as a consequence, owners are reluctant to invest in energy-efficient technologies. The differences between the actual and the expected energy consumption are caused by inexact input data on the thermal properties of the building envelope and by the use of standard occupancy data. Integrating occupancy patterns of diversity and variability in behaviour into building simulation can potentially foresee and account for the impact of behaviour in building performance. The presented research develops and applies occupancy heating profiles for building simulation tools in order create more accurate predictions of energy demand and energy performance. Statistical analyses were used to define the relationship between seven most common household types and occupancy patterns in the Netherlands. The developed household profiles aim at providing energy modellers with reliable, detailed and ready-to-use occupancy data for building simulation. This household-specific occupancy information can be used in projects that are highly sensitive to the uncertainty related to return of investments.

The indoor environment quality in care facilities impacts residents’ daily lives. Sensor technology has been proven useful in evaluating the indoor environment of buildings, but the process of using this information to improve residents’ comfort, specifically in the context of nursing homes, is still underdeveloped. Thus, this study focuses on monitoring indoor environmental quality in a nursing home in the Netherlands, supported by professional caregivers’ insights. A campaign was conducted for one year to monitor eight rooms, and a mixed-method approach was used to collect and analyse the data on local weather, building facility operation and proxies’ responses to residents’ comfort. Seventeen care professionals and twenty-two guardians (visitors) answered questions based on their opinions and observation. The results show that the low indoor humidity during heating seasons and high CO₂ concentration at night were the main factors leading to environment-related symptoms of residents and care professionals, such as dry eyes. Furthermore, we found that data outliers can help to reveal residents’ occupancy, ventilation habits and activity time, thus showing the application value of environmental sensors in dementia care. We also recommend using non-intrusive sensors for nursing home residents and taking into account room layouts and occupants’ conditions before installing sensors.