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This study aims to develop two piezoelectric textile devices formed from different weft knitted fabric rapports (Jersey and Pique) to be applied in the renewable energy’s (RE) area.

Two different weft knitted rapports were produced with polyester (PES). The device developed has five layers: a central of poly(vinylidene fluoride) (PVDF) nonwoven, involved by two insulating layers of PES knitted fabric; and two conductive external layers, made of polypyrrole-coated PES knitted fabric. The piezoelectric textile devices were joined by sewing the five layers of the device.

The FTIR technique confirmed the β-phase in the PVDF nonwoven. This study produced and tested two different textiles devices with piezoelectric behavior, confirmed by the correlated pattern of voltage and tensile stress difference curves, showing the potential application in RE’s and sustainable energies field as smart textiles, such as devices incorporated in garments in the areas of high movement (elbow, knee, foot, fingers and hands, among others), and as an energy generator device

Textile materials with piezoelectric properties promise to advance RE’s developments due to their high material flexibility and sensitivity to the electrical response. The knitted fabric technology presents flexibility due to its construction process. Comparative studies analyzing the electrical response between knitted and woven fabrics have already been realized. However, there is a gap in terms of research scientific research regarding the comparison of the piezoelectric effect in a material that presents different knitted fabric rapports.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

This paper aims to investigate the optimization of window and shading designs to reduce the building energy consumption of a standard office room while improving occupants' comfort in Tehran and Auckland.

The NSGA-II algorithm, as a multi-objective optimization method, is applied in this study. First, a comparison of the effects of each variable on all objectives in both cities is conducted. Afterwards, the optimal solutions and the most undesirable scenarios for each city are presented for architects and decision-makers to select or avoid.

The results indicate that, in both cities, the number of slats and their distance from the wall are the most influential variables for shading configurations. Additionally, occupants' thermal comfort in Auckland is much better than in Tehran, while the latter city can receive more daylight. Furthermore, the annual energy use in Tehran can be significantly reduced by using a proper shading device and window-to-wall ratio (WWR), while building energy consumption, especially heating, is negligible in Auckland.

To the best of the authors' knowledge, this is the first study that compares the differences in window and shading design between two cities, Tehran and Auckland, with similar latitudes but located in different hemispheres. The outcomes of this study can benefit two groups: firstly, architects and decision-makers can choose an appropriate WWR and shading to enhance building energy efficiency and occupants' comfort. Secondly, researchers who want to study window and shading systems can implement this approach for different climates.

This paper aims to conduct a detailed analysis of the industrial practices currently being used in the geothermal energy industry and to determine whether they are contributing to any limitations. A HAZOP-based upgradation model for improvement in existing industrial practices is proposed to ensure the removal of inefficient conventional practices. The HAZOP-based upgradation model examines the setbacks, identifies its causes and consequences and suggests improvement methods comprising of modern-day technology.

This paper proposed a HAZOP-based upgradation model for improvement in existing industrial practices. The proposed HAZOP model identifies the drawbacks brought on by conventional practices and suggests improvements.

The study reviewed the challenges geothermal power plants currently face due to conventional practices and suggested a total of 22 upgradation recommendations. From those, a total of 11 upgradation modules comprising modern digital technology and Industry 4.0 elements were proposed to improve the existing practices in the geothermal energy industry. Autonomous robots, augmented reality, machine learning and Internet of Things were identified as useful methods for the upgradation of the existing geothermal energy system.

If proposed recommendations are incorporated, the efficiency of geothermal energy generation will increase as cumulating setbacks will no longer degrade the work output.

The proposed recommendation by the study will make way for Industry 4.0 integration with the geothermal energy sector.

The paper uses a proposed HAZOP-based upgradation model to review issues in existing industrial practices of the geothermal energy sector and recommends solutions to overcome operability issues using Industry 4.0 technologies.

The purpose of this paper is to introduce flexible dye-sensitized solar cells (FDSSCs).

In the third generation solar cells, glass was used as a substrate, which due to its high weight and fragility, was not possible to produce continuously. However, in flexible solar cells, flexible substrates are used as new technology. The most important thing may choose a suitable substrate to produce a photovoltaic (PV) device with optimal efficiency.

Conductive plastics or metallic foils are the two main candidates for glass replacement, each with its advantages and disadvantages. As some high-temperature methods are used to prepare solar cells, metal substrates can be used to prepare PV devices without any problems. In contrast to the advantage of high thermal resistance in metals, metal substrates are dark and do not transmit enough light. In other words, metal substrates have a high loss of photon energy. Like all technologies, PV devices with polymer substrates have technical disadvantages.

In this study, the development of FDSSCs offers improved photovoltaic properties.

The most important challenge is the poor thermal stability of polymers compared to glass and metal, which requires special methods to prepare polymer solar cells. The second important point is choosing the suitable components and materials for this purpose.

Dependence of efficiency and performance of the device on the angle of sunlight, high-cost preparation devices components, limitations of functional materials such as organic-mineral sensitizers, lack of close connection between practical achievements and theoretical results and complicated fabrication process and high weight.

This purpose of this paper is to address the problem of reducing energy consumption in existing buildings using advanced noninvasive interventions (NVIs).

The study methodology involves systematically developing and testing 18 different NVIs in six categories (glazing types, window films, external shading devices, automated internal shades, lighting systems and nanopainting) to identify the most effective individual NVIs. The impact of each individual NVI was examined on an exemplary university educational building in a hot climate zone in Egypt using a computational energy simulation tool, and the results were used to develop 39 combination scenarios of dual, triple and quadruple combinations of NVIs.

The optimal 10 combination scenarios of NVIs were determined based on achieving the highest percentages of energy reduction. The optimal percentage of energy reduction is 47.1%, and it was obtained from a combination of nanowindow film, nanopainting, LED lighting and horizontal louver external. The study found that appropriate mixture of NVIs is the most key factor in achieving the highest percentages of energy reduction.

These results have important implications for optimizing energy savings in existing buildings. The results can guide architects, owners and policymakers in selecting the most appropriate interventions in existing buildings to achieve the optimal reduction in energy consumption.

The novelty of this research unfolds in two significant ways: first, through the exploration of the potential effects arising from the integration of advanced NVIs into existing building facades. Second, it lies in the systematic development of a series of scenarios that amalgamate these NVIs, thereby pinpointing the most efficient strategies to optimize energy savings, all without necessitating any disruptive alterations to the existing building structure. These combination scenarios encompass the incorporation of both passive and active NVIs. The potential application of these diverse scenarios to a real-life case study is presented to underscore the substantial impact that these advanced NVIs can have on the energy performance of the building.

The escalating levels of greenhouse gas emissions have become a growing global concern, with household energy consumption emerging as a significant contributor. To develop effective public policies, it is crucial to understand the energy-saving behavior of households. This study delves into the determinants of energy-saving practices in a developing country.

The authors chose a multivariate probit model, as it allowed to look after possible correlations among seven energy-saving practices within households.

The findings underscore the significant influence of sociodemographic variables, such as gender, civil status, income and education, on energy-saving practices. Furthermore, the authors discovered that households where the head actively volunteers in social organizations are more likely to adopt energy-saving behaviors. Additionally, internet access positively contributes to pro-environmental behavior. This research reveals that certain energy-saving practices are interconnected, acting as complements or substitutes.

Recommendations for public policy include prioritizing education in rural areas to boost energy-saving practices, improving internet access in nonurban regions and promoting citizen involvement in social organizations to enhance environmental awareness and encourage energy-saving behavior. The authors contribute to literature evidencing that certain energy-saving practices are not independent of each other, they are rather complementary and, in some cases, substitutes.

Recommendations for public policy include prioritizing education in rural areas to boost energy-saving practices, improving Internet access in nonurban regions and promoting citizen involvement in social organizations to enhance environmental awareness and encourage energy-saving behavior.

Previous studies have overlooked these interdependencies, highlighting the necessity of a system of equations to yield more efficient estimates by considering correlations between error terms.

The changes brought by Industry 4.0 go beyond transformations in the industrial environment. The increasingly frequent digitization and robotization of activities is not only restricted to the industrial environment, but also to people's daily routine. People spend a large part of their time inside buildings, and maintaining adequate Indoor Environmental Quality (IEQ) is an essential factor for a healthy and productive environment. In this sense, the purpose of this study is to verify how the Internet of Things (IoT) is being used to improve the indoor environment, through sensors that instantly measure the conditions of the environment.

The aim of this paper is to verify, through a literature review, how IoT is being used for building control (for energy saving purposes) and to monitor IEQ conditions inside buildings, in order to provide a better environment for occupants, in terms of health and comfort. By combining keywords in databases, PRISMA method was used to select the articles for analysis, and 91 articles were analyzed.

The main findings in this research are: (1) the main purpose for applying IoT inside buildings is to reduce energy consumption; (2) there is an interest in developing low-cost sensoring devices with a learning approach; (3) Machine Learning methods are mainly used for energy saving purposes and to learn about occupants' behavior inside buildings, focusing on thermal comfort; (4) sensors in the IoT era are a requirement to help improve people's comfort and well-being.

Studies directly correlating IoT and IEQ are limited. This paper emphasises the link between them, through the presentation of recent methods to control the built environment.