Building Energy Efficiency Research Articles

Dynamic Indoor Environmental Quality Assessment in Residential Buildings: Real-Time Monitoring of Comfort Parameters Using LoRaWAN

This study addresses an identified literature gap regarding indoor environmental quality in residential buildings, where the primary focus has traditionally been on energy performance rather than comfort optimization. Leveraging the low-cost and easy-to-implement LoRaWAN protocol, this research collects and analyses real-time data on comfort parameters, including temperature, CO2 levels, humidity, lighting, atmospheric pressure, and total volatile organic compounds (TVOC) across various buildings within the INCUBE EU project. The results highlight the dynamic nature of the parameters and emphasize the importance of continuous monitoring to enhance comfort and energy efficiency in smart residential buildings. The findings advocate for integrating technologies like LoRaWAN to optimize indoor environmental quality, ultimately improving residential comfort and occupant well-being.

Historical Evolution and Current Developments in Building Thermal Insulation Materials—A Review

The European Climate Law mandates a 55% reduction in CO2 emissions by 2030, intending to achieve climate neutrality by 2050. To meet these targets, there is a strong focus on reducing energy consumption in buildings, particularly for heating and cooling, which are the primary drivers of energy use and greenhouse gas emissions. As a result, the demand for energy-efficient and sustainable buildings is increasing, and thermal insulation plays a crucial role in minimizing energy consumption for both winter heating and summer cooling. This review explores the historical development of thermal insulation materials, beginning with natural options such as straw, wool, and clay, progressing to materials like cork, asbestos, and mineral wool, and culminating in synthetic insulators such as fiberglass and polystyrene. The review also examines innovative materials like polyurethane foam, vacuum insulation panels, and cement foams enhanced with phase change materials. Additionally, it highlights the renewed interest in environmentally friendly materials like cellulose, hemp, and sheep wool. The current challenges in developing sustainable, high-performance building solutions are discussed, including the implementation of the 6R principles for insulating materials. Finally, the review not only traces the historical evolution of insulation materials but also provides various classifications and summarizes emerging aspects in the field.

Electrically Controlled Smart Window for Seasonally Adaptive Thermal Management in Buildings.

Smart windows offer a sustainable solution for energy-efficient buildings by adapting to various weather conditions. However, the challenge lies in achieving precise control over specific sunlight bands to effectively respond to complex weather changes and individual needs. Herein, a novel electrochromic smart window fabricated by integrating a self-assembled cellulose nanocrystals (CNCs) layer with an electrochromic poly(3,4-ethylenedioxythiophene):poly(styrene sulfonic acid) (PEDOT:PSS) layer is reported, which exhibits high near-infrared transmittance, low solar reflectivity (26%), and infrared emissivity (20%) in winter, and low near-infrared transmittance, high solar reflectivity (91%), and infrared emissivity (≈94%) in summer. Interestingly, the material offers dynamic temperature control based on its photothermal properties, maintaining the internal temperature of buildings within a comfortable range of 20-25 °C from morning to night, particularly in winter with significant daily temperature fluctuations. Simulations show that the CNC-PED device demonstrates excellent energy-saving and CO2 emission reduction capacities across various global climate zones. This study presents a feasible pathway for constructing season-adaptive smart windows, making them suitable for energy-efficient buildings.

Experimental analysis of glass failure criteria under different thermal conditions

The initiation of the first crack mainly determines the criteria for glass failure. However, the extended consequences of cracking, with the formation of multiple cracks merging, result in fallout conditions under varying thermal loads that become more critical. Point-supported glass arrangements are globally used in high-rise and energy-efficient buildings for architectural ingenuity aimed at a low budget. However, the formation of cracks due to thermal load resulting in glass breakage could infuriate the overall fire dynamics of the enclosed area. Therefore, experimental study and prediction of glass failure become very crucial. The present experimental study focuses on finding the most critical parameter that may quantify the cause of glass failure and further breakage in fallout conditions under varying thermal loads. 45 experiments were carried out on float glass of 300 × 300 mm2 with 4 mm, 6 mm, 8 mm, 10 mm, and 12 mm with continuous fuel supply arrangements. Critical parameters analysed were the time of crack initiation, glass temperature at the time of cracking, maximum temperature difference at glass failure, and thermal strain caused by the temperature difference on the glass surface. The range of minimum and maximum temperature difference recorded on the glass surface for the present study was between 30–35°C and 55–60°C at the breakage time for all the experiments. The Maximum temperature difference measured was 56.99°C on the 12 mm glass surface, and the corresponding maximum thermal strain found was 482 × 10−6 mm/mm. The maximum heat release rate was found to be approximately 200 kW. Maximum heat flux was found in the range of 10.33 kW/m2 to 21.14 kW/m2. A correlation was also developed using the least square method for all the thicknesses, which is well correlated with the glass thickness per unit length.

Implementation of thermoelectric wall systems for sustainable indoor environment regulation in buildings through numerical and experimental performance analysis

With buildings representing a substantial portion of global energy consumption, exploring alternatives to traditional fossil fuel-based heating and cooling systems is critical. Thermoelectricity offers a promising solution by converting temperature differentials into electrical voltage or vice versa, enabling efficient indoor thermal regulation. This paper presents a comprehensive investigation into the integration of thermoelectric wall systems for sustainable building climate control through numerical simulations and experimental analyses. Numerical simulations using computational fluid dynamics (CFD) techniques were conducted to model fluid flow and heat transfer within the thermoelectric wall systems under various operating conditions. These simulations provided insights into the system’s thermal behavior, which were validated through experimental setups designed to measure temperature differentials, airflow rates, and power consumption. The results showed that power consumption is directly correlated with electrical current, ranging from 0.19 W to 77.4 W as the current increased from 0.1 A to 2 A. Additionally, the heat absorbed by the system increased significantly with electrical current, by 706–1044%, depending on the air velocity. The thermal energy released from the hot side of the thermoelectric modules also rose substantially, ranging from 9850 to 5285% with increasing electrical current, and from 275 to 51% with higher air velocities. Moreover, increasing air velocity led to a 6.78–9.37% reduction in power consumption for currents between 0.1 A and 2 A. The coefficient of performance (COP) analysis revealed that optimizing both electrical current and air velocity is essential for maximizing system efficiency. While fan power consumption reduces COP at higher air velocities, neglecting fan power consumption results in COP improvements ranging from 6.5 × 10⁻⁴ to 49.0%. These findings highlight the potential of thermoelectric wall systems to enhance indoor comfort and energy efficiency in buildings.

Energy-Saving Potential of Building-Integrated Photovoltaic Technology Applied to a Library in Changsha, China

With the increasing number of public buildings worldwide, their energy consumption has garnered significant attention. This study aims to promote building energy efficiency and emission reduction by exploring the application of Building-Integrated Photovoltaic technology in library retrofitting. Using a library in Changsha City as a case study, we conducted an energy consumption analysis of the building’s envelope and identified the window section as the highest energy consumer. We proposed a novel improvement scheme—the sun-shading photovoltaic panel (which shades the sun while generating electricity). Additionally, we utilized the roof space for the installation of conventional photovoltaic panels. Simultaneously, the primary objective of this paper was to derive a renovation strategy for public buildings in regions characterized by high summer temperatures and low winter temperatures based on the renovation case of this library. This paper comprehensively investigates the length and angle of sun-shading photovoltaic panels facing different directions, as well as the azimuth angle, tilt angle, and installation spacing of the conventional photovoltaic panels on the roof. Two retrofitting schemes were proposed. Through simulation and comparison, the second scheme was found to reduce the annual electricity consumption by 1,233,354 kWh, achieving a 35.4% decrease compared to the original building. Using the Changsha library as a template for public buildings, this study provided a retrofitting approach with Building-Integrated Photovoltaic technology via DesignBuilder, which could be extended to other geographic locations. The results demonstrated the significant energy-saving effects of the proposed retrofitting scheme.

Occupancy and equipment usage prototype schedules for building energy simulations of office building types in China

The accuracy of occupancy and energy-consuming equipment schedules significantly influences building energy simulations. Existing standards provide generalized schedules that do not fully capture variations across different office building types and periods. This study utilizes questionnaire data from office buildings across four Chinese cities to extract refined prototypes for occupancy and equipment usage schedules using hierarchical clustering analysis. Specific schedules are developed for summer workdays, winter workdays, summer weekends, and winter weekends, covering HVAC, lighting, and office equipment. For instance, the extracted lighting schedule increases annual energy consumption intensity by 25.35% compared to standard schedules. Additionally, XGBoost models identify key factors influencing equipment usage; for HVAC, floor number emerges as most significant. The study's prototypes offer more realistic inputs for building energy simulations, enhancing accuracy and guiding energy-efficient building design and management strategies in China.

Multi-objective decision optimization design for building energy-saving retrofitting design based on improved grasshopper optimization algorithm

With the national emphasis on building energy efficiency planning, energy efficiency optimization in existing buildings requires renovation measures based on multi-objective factors. In order to get the optimal solution in the multi-objective decision-making of renovation, the study proposes a class of improved grasshopper optimization algorithms. The process employs a systematic methodology to identify an optimal energy renovation method, taking into account the specific characteristics of the building environment. It then classifies and formulates the energy reduction substitution items for building renovation, and finally, it synchronizes the cost of the renovation project as a measure for decision-making. The elite inverse strategy approach enhances the grasshopper optimization algorithm to facilitate the multi-objective decision-making process associated with building renovation measures. The results showed that the improved grasshopper optimization algorithm could achieve a decision accuracy of 98.8% for the test samples, which was 5.5% higher than the accuracy of the particle swarm optimization algorithm. Repeated run tests of the research algorithm for multi-objective decision making yielded a mean decision fitness value of 2.34×104 and a data extreme value of 0.38×104. Compared to other algorithms improved grasshopper optimization algorithm converged in a lower range of fitness values, which indicated that the algorithm worked well for multi-objective optimization and the model repeatability was good. The research algorithm was used to decide the energy efficient renovation planning of the building and the power consumption of the renovated power supply system was reduced by 23.7%-49.6%. This indicates that the renovated building has better energy efficiency and can provide a reliable technical direction for decision-making optimization of building energy efficiency renovation.

Development of novel multifunctional phase change microcapsules for improving thermal comfort and radiation properties

Microencapsulated phase change materials (MPCMs) have gained widespread application in energy-efficient buildings, aiming to improve thermal comfort and reduce energy consumption. To enhance the engineering feasibility of MPCMs, researchers are now focusing on developing MPCMs with multifunctional properties, beyond single thermal storage functionality. In this study, we proposed a novel and straightforward approach to fabricate multifunctional MPCMs with BaCO3 as shell and a core composed of binary phase change materials (PCMs) and lipophilic-modified graphite (MG) via self-assembly method. The incorporation of BaCO3 shell provides MPCMs with additional resistance to ionizing radiation pollution due to the high atomic number element Ba. Additionally, the incorporation of MG into PCMs enhances its temperature sensitivity. The thermal analysis indicates that the binary PCMs’ composition in MPCMs results in two phase transition temperatures at 3.3 °C and 26.4 °C, making them capable of thermal storage in line with comfortable residential temperatures across different seasons. Furthermore, MPCMs were introduced into cement paste (CPM) and used to construct cement chambers. Adding 10 wt% MPCMs in the CPM chambers placed outdoors in Wuhan (from June 7th to June 9th) led to a 23.8 % decrease in temperature fluctuations compared to the reference sample. Radiation shielding results indicated that the linear attenuation coefficient (μ) of CPM increased by 58.7 %, due to enhanced incoherent scattering and photoelectric effects between high atomic number elements and photons. Additionally, XCOM simulations predicted a strong correlation between MPCM content and μ values, with particularly high accuracy at low photon energies. Overall, the multifunctional MPCMs developed in this study not only offers a new route for reducing residential energy consumption and shielding ionizing pollution, but also broadens the applicability of traditional PCMs in the building and other fields.

Investigating envelope retrofitting potential and resilience of Australian residential buildings − A stock modelling approach

Residential buildings consume around 24 percent of overall electricity use in Australia. Though the energy efficiency of new buildings is progressively increasing, there are around 10 million existing homes most with poor thermal and energy performance. Improving these existing homes are imperative for Australia to reach its target of net zero by 2050. This paper adopts a stock modelling approach using real designs of more than two hundred thousand detached dwellings and apartments submitted for certification in eight states and territories across Australia to investigate envelope retrofitting potential of the housing stock. The performance of the existing housing stock was assessed and the effect of various levels of envelope improvements on energy efficiency and overheating were analysed for current and future climatic conditions. With improvements in 10% of the entire building stock, 3.14 Mt, 3.52 Mt and 7.2 Mt CO2 emission reductions per year respectively were estimated with Rehab, Refurb and Renov improvements. Both detached dwellings and apartments experienced overheating across all the states and territories for the current and future climatic conditions. Though envelope improvement caused some reduction in the overheating, it was not significant. The high average overheating hours in Queensland come from nighttime overheating in the bedrooms, whereas in most other states daytime overheating constitute the majority. Various improvements in the building envelope were effective in reducing daytime overheating reductions rather than nighttime overheating, though the impact was marginal. The results from this study provided guidance on policy and regulatory mechanisms that can be introduced for developing decarbonization pathways for buildings at a national level.

Urban heat islands’ effects on the thermo-energy performance of buildings according to their socio-economic factors

Urban areas experience the urban heat island (UHI) effect, which affects the thermal comfort and energy consumption of buildings. These consequences could vary depending on the socio-economic status of the neighbourhoods. Few studies have investigated how UHI affects socio-economically contrasting districts in thermal comfort and energy performance. Therefore, the primary goal of this research is to evaluate and compare the energy efficiency and thermal comfort conditions of residential buildings in the same city (Temuco, Chile) but located in socio-economically contrasting neighbourhoods. Urban weather files were first modelled in four urban zones using UWG software. Also, EnergyPlus building simulations were conducted to evaluate discomfort hours in adaptive comfort models and energy performance. The results showed annual average UHI intensities between 1.5 and 2.5 K. Urban–rural cooling energy load differences ranged between 12.47% and 38.92%, while heating energy load differences ranged between -20.47% and -81.95%. These distinctions depended on the urban zone, residence model analysed, or energy building standard applied. Similarly, urban-rural differences in thermal comfort times varied from 0.5% to 100%. Results illustrate that the risk of overheating could increase in socio-economically vulnerable areas. This issue could worsen if urban segregation continues to generate poor urban design in low-income districts.

China's newest design of apartment buildings with modernized façade: a comparative evaluation of its energy performance in five major climate zones

Many studies have indicated that the energy efficiency of residential buildings can greatly mitigate energy shortages and environmental problems. High window-to-wall ratio, flat geometric shape, and open space layout are the key characteristics of apartment buildings with modernized façade (ABMF), and the major design trend dominating China's housing market. This study aims to understand the isolated effects of these three design factors on the energy performance of ABMF in five major climate zones using a parametric performance design method. Three important findings were concluded: 1) the energy use intensity (EUI) of ABMF showed a positive relationship to the window-to-wall ratio in five climate zones. Qingdao in Cold Region (2.12 kWh/m2) and Kunming in Temperate Region (1.04 kWh/m2) exhibited lowest average increase in EUI; 2) the reduction of EUI was twice as much in Kunming than in the other four cities, when the aspect ratio of ABMF changed from 1.75 to 0.95; 3) the ‘exterior-side hall’ was the most energy-efficient layout in the five cities. This study is the first to investigate the energy performance of the newest apartment design and hopefully can attract more studies to explore the suitability of ABMF for the sustainable development of China's housing market.

Barriers to the Effective Selection of Sustainable Materials for Residential Building Projects: A Qualitative Study

Although sustainability in Tanzania’s construction sector has been explored in areas such as energy efficiency and green building practices, little attention has been given to understanding the specific barriers to the selection of SBMs in residential projects. This study fills that gap by identifying and analyzing the critical barriers hindering the effective selection of SBMs in Tanzania’s residential construction sector. Through qualitative interviews with experts from regulatory bodies, public developers, and academic researchers, this research provides a comprehensive examination of these barriers. Using Atlas.ti 23 software for a qualitative data analysis, six key categories of barriers were identified: (1) Regulatory and Policy Barriers, (2) Financial Barriers, (3) Knowledge and Awareness Barriers, (4) Technical Barriers, (5) Market and Supply Chain Issues, and (6) Cultural and Social Barriers. Among these, lack of awareness and limited knowledge emerged as particularly significant, alongside regulatory and policy barriers, in hindering the effective selection of SBMs. This study’s novelty lies in its focus on the Tanzanian context, depth of the analysis of the unique challenges, and categorization of the barriers. The findings underscore the need for targeted policy interventions, particularly in raising awareness, offering financial incentives, and establishing comprehensive regulatory frameworks. Furthermore, this study presents a graphical representation to illustrate the categories and constructs of these barriers, adding a visual dimension to the understanding of the issues. Future research should expand the scope to include private developers and material suppliers, whose roles are critical in enhancing the availability and adoption of SBMs in Tanzania’s construction industry.

Physics-informed ensemble learning with residual modeling for enhanced building energy prediction

Accurate modeling of building energy use is important to support a diverse spectrum of its downstream applications, such as building energy efficiency assessment, resilience analysis, smart control, etc. As mainstream approaches of building energy modeling, physics-based modeling builds on different fidelities of physics rules yet are usually compromised in modeling accuracy due to insufficiency of physics rules to capture real-world dynamics and incomplete input information. Data-driven approaches are computationally efficient, but black box (uninterpretable) in nature. For improved modeling of building energy use, this work proposes a physics-informed ensemble learning approach in building energy prediction through residual modeling. Specifically, we first analyze the components of building energy use data. Evidence suggests that the building energy use data can be decomposed into the physics-driven part, occupant-driven part, and white noise. Second, high-fidelity physics-based building models (EnergyPlus) and low-fidelity ones (RC models) are developed to capture the physics-driven part while time series methods are explored as the residual modeling approach to capture the occupant-driven discrepancies between physics-based simulation and measured building energy use (i.e., residuals). Finally, the physics-informed ensemble learning is proposed to integrate physics-based and data-driven models for enhanced accuracy of building energy modeling. Results demonstrate 40–90% decrease of discrepancies between modeling and field observations compared to traditional physics-based modeling methods. Moreover, when the training dataset size is small, the proposed ensemble model overperforms the pure data-driven models, demonstrating its higher robustness in extrapolation scenarios. This work makes fundamental contributions to the development of convergent modeling approaches in the building modeling field.

Assessment of heating degree-days factor (HDDF) for building-oriented climate zoning in Türkiye

ABSTRACT In this study, a novel heating degree-days factor (HDDF) is proposed to determine the optimum facade design for buildings in Türkiye as a function of both cooling degree-days (CDD) and heating degree-days (HDD) data. For this purpose, the HDDF (HDD/(HDD+CDD)) is defined as the ratio of the heating degree-days of a region to the total heating and cooling degree-days. Firstly, the HDDF values of all provinces in Türkiye are calculated by using meteorological data from 81 meteorological stations covering the period 1991–2022, and HDDF performance is evaluated. Then, the building-oriented climate zoning is realized based on the HDDF values. Moreover, historical trends of monthly and yearly average HDD, CDD, and HDDF values are revealed and yearly HDD, CDD, and HDDF maps were created using the ArcGIS program. According to the results, HDDF values in Türkiye varied between 0.4519 and 0.9998, and HDDF values between 0.9 ≤ HDDF ≤ 1 cover 46 out of 81 cities in the country and span a broad area across the country. The findings suggest that if global warming continues at the current rate, cooling energy demand in the residential sector will dramatically increase in the future, while heating energy demand will fall in Türkiye. This indicates that domestic energy consumption regulations would require modification. The building-oriented climate zoning resulting from this study is unique to Türkiye and can aid engineers, architects, and policymakers in building energy efficiency programs, studies, regulations, and standards.

Validation of 3D thermal simulations of the Double C Block, a novel composite masonry unit, using in-situ U-value measurements

Energy efficient building envelopes, particularly innovative prefabricated building components, can significantly contribute to lower the building industry energy-related emissions. In this research the composite masonry unit Double C Block (DCB) is quantitatively tested by means of three-dimensional thermal simulation validated by in-situ U-value measurements carried out in both summer and winter conditions.The simulations were enhanced by the experimental measurement of the dry thermo-physical material properties (specific heat capacity, thermal conductivity, and density) in laboratory conditions for both concrete and polyurethane. The samples were extracted from real-scale DCB prototypes. Furthermore, site-specific boundary conditions of Malta — representative a case study of a Mediterranean climate − were utilised in the simulations. Both laboratory and in-situ assessments of thermal transmittance, or U-value, had their uncertainty specified as part of the calculations.The validation exercise was performed by means of hourly recorded surface temperature and the selected indices were the root mean square error and mean absolute error. Results showed that these indices were within the recommended accuracy thresholds during both winter and summer assessments. For the hourly-based heat flux measurements, the mean bias error and coefficient of variation of the root mean square error were found lower than values reported in literature, thus supporting the robustness of the overall simulation outputs. Hence the 3D CVM simulation was experimentally validated by in-situ assessments.The convergence value of the experimental U-value provided respectively 1.51 ± 0.20 W/m2K (winter) and 1.44 ± 0.19 W/m2K (summer). Then, the validated 3D CVM model was adapted to calculate the theoretical U-value of DCB, using monthly values of recorded surface temperatures obtained by the test cells (in both seasons). The predicted thermal transmittance was of 1.47 W/m2K, in both conditions, and this almost matches the above-mentioned experimental assessments and thresholds established in previous works.

Development and validation of the motivation for electricity saving behaviour scale (MESBS) among residents living in energy-efficient buildings in Sweden

Even though energy-efficient technologies are well developed, the behaviour of building occupants plays an important role in the search for the optimum level of energy efficiency. In academic literature, however, very few studies have used psychological theories to understand individuals’ drivers of energy use behaviour when interacting with energy-efficient technologies. Specifically, there are no studies solely focused on individuals' motivations for electricity saving behaviour. This paper is based on an empirical study carried out in energy-efficient residential buildings to develop and test a new scale by applying self-determination theory (SDT). A postal survey about the Motivation for Electricity Saving Behaviour Scale (MESBS), including self-reported electricity use, was sent out to 1,084 residents living in newly built energy-efficient multifamily dwellings and eco-villages in Southern Sweden. The answers obtained from 235 participants were analysed for the reliability and validity of MESBS. The findings indicated that i) MESBS items have good internal consistency and are in line with expectations based on SDT, and ii) the autonomous motivation component of MESBS is strongly associated with electricity saving behaviour (i.e. turning off lights when not needed) in energy-efficient buildings. Our results emphasise the importance of considering individuals’ motivations for undertaking electricity saving behaviour in energy-efficient buildings. The study also provides useful information for future studies of energy-efficient buildings as well as designing new technologies and interventions to reach the optimum level of energy-efficiency.

BIM-based energy consumption analysis for residential buildings: effects of orientation, size, and type of windows

Buildings have a significant environmental impact due to their reliance on nonrenewable energy sources. To address this concern, computer software is utilized to estimate building energy requirements. Building Information Modeling (BIM) has emerged as a valuable tool in this process, with BIM 6D offering a particularly beneficial feature. BIM 6D provides a comprehensive energy model of the building, simulating its actual energy performance. By analyzing natural and artificial lighting systems, particularly daylighting, BIM 6D can assist in optimizing energy efficiency. Despite being underutilized, the potential of this feature to enhance building sustainability is noteworthy. BIM 6D facilitates well-informed design and operational decisions for both new constructions and the renovation of existing buildings. The study examines design criteria such as building orientation, window orientation, size, and type to optimize energy consumption in a bungalow in the Sangli region of Maharashtra, underscoring the importance of energy-efficient buildings to local communities. Energy analysis and optimization are conducted using the Autodesk Insight tool. The methodology involves creating 3D models with Autodesk Revit Architecture software and performing various analyses, including Building Energy Modeling (BEM) simulations, Illuminance Analysis, Solar Access, and Daylight Autonomy assessments. The analysis findings indicate that low-e glass windows of small size and oriented between 0° and 90° significantly enhance energy efficiency under certain conditions, while changing the window type does not affect the analysis. The paper concludes with recommendations for window orientation and size to enhance energy performance in residential buildings, contributing to the broader goal of sustainable and energy-efficient construction practices. This study provides valuable insights for designing energy-efficient residential buildings in rural areas, addressing awareness gaps, and promoting sustainable construction practices.

IoT—A Promising Solution to Energy Management in Smart Buildings: A Systematic Review, Applications, Barriers, and Future Scope

The use of Internet of Things (IoT) technology is crucial for improving energy efficiency in smart buildings, which could minimize global energy consumption and greenhouse gas emissions. IoT applications use numerous sensors to integrate diverse building systems, facilitating intelligent operations, real-time monitoring, and data-informed decision-making. This critical analysis of the features and adoption frameworks of IoT in smart buildings carefully investigates various applications that enhance energy management, operational efficiency, and occupant comfort. Research indicates that IoT technology may decrease energy consumption by as much as 30% and operating expenses by 20%. This paper provides a comprehensive review of significant obstacles to the use of IoT in smart buildings, including substantial initial expenditures (averaging 15% of project budgets), data security issues, and the complexity of system integration. Recommendations are offered to tackle these difficulties, emphasizing the need for established processes and improved coordination across stakeholders. The insights provided seek to influence future research initiatives and direct the academic community in construction engineering and management about the appropriate use of IoT technology in smart buildings. This study is a significant resource for academics and practitioners aiming to enhance the development and implementation of IoT solutions in the construction sector.

Public Policies for the Energy Efficiency of Buildings in Mexico

In Latin America, the energy crisis has worsened due to the dependence on energy services and fossil fuel imports from highly industrialized countries at prices established by the international market; this is particularly relevant to the construction industry, which presents a significant deficit in optimal energy consumption. Hence, some governments have established public policies to maximize the efficiency of these services and, at the same time, minimize the carbon footprint. In this research study, we reviewed the public policies, strategies, and incentives for energy efficiency (EE) implementation in the residential sector established by the Mexican government. A scoping review methodology was chosen and implemented in the following steps: 1. Research inquiry identification. 2. Determination of the relevant literature and studies. 3. The literature selection. 4. Data graphing. 5. Results collection, overview, and submission. In this systematic review, we identified five mandatory standards (NOM-008-ENER-2001, NOM-009-ENER-2014, NOM-018-ENER-2011, NOM-020-ENER-2011, and NOM-024-ENER-2012), six optional standards, four strategies (Green Mortgage, Integral Sustainable Improvement in Existing Housing, ECOCASA, and NAMA), and three kinds of incentives (green bonds, credit and interest rates (Green Mortgage, FIDE, and Ecocasa), and taxes (Income Tax Reduction)). As a result of the implementation of the above, as of December 2020, NAMA financed 5106 developers of 38 projects in 15 states; contributed to a reduction of 126,779 tons of CO2; and aided 19,913 people. From 2013 to December 2023, EcoCasa subsidized 71,440 households for a total of 224 projects in 25 states; contributed to a reduction of 2.6 million tons of CO2; aided 285,760 Mexicans; and issued EcoCasa certificates for 3,473,556 m2. The results of the EE indicators in residential buildings showed an increase in the housing unit number as well as an increase in household appliances, with those based on power consumption prevailing. The residential sector ranks third in power consumption in Mexico, consuming an estimated 790 pj, of which 76% corresponds to thermal energy and 24% to electric power. Among countries in Latin America and the Caribbean, Mexico has achieved an Energy Transition Index of 62%.