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The aim of this work is to develop a model of heat supply to buildings with almost zero energy consumption, indicating the significant importance of heat losses and gains in heating installations. The prepared model is to indicate the need for changes in the structure and topology of heating installations, resulting from the changing heat demand of buildings. The need to create a new model is heightened by changes that relate to tightening legal regulations related to energy consumption and demand, which must meet the standards of buildings in Poland from 2021. The article presents the assumptions and results of analyses of the use of energy installations in residential buildings that use renewable energy sources to balance energy consumption in various areas of its use. To achieve this goal, calculations were made using simulations of the impact of the use of installations using renewable energy sources on the energy performance of a building with different quality of partitions and improvement of energy efficiency in accordance with the Polish standard PN-EN 12831. The test results allow to choose the most advantageous, from the point of view of economic profitability, option of replacing installations in residential buildings, and they also allow to determine the possibilities of meeting national obligations in the field of final energy reduction and increasing the share of renewable energy sources in meeting its demand in accordance with the EU obligations imposed on Poland. Thermomodernization of buildings in the temperate climate zone allows for a reduction of 38% of energy demand over the entire life cycle of a building and a reduction of CO2 emissions by 99%.

This paper presents a novel rail-to-rail Class-AB operational amplifier tailored for wake-up systems in motion sensor applications. By addressing limitations in free Class-AB designs, such as large inrush current, unstable bias conditions, and area ineffiiency, the proposed design achieves a gain of 59 dB and unity gain frequency of 550 kHz driving a 5 pF load. The inrush current is reduced from 1 mA to 7 µA, increasing the battery life. The layout area is reduced by 53% compared to the free Class-AB design, making it highly suitable for compact implementations. Operating at a low power consumption of 2 µW with a 1.8 V supply, the amplifier achieves a Signal-to-Noise-and-Distortion Ratio (SNDR) of 22 dB. These advancements demonstrate the potential of the design for energy-efficient analog front-end solutions in IoT and portable systems.

Three-dimensional printing, or additive manufacturing, is one of the modern techniques emerging in the construction industry. Three-Dimensional Printed Concrete (3DPC) technology is currently evolving with high demand amongst researchers, and the integration of modular building systems with this technology would provide a sustainable solution to modern construction challenges. This work investigates and develops energy-efficient 3D-printable walls that can be implemented worldwide through energy efficiency and sustainability criteria. Numerical research and experimental investigations, bench tests with software packages, and high-precision modern equipment have been used to investigate the thermal performance of 3DPC envelopes with different types of configurations, arrangements of materials, and types of insulation. The research findings showed that an innovative energy-efficient ventilated 3DPC envelope with a low thermal conductivity coefficient was developed following the climatic zone. The annual costs of heat energy consumed for heating and carbon footprint were determined in the software package Revit Insight to assess the energy efficiency of the 3D-printed building. The thermal properties of the main wall body of the tested 3D-printed walls were calculated with on-site monitoring data. The infrared thermography technique detected heterogeneous and non-uniform temperature distributions on the exterior wall surface of the 3DPC tested envelopes.

This research is motivated by the increase in energy consumption in the Indonesian household sector, especially on the island of Java, which contributes significantly to greenhouse gas emissions. Although the government has implemented an energy-saving label policy, the adoption of energy-saving appliances still needs to be higher. The main problems identified include low consumer awareness of the long-term benefits, high perception of initial costs, and lack of effective information dissemination. This study aims to analyze the factors that affect consumer intentions in switching to energy- efficient appliances using the Push-Pull-Mooring (PPM) theory. Environmental consciousness functions as a push factor, social media, energy-saving labels, Curiosity as a pull factor, and technology compatibility as a mooring factor. A quantitative survey was conducted on 310 households in Java, and the data was analyzed using PLS-SEM. The results show that environmental consciousness and Curiosity influence consumers’ intention to switch, while technology compatibility strengthens adoption decisions. In addition, social media and energy labels directly increase consumer curiosity about energy-efficient appliances. The implications of this study include strategic recommendations for governments and marketers to increase awareness campaigns and financial incentives and leverage social media to accelerate the adoption of sustainable technologies in the household sector.

In the present study, the real-world performance of a ground-to-air heat exchanger (GAHE) was analyzed in the Polish climate which is characterized by warm summers and cold winters. The heat exchanger’s performance was monitored over a period of three years (2017 to 2019), and real-world conditions were compared with a Typical Meteorological Year (TMY). The aim of the study was to assess the exchanger’s energy-efficiency potential in various ventilation scenarios in a single-family home under variable real-world conditions, rather than to simply determine its heating and cooling capacity. The analyzed single-family home was a modern, single-story building with a usable floor area of 115 m2. The building’s thermal insulation and airtightness met stringent energy-efficiency standards. Energy consumption in a building equipped with a natural ventilation system was compared with three other scenarios: ventilation coupled with a GAHE, mechanical ventilation with heat recovery and a high-efficiency heat exchanger (HE), and mechanical ventilation with heat recovery coupled with a GAHE. Sensible heating and cooling loads were calculated based on standard ISO 13790:2008, and latent heating and cooling loads were also included in the energy balance. During the year, the GAHE generated around 257.6 W of heating energy per hour and 124.7 W of cooling energy per hour. Presented results can be used to select the optimal HVAC system scenarios for engineering projects as well as private investors.

Sustainable development is a global policy that requires the collective effort of the actors present in each territory. In this sense, an energy renewal intervention model is presented at the Juan XXIII Educational Institution in the city of Monteria, Córdoba, Colombia, which results from alliances between international, national, and regional actors, becoming a reference that could serve as a basis. To be replicated in other institutions with characteristics similar to those described in this case. The model generally describes the entire process carried out in the intervention and focuses on the benefits generated for the educational community. Among the main results, the increase in thermal, lighting, and acoustic comfort of the educational community stands out, according to a survey and semi-structured interviews carried out. A fact that could be attributed to the perception of increased comfort in the community is the increase in the student population in 2022, going from 1,478 in 2019 to 1,909 in 2022, with a growth of approximately 29%. Energy renovation also resulted in the improvement of the indoor climate of the classrooms (from 35°C to 27°C), the improvement in the physical infrastructure of the institution, the integration of photovoltaic solar energy, and the subsequent reduction of energy cost.

In this paper, we propose a novel energy-efficient approach for mobile activity recognition system (ARS) to detect human activities. The proposed energy-efficient ARS, using low sampling rates, can achieve high recognition accuracy and low energy consumption. A novel classifier that integrates hierarchical support vector machine and context-based classification (HSVMCC) is presented to achieve a high accuracy of activity recognition when the sampling rate is less than the activity frequency, i.e., the Nyquist sampling theorem is not satisfied. We tested the proposed energy-efficient approach with the data collected from 20 volunteers (14 males and six females) and the average recognition accuracy of around 96.0% was achieved. Results show that using a low sampling rate of 1Hz can save 17.3% and 59.6% of energy compared with the sampling rates of 5 Hz and 50 Hz. The proposed low sampling rate approach can greatly reduce the power consumption while maintaining high activity recognition accuracy. The composition of power consumption in online ARS is also investigated in this paper.

Nowadays, manufacturing industry is under increasing pressure to save energy and reduce emissions, and thereby enhancing the energy efficiency of the machining system (MS) through operational methods on the system-level has attracted more attention. Energy-efficient scheduling (ES) has proved to be a typical measure suitable for all shop types, and an energy-efficient mechanism that a machine can be switched off and back on if it waits for a new job for a relatively long period is another proven effective energy-saving measure. Furthermore, their combination has been fully investigated in a single machine, flow shop and job shop, and the improvement in energy efficiency is significant compared with only applying ES for MS. However, whether such two energy-saving measures can be integrated in a flexible job shop environment is a gap in the existing study. To address this, a scheduling method applying an energy-efficient mechanism is proposed for a flexible job shop environment and the corresponding mathematical model, namely the energy-efficient flexible job shop scheduling (EFJSS) model, considering total production energy consumption (EC) and makespan is formulated. Besides, transportation as well as its impact on EC is taken into account in this model for practical application. Furthermore, a solution approach based on the non-dominated sorting genetic algorithm-II (NSGA-II) is adopted, which can avoid the interference of subjective factors and help select a suitable machine for each operation and undertake rational operation sequencing simultaneously. Moreover, experimental results confirm the validity of the improved energy-efficient scheduling approach in a flexible job shop environment and the effectiveness of the solution.

Buildings are responsible for 37% of CO2 emissions and 36% of energy use worldwide, making them significant contributors to both energy use and carbon emissions, due to which building energy efficiency is currently a top priority for regional, national, and global energy policy. This study evaluates building design features, such as window wall ratio (WWR), orientation, and shading coefficient (SC) for its single‐, low‐E double‐, and low‐E triple‐glazed windows. The building analyzed in this study is a hypothetical commercial building located in Lahore, Pakistan (ASHRAE zone 1B). The results show that compared to unglazed windows with a SC of 0.2 and 0.3, peak cooling total load (PCTL) and CO2 emissions are reduced by 17.84% and 17%, respectively, for single‐glazed windows. Similarly, low‐E double‐glazed windows reduce 21.3% and 20.9% in PCTL and CO2 emissions, while low‐E triple‐glazed windows result in reductions of 21.8% and 21.1%, respectively. Reducing the WWR from 15.14% to 4.94% results in a 5.35% reduction in PCTL and CO2 emissions. Moreover, Using the optimized orientation of the building (180° clockwise from north) further decreases PCTL and CO2 emissions by 8.63%. This analysis concludes that significant energy and environmental gains can be achieved by higher‐quality windows, utilizing optimized orientation, and reducing the WWR. In addition to ensuring long‐term cost savings, this strategic approach promotes a more sustainable and environmentally friendly future for future generations. The investigation of the effects of the building's orientation, window‐to‐wall ratio, and shading coefficient (SC) on the operational carbon reduction and peak cooling total load (PCTL) of the Plaza commercial building in Lahore, Pakistan (ASHRAE zone 1B).

Energy-efficient routing has become a critical issue for advanced energy-hungry unmanned aerial vehicles (UAVs). Routing in a flying ad hoc network is always challenging and becomes even more critical when a small number of UAVs must cover a large area. The routing protocols based on the delay-tolerant network (DTN) are best suited for such scenarios. However, traditional DTN-based routing protocols depend on data dissemination to offer a better packet delivery ratio, leading to congestion and excess transmissions, causing heavy and unnecessary energy consumption. We propose a location estimation-based congestion-aware routing protocol (LECAR) to balance these two issues. Considering outdated location information, LECAR takes advantage of the mobility model to estimate the current location of the destination. In addition, LECAR routes a packet by considering both the distance to destination and buffer occupancy of the neighboring UAVs. Simulation results show that LECAR could ensure both a high packet delivery ratio and low energy consumption. Moreover, LECAR could provide a minimal number of transmissions, while minimizing the number of copies per packet at a time.