In human-centered intelligent building, real-time measurements of human thermal comfort play critical roles and supply feedback control signals for building heating, ventilation, and air conditioning (HVAC) systems. Due to the challenges of intra- and inter-individual differences and skin subtleness variations, there has not been any satisfactory solution for thermal comfort measurements until now. In this paper, a contactless measuring method based on a skin sensitivity index and deep learning (NISDL) was proposed to measure real-time skin temperature. A new evaluating index, named the skin sensitivity index (SSI), was defined to overcome individual differences and skin subtleness variations. To illustrate the effectiveness of SSI proposed, a two multi-layers deep learning framework (NISDL method I and II) was designed and the DenseNet201 was used for extracting features from skin images. The partly personal saturation temperature (NIPST) algorithm was use for algorithm comparisons. Another deep learning algorithm without SSI (DL) was also generated for algorithm comparisons. Finally, a total of 1.44 million image data was used for algorithm validation. The results show that 55.62% and 52.25% error values (NISDL method I, II) are scattered at (0 °C, 0.25 °C), and the same error intervals distribution of NIPST is 35.39%. 

Single-family houses offer a large potential for energy savings by energy renovation (ER). Homeowners’ motivation to implement ER derives from the benefits and barriers they perceive. Benefits are the positive consequences that can motivate homeowners to act and barriers are the challenges that demotivate them to undertake ER. Different benefits and barriers do not homogenously affect every homeowner. Identifying motivating benefits and demotivating barriers for each specific group among homeowners can shed lights on ER decision-making and enable policies that are more effective. The objective of this study is to contextualize the implementation of ER by understanding how the perceived benefits and barriers influence homeowners. This study links the expected consequences, which are benefits and barriers to the influential factors on ER, which are used to group the homeowners.

The analysis is based on a questionnaire survey mailed to 1550 owners of single-family houses in northern Sweden. The perceptions of homeowners on benefits and barriers of ER are significantly different between the groups that are motivated and unmotivated to implement ER. Despite the perceived importance of some of the benefits such as energy cost reduction, they may not be determinative for the homeowners’ decision to undertake ER. The homeowners are more likely to implement ER for reasons other than energy use reduction such as for improving the indoor environment. The barriers such as the difficulty of finding a low-interest loan and reliable information sources are found to impede the intention to implement ER among different groups. Policy implications to facilitate ER in single-family houses are discussed.

The aim of this study is to assess how different renovation scenarios affect the environmental and economic impacts of a multi-dwelling building in a Nordic climate, how these aspects are correlated and how different energy carriers affect different environmental impact categories. In order to reduce greenhouse gas emissions, the European Union has set an agenda in order to reduce energy use in buildings. New buildings on the European market have a low replacement rate, which makes building renovation an important factor for achieving the European Union goals. In this study, eight renovation strategies were analyzed following the European Committee for Standardization standards for life cycle assessment and life cycle costs of buildings. This study covers all life cycle steps from cradle to grave. The renovation scenarios include combinations of photovoltaics, geothermal heat pumps, heat recovery ventilation and improved building envelopes. Results show that, depending on the energy carrier, reductions in global warming potential can be achieved at the expense of an increased nuclear waste disposal. It also shows that for the investigated renovation strategies in Sweden there is no correlation between the economic and the environmental performance of the building. Changing energy carriers in Sweden in order to reduce greenhouse gas emissions can be a good alternative, but it makes the system more dependent on nuclear power.

The successful implementation of energy efficiency measures in the residential sector will depend to a large extent on the attitudes and perceptions of the end-users since they are the final decision maker. The tenure of the housing could influence the building occupants' perspectives on energy issues. In this study we conducted a comparative evaluation of perspectives on energy use of three categories of households: those living in single family houses, tenants and owners' of apartment. The analysis is based on responses to a mail-in questionnaire by approximately 650 residents in Umeå, Sweden. Majority of the respondents believed that their annual household energy use is less. Residents in single-family houses, as compared to the other two types of tenure of the housing, were more likely to believe their heat energy use as high and likely to take actions to reduce the energy use. Financial incentives such as subsidy or lower interest rate were preferred by most of single-family homeowners (45%) to motivate them to take actions to reduce energy use. While personalized information to reduce energy use and lower interest rate and reduced rent are preferred by more residents in the other two categories. The implications for promoting energy efficient measures based on housing tenure is discussed.

Heating, ventilation and air-conditioning (HVAC) are by farthe most energy intensive systems in commercial and institutionalbuildings with office spaces. This makes HVAC systemsattractive targets for energy efficiency improvement. New technologicaladvancements can play significant role on improvingenergy efficiency. Such advancements have been also emergedin form of novel management and control strategies, whichmight lead to considerable energy savings with relatively minorinvestments. This paper evaluates demand control HVAC andlighting to assess the energy saving potential of upgrading theconventional building energy systems.

This paper provides a summary of different methods and occupancydetection technologies. A range of technologies andmethods are covered that vary in complexity, limitations andenergy saving potential. Additional benefits such as demandresponse are evaluated and other emerging applications arediscussed. Based on the review of methods and potentials, thepaper assesses the state of the art in demand controlled energysystems and suggests areas for further research.

Energy efficiency investments in existing buildings are an effective way of reducing the environmental impact of the building stock. Even though policies in the European Union and elsewhere promote a unilateral focus on operational energy reduction, scientific studies highlight the importance of applying a life cycle perspective to energy refurbishment. However, life cycle assessment is often perceived as being complicated and the results difficult to interpret by the construction sector. There is also a lack of guidelines regarding the sustainable ratio between the embodied and accumulated operational impact. The scope of this study is to introduce a life cycle assessment method for building refurbishment that utilizes familiar economic performance tools, namely return on investment and annual yield. The aim is to use the introduced method to analyze a case building with a sustainability profile. The building was refurbished in order to reduce its operational energy use. The introduced method is compatible with a theory of minimum sustainable environmental performance that may be developed through backcasting from defined energy and GHG emissions objectives. The proposed approach will hopefully allow development of sustainable refurbishment objectives that can support the choice of refurbishment investments.

The scope of this study is to assess how different energy efficient renovation strategies affect the environmental impacts of a multi-family house in a Nordic climate within district heating systems. The European Union has set ambitious targets to reduce energy use and greenhouse gas emissions by the year 2030. There is special attention on reducing the life cycle emissions in the buildings sector. However, the focus has often been on new buildings, although existing buildings represent great potential within the building stock in Europe. In this study, four different renovation scenarios were analyzed with the commercially available life cycle assessment software that follows the European Committee for Standardization (CEN) standard. This study covers all life cycle steps from the cradle to the grave for a residential building in Borlänge, Sweden, where renewable energy dominates. The four scenarios included reduced indoor temperature, improved thermal properties of building material components and heat recovery for the ventilation system. One finding is that changing installations gives an environmental impact comparable to renovations that include both ventilation and building facilities. In addition, the life cycle steps that have the greatest environmental impact in all scenarios are the operational energy use and the building and installation processes. Renovation measures had a major impact on energy use due to the cold climate and low solar irradiation in the heating season. An interesting aspect, however, is that the building materials and the construction processes gave a significant amount of environmental impact.

Monitoring a ground source heat pump can provide important insights into its working, but to study the behaviour of the borehole heat exchanger (BHE) we require monitored data for the whole period of operation. In practice, the monitored data often has periods of missing data. We propose a method to estimate the load during the periods of missing data based on the fluid temperature after that period. The method determined the missing load with negligible error, for the case of a BHE that behaves exactly like the model describing it. A sensitivity analysis showed that the estimated load is highly sensitive to errors in measured load and fluid temperature. The method was applied to a real monitored BHE, the magnitude of estimated loads were unreasonably high, but the overall deviation between the measured and simulated values of fluid temperature decreased. Therefore, the high magnitude of missing load compensates for the lack of agreement between the model and the measured data.

Monitoring a ground source heat pump can provide important insights into its working, but to study the behaviour of the borehole heat exchanger (BHE) we require monitored data for the whole period of operation. In practice, the monitored data often has periods of missing data. We propose a method to estimate the load during the periods of missing data based on the fluid temperature after that period. The method determined the missing load with negligible error, for the case of a BHE that behaves exactly like the model describing it. A sensitivity analysis showed that the estimated load is highly sensitive to errors in measured load and fluid temperature. The method was applied to a real monitored BHE, the magnitude of estimated loads were unreasonably high, but the overall deviation between the measured and simulated values of fluid temperature decreased. Therefore, the high magnitude of missing load compensates for the lack of agreement between the model and the measured data.

Human thermal comfort measurement plays a critical role in giving feedback signals for building energy efficiency. A contactless measuring method based on subtleness magnification and deep learning (NIDL) was designed to achieve a comfortable, energy efficient built environment. The method relies on skin feature data, e.g., subtle motion and texture variation, and a 315-layer deep neural network for constructing the relationship between skin features and skin temperature. A physiological experiment was conducted for collecting feature data (1.44 million) and algorithm validation. The contactless measurement algorithm based on a partly-personalized saturation temperature model (NIPST) was used for algorithm performance comparisons. The results show that the mean error and median error of the NIDL are 0.476 °C and 0.343°C which is equivalent to accuracy improvements of 39.07 % and 38.76 %, respectively.