Search Results (45)

With the rapid development of Internet of Things (IoT) and bioscience technology, wearable smart devices are developing toward advanced trends such as flexibility, convenience and environmental-friendliness. Poly (p-styrenesulfonic acid) (PSS), as a common template and dispersant, is indispensable in the polymerization of conductive polymers. However, the doping amount of PSS has a significant effect on the electrical conductivity of the polymer. Herein, different molar quantities of PSS were used to assist the polymerization of 3,4-ethylenedioxythiophene (EDOT) monomer in a horseradish peroxidase/hydrogen peroxide (HRP/H₂O₂) low-temperature system to obtain conductive finishing solutions with more excellent electrical properties. Then, the polyester nonwoven fabric was immersed in the conductive finishing solution, and when the addition ratio of EDOT and PSS was 1:2, the conductive performance was optimal (3.27 KΩ cm⁻¹). Finally, the conductive fabric was assembled into a pressure sensor and a temperature sensor, which can transmit Morse code in the form of single-parameter (pressure response or temperature response) or collaboration. Overall, this research has great potential for production of poly(3,4-ethylenedioxythiophene) (PEDOT)-based composites and their applications in smart wearable device. Full article

High-precision indoor positioning technology is increasingly prominent in its application value in emerging fields such as the Industrial Internet of Things, smart cities, and autonomous driving. 5G networks can transmit large-bandwidth signals and have the capability to transmit and receive signals with multiple antennas, enabling the simultaneous acquisition of angle and distance observation information, providing a solution for high-precision positioning. Differences in the types and quantities of observation information in complex environments lead to positioning scenarios having a multimodal nature; how to propose an effective observation model that covers multimodal scenarios for high-precision robust positioning is an urgent problem to be solved. This paper proposes a three-stage time–frequency synchronization method based on group peak time sequence tracing. Timing coarse synchronization is performed through a group peak accumulation timing coarse synchronization algorithm for multi-window joint estimation, frequency offset estimation is based on cyclic prefixes, and finally, fine timing synchronization based on the primary synchronization signal (PSS) sliding cross-correlation is used to synchronize 5G signals to chip-level accuracy. Then, a tracking loop is used to track the Positioning Reference Signal (PRS) to within-chip accuracy, obtaining accurate distance information. After obtaining distance and angle information, a high-precision positioning method for multimodal scenarios based on 5G heterogeneous measurement combination is proposed. Using high-precision angle observation values as intermediate variables, this algorithm can still solve a closed-form positioning solution under sparse observation conditions, enabling the positioning system to achieve good positioning performance even with limited redundant observation information. Full article

This study proposes a design method for the evaluation and redesign of product–service systems (PSSs) from the perspective of social sustainability, one that applies Max-Neef’s framework of fundamental human needs. The proposed method systematically connects PSS functions and requirements—identified through service blueprints and value graphs—to “satisfiers” and “barriers” extracted via needs-based workshops. This connection enables the identification of functions that either contribute to or hinder the fulfillment of fundamental human needs and guide the generation of redesign proposals aimed at sufficiency-oriented outcomes. A case study involving a smart-cart system in Osaka, Japan, was conducted to demonstrate the applicability of the method. Through an online workshop, satisfiers and barriers related to both physical and online shopping experiences were identified. The analysis revealed that existing functions such as promotional information and automated checkout processes negatively impacted needs such as understanding and affection due to information overload and reduced human interaction. In response, redesign concepts were developed, including filtering options for information, product background storytelling, and optional slower checkout lanes with human assistants. The redesigned functions contribute to the fulfillment of fundamental human needs, indicating that the proposed method can enhance social sustainability in PSS design. This study offers a novel framework that extends beyond traditional customer requirement-based approaches by explicitly incorporating human needs into function-level redesign. Full article

The smart construction of nano-photosensitizers (PSs) is significant for multipurpose applications, such as bioimaging, efficient photodynamic anti-tumor or anti-bacterial studies. This work reports a flexible self-assembling strategy for the construction of nano-PSs, in which PSs spontaneously form amorphous aggregates for killing bacteria, or self-assemble with tetraphenylethene (TPE) based glycoclusters (TPE-Glc₄) to construct glyco-dots for cell imaging and photodynamic anti-tumor studies. Tricyanofuran (TCF) and TPE units were bridged with furan or thiophene moiety to construct two PSs (1 and 2) with NIR fluorescence in monomers, and a performance of the aggregation-induced generation of reactive oxygen species (AIG-ROS) in an aggregated state. Compared to the large amorphous aggregates (2-a), TPE-based glycoclusters encapsulated with PS form glyco-dots (2-Glc) that exhibit a smaller and more homogeneous hydrated size of approximately 40 nm, as well as enhanced water-solubility and biocompatibility. TPE-glycoclusters facilitate the cellular uptake of 2 into HepG2 cells, therefore enhancing the NIR fluorescence imaging signal and photodynamic therapy. Meanwhile, 2-a exhibits satisfied phototoxicity against Escherichia coli. This work highlights the flexible self-assembly of nano-PSs for multifunctional bioapplications. Full article

PSS (Photovoltaic Solar Systems) are a key technology in energy transition, and their efficiency depends on multiple interrelated factors. This study uses a systematic review based on the PRISMA methodology to identify four main categories affecting performance: technological, environmental, design and installation, and operational factors. Notably, technological advances in materials such as perovskites and emerging technologies like tandem and bifacial cells significantly enhance conversion efficiency, fostering optimism in the field. Environmental factors, including solar radiation, temperature, and contaminants, also substantially impact system performance. Design and installation play a crucial role, particularly in panel orientation, solar tracking systems, and the optimization of electrical configurations. Maintenance, material degradation, and advanced monitoring systems are essential for sustaining efficiency over time. This study provides a comprehensive understanding of the field by reviewing 113 articles and analyzing three key areas—materials, application of sizing technologies, and optimization—from 2018 to 2025. The paper also explores emerging trends, such as the development of energy storage systems and the integration of smart grids, which hold promise for enhancing photovoltaic module (PM) performance. The findings highlight the importance of integrating technological innovation, design strategies, and effective operational management to maximize the potential of PM systems, providing a solid foundation for future research and applications across residential, industrial, and large-scale contexts. Full article

Recent advancements in smart textiles have facilitated their extensive application in wearable health monitoring, particularly in brain activity measurement. This study introduces a flexible and washable fabric dry electroencephalography (EEG) electrode designed for brain activity measurement. The fabric dry electrode is constructed from electrically conductive polyester fabric with a resistivity of 0.09 Ω·cm, achieved by applying a PEDOT: PSS/PVA conductive paste coating on the textile substrate. A comparative analysis of the tensile properties between the conductive and untreated polyester fabric was conducted. The SEM images demonstrated that the PEDOT: PSS/PVA conductive polymer composite resulted in a uniform coating on the fabric surface. When enveloped in elastic foam, the fabric dry electrode maintained a low and stable electrode–skin contact impedance during prolonged EEG monitoring. Additionally, the short circuit noise level of the fabric dry electrode exhibited superior performance compared to both Ag/AgCl wet and finger dry electrode. The EEG signals acquired from the fabric dry electrode were comparable to those recorded by the Ag/AgCl wet electrode. Moreover, the fabric electrode effectively captured clear and reliable EEG signals, even after undergoing 10 washing cycles. The fabric dry electrode indicates good sweat resistance and biocompatibility during prolonged monitoring. Full article

As an innovative branch of electronics, intelligent electronic textiles (e-textiles) have broad prospects in applications such as e-skin, human–computer interaction, and smart homes. However, it is still a challenge to distinguish multiple stimuli in the same e-textile. Herein, we propose a dual-parameter smart e-textile that can detect human pulse and body temperature in real time, with high performance and no signal interference. The doping of SWCNTs in PEDOT:PSS improves the electrical conductivity and Seebeck coefficient of the prepared composites, which results in excellent pressure and temperature-sensing properties of the PEDOT:PSS/SWCNTs/CS@PET-textile (PSCP) sensor. The dual-mode sensor has high sensitivity (32.4 kPa⁻¹), fast response time (~21 ms), and excellent durability (>2000 times) in pressure detection. Concurrently, this sensor maintains a high Seebeck coefficient of 25 μV/K in the 0–120 K temperature range with a tremendous linear relationship. Based on impressive dual-mode sensing characteristics and independent temperature-difference- and pressure-sensing mechanisms, smart e-textile sensors realize the real-time simultaneous monitoring of weak pulse signals and human body temperature, showing great potential in medical healthcare. In addition, the potential energy is excited by the temperature gradient between the human skin and the environment, which provides a novel idea for wearable self-powered devices. Full article

The global rise in diabetes has highlighted the urgent need for continuous, non-invasive health monitoring solutions. Traditional glucose monitoring methods, which are invasive and often inconvenient, have created a demand for alternative technologies that can offer comfort, accuracy, and real-time data. In this study, the development of a textile-based organic electrochemical transistor (OECT) is presented, designed for non-invasive glucose sensing, aiming to integrate this technology seamlessly into everyday clothing. The document details the design, optimization, and testing of a one-component textile-based OECT, featuring a porous PEDOT:PSS structure and a glucose oxidase-modified electrolyte for effective glucose detection in sweat. The research demonstrates the feasibility of using this textile-based OECT for non-invasive glucose monitoring, with enhanced sensitivity and specificity achieved through the integration of glucose oxidase within the electrolyte and the innovative porous PEDOT:PSS design. These findings suggest a significant advancement in wearable health monitoring technologies, providing a promising pathway for the development of smart textiles capable of non-invasively tracking glucose levels. Future work should focus on refining this technology for clinical use, including individual calibration for accurate blood glucose correlation and its integration into commercially available smart textiles. Full article

Porous conductive polymer structures, in particular Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) structures, are gaining in importance due to their versatile fields of application as sensors, hydrogels, or supercapacitors, to name just a few. Moreover, (porous) conducting polymers have become of interest for wearable and smart textile applications due to their biocompatibility, which enables applications with direct skin contact. Therefore, there is a huge need to investigate distinct, straightforward, and textile-compatible production methods for the fabrication of porous PEDOT:PSS structures. Here, we present novel and uncomplicated approaches to producing diverse porous PEDOT:PSS structures and characterize them thoroughly in terms of porosity, electrical resistance, and their overall appearance. Production methods comprise the incorporation of micro cellulose, the usage of a blowing agent, creating a sponge-like structure, and spraying onto a porous base substrate. This results in the fabrication of various porous structures, ranging from thin and slightly porous to thick and highly porous. Depending on the application, these structures can be modified and integrated into electronic components or wearables to serve as porous electrodes, sensors, or other functional devices. Full article

Ice formation on aircraft surfaces poses significant safety risks, and current detection systems often struggle to provide accurate, real-time predictions. This paper presents the development and comprehensive evaluation of a smart ice control system using a suite of machine learning models. The system utilizes various sensors to detect temperature anomalies and signal potential ice formation. We trained and tested supervised learning models (Logistic Regression, Support Vector Machine, and Random Forest), unsupervised learning models (K-Means Clustering), and neural networks (Multilayer Perceptron) to predict and identify ice formation patterns. The experimental results demonstrate that our smart system, driven by machine learning, accurately predicts ice formation in real time, optimizes deicing processes, and enhances safety while reducing power consumption. This solution holds the potential for improving ice detection accuracy in aviation and other critical industries requiring robust predictive maintenance. Full article

In the context of improving aircraft safety, this work focuses on creating and testing a graphene-based ice detection system in an environmental chamber. This research is driven by the need for more accurate and efficient ice detection methods, which are crucial in mitigating in-flight icing hazards. The methodology employed involves testing flat graphene-based sensors in a controlled environment, simulating a variety of climatic conditions that could be experienced in an aircraft during its entire flight. The environmental chamber enabled precise manipulation of temperature and humidity levels, thereby providing a realistic and comprehensive test bed for sensor performance evaluation. The results were significant, revealing the graphene sensors’ heightened sensitivity and rapid response to the subtle changes in environmental conditions, especially the critical phase transition from water to ice. This sensitivity is the key to detecting ice formation at its onset, a critical requirement for aviation safety. The study concludes that graphene-based sensors tested under varied and controlled atmospheric conditions exhibit a remarkable potential to enhance ice detection systems for aircraft. Their lightweight, efficient, and highly responsive nature makes them a superior alternative to traditional ice detection technologies, paving the way for more advanced and reliable aircraft safety solutions. Full article

Supply chain and logistics management is of tremendous importance for multinational organizations. Logistics Service Providers (LSPs) provide logistics services and smooth logistics operations between suppliers, manufacturers, distributors, and customers. This paper uses a Systematic Literature Review (SLR) to identify the current trends and future developments of LSPs and the underlying (smart) logistics operations connected to the concept of lifecycle management. An SLR review was conducted to identify relevant research papers in the areas of LSPs and logistics lifecycle management. Out of 288 papers analyzed, 81 were identified as highly appropriate for in-depth analysis. The LSP Lifecycle Model (LSLM) was then developed by combining logistics service characteristics and the lifecycle management concept, including Product Lifecycle Management (PLM), Service Lifecycle Management (SLM), and Product Service System (PSS). The LSLM consists of three phases: The Beginning of Life (BOL), the Middle of Life (MOL), and the End of Life (EOL). The LSLM is characterized by three phases, eight criteria, and seventeen sub-criteria. This paper aims to fulfil customer requirements through a product or service in the whole lifecycle of the logistics service provider. The findings further present an adaptable LSLM by focusing on various logistics services and integrating sustainability factors to meet market trends. Logistics cost factors can also be used to evaluate logistics services in the MOL stage. The EOL shows the trend of risk management, evaluation, and decomposition, which is determined by new or re-designed logistics products and services. Full article

Recently, online education has been gaining prominence in university life. Our survey aimed to examine sleep quality and perceived stress levels among students at the University of Pécs Faculty of Health Sciences. A cross-sectional, quantitative, descriptive survey was conducted between February and March 2023. The online survey included the Hungarian versions of the internationally validated Athens Insomnia Scale (AIS) and Perceived Stress Scale (PSS). Statistical analysis involved descriptive statistics, independent t-tests, analysis of variance (ANOVA), and Mann–Whitney and Kruskal–Wallis tests (p < 0.05). We analyzed 304 responses, and females dominated (n = 270; 88.8%). Students in a relationship had significantly higher AIS scores (t = −2.470; p = 0.014). Medium average (2.50–3.49) students and those who rarely/never exercise showed significantly higher AIS and PSS (p ≤ 0.05). Students on the phone/watching a series during online education, daily laptop/TV use for more than 2 h, and pre-sleep use of smart devices for more than 60 min also negatively affected AIS and PSS scores (p ≤ 0.05). Nursing, physiotherapy, and radiography students were the most affected regarding insomnia and perceived stress (p ≤ 0.05). Our survey shows that excessive smart device use and lack of exercise are associated with higher stress levels and poorer sleep quality. Full article

With the continuous development of information and communication technology, the development of smart product service systems (smart PSS) has become a crucial approach for enterprises to establish a competitive advantage. However, there is still a lack of clarity regarding the impact process of smart PSS on competitive advantage. This paper aims to explore the impact mechanism of smart PSS on competitive advantage from the perspective of value creation, using an intelligent connected vehicle supplier as a case study. The findings reveal that the composition of smart PSS, including smart technology, smart products, and smart services, influences competitive advantage through the value creation process, which involves relationship construction, relationship operation, and value release. Under the smart PSS environment, changes occur in subject relationships, resources, and key elements. In the context of smart PSS, deep cooperation between enterprises and partners focuses on ecological advantages, while general cooperation emphasizes benefit advantages. This research provides valuable insights into the impact of smart PSS composition on competitive advantage and offers reference values for organizations to establish competitive advantage objectives. Full article

Multifunctional fiber materials play a key role in the field of smart textiles. Temperature sensing and active thermal management are two important functions of smart fabrics, but few studies have combined both functions in a single fiber material. In this work, we demonstrate a temperature-sensing and in situ heating functionalized conductive polymer microfiber by exploiting its high electrical conductivity and thermoelectric properties. The conductive polymer microfibers were prepared by wet-spinning the PEDOT:PSS aqueous dispersion with ionic liquid additives, which was used to enhance the electrical and mechanical properties of the final microfibers. The thermoelectric properties of these microfibers were further studied. Due to their excellent flexibility and mechanical properties, these fibers can be easily integrated into commercial fabrics for the manufacture of smart textiles through knitting. We further demonstrated a smart glove with integrated temperature-sensing and in situ heating functions, and further explored thermoelectric fiber-based temperature-sensing array fabric. These works combine the thermoelectric properties and heating function of conductive polymer fibers, providing new insights that enable further development of high-performance, multifunctional wearable smart textiles. Full article