Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (8,540)

Search Parameters:
Keywords = power monitoring

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
17 pages, 1389 KiB  
Article
An Automatic Ear Temperature Monitoring Method for Group-Housed Pigs Adopting Infrared Thermography
by Changzhen Zhang, Xiaoping Wu, Deqin Xiao, Xude Zhang, Xiaopeng Lei and Sicong Lin
Animals 2025, 15(15), 2279; https://doi.org/10.3390/ani15152279 (registering DOI) - 4 Aug 2025
Abstract
The goal of this study was to develop an automated monitoring system based on infrared thermography (IRT) for the detection of group-housed pig ears temperature. The aim in the first part of the study was to recognize pigs’ ears by using neural network [...] Read more.
The goal of this study was to develop an automated monitoring system based on infrared thermography (IRT) for the detection of group-housed pig ears temperature. The aim in the first part of the study was to recognize pigs’ ears by using neural network analysis (SwinStar-YOLO). In the second part of the study, the goal was to automatically extract the maximum and average values of the temperature in the ear region using morphological image processing and a temperature matrix. Our dataset (3600 pictures, 10,812 pig ears) was processed using 5-fold cross-validation before training the ear detection model. The model recognized pigs’ ears with a precision of 93.74% related to threshold intersection over union (IoU). Correlation analysis between manually extracted and algorithm-derived ear temperatures from 400 pig ear samples showed coefficients of determination () of 0.97 for maximum and 0.88 for average values. This demonstrates that our proposed method is feasible and reliable for automatic pig ear temperature monitoring, serving as a powerful tool for early health warning. Full article
(This article belongs to the Special Issue Infrared Thermography in Animals)
28 pages, 2340 KiB  
Article
Determining the Operating Performance of an Isolated, High-Power, Photovoltaic Pumping System Through Sensor Measurements
by Florin Dragan, Dorin Bordeasu and Ioan Filip
Appl. Sci. 2025, 15(15), 8639; https://doi.org/10.3390/app15158639 (registering DOI) - 4 Aug 2025
Abstract
Modernizing irrigation systems (ISs) from traditional gravity methods to sprinkler and drip technologies has significantly improved water use efficiency. However, it has simultaneously increased electricity demand and operational costs. Integrating photovoltaic generators into ISs represents a promising solution, as solar energy availability typically [...] Read more.
Modernizing irrigation systems (ISs) from traditional gravity methods to sprinkler and drip technologies has significantly improved water use efficiency. However, it has simultaneously increased electricity demand and operational costs. Integrating photovoltaic generators into ISs represents a promising solution, as solar energy availability typically aligns with peak irrigation periods. Despite this potential, photovoltaic pumping systems (PVPSs) often face reliability issues due to fluctuations in solar irradiance, resulting in frequent start/stop cycles and premature equipment wear. The IEC 62253 standard establishes procedures for evaluating PVPS performance but primarily addresses steady-state conditions, neglecting transient regimes. As the main contribution, the current paper proposes a non-intrusive, high-resolution monitoring system and a methodology to assess the performance of an isolated, high-power PVPS, considering also transient regimes. The system records critical electrical, hydraulic and environmental parameters every second, enabling in-depth analysis under various weather conditions. Two performance indicators, pumped volume efficiency and equivalent operating time, were used to evaluate the system’s performance. The results indicate that near-optimal performance is only achievable under clear sky conditions. Under the appearance of clouds, control strategies designed to protect the system reduce overall efficiency. The proposed methodology enables detailed performance diagnostics and supports the development of more robust PVPSs. Full article
(This article belongs to the Special Issue New Trends in Renewable Energy and Power Systems)
Show Figures

Figure 1

22 pages, 1674 KiB  
Article
Air-STORM: Informed Decision Making to Improve the Success of Solar-Powered Air Quality Samplers in Challenging Environments
by Kyan Kuo Shlipak, Julian Probsdorfer and Christian L’Orange
Sensors 2025, 25(15), 4798; https://doi.org/10.3390/s25154798 (registering DOI) - 4 Aug 2025
Abstract
Outdoor air pollution poses a major global health risk, yet monitoring remains insufficient, especially in regions with limited infrastructure. Solar-powered monitors could allow for increased coverage in regions lacking robust connectivity. However, reliable sample collection can be challenging with these systems due to [...] Read more.
Outdoor air pollution poses a major global health risk, yet monitoring remains insufficient, especially in regions with limited infrastructure. Solar-powered monitors could allow for increased coverage in regions lacking robust connectivity. However, reliable sample collection can be challenging with these systems due to extreme temperatures and insufficient solar energy. Proper planning can help overcome these challenges. Air Sampler Solar and Thermal Optimization for Reliable Monitoring (Air-STORM) is an open-source tool that uses meteorological and solar radiation data to identify temperature and solar charging risks for air pollution monitors based on the target deployment area. The model was validated experimentally, and its utility was demonstrated through illustrative case studies. Air-STORM simulations can be customized for specific locations, seasons, and monitor configurations. This capability enables the early detection of potential sampling risks and provides opportunities to optimize monitor design, proactively mitigate temperature and power failures, and increase the likelihood of successful sample collection. Ultimately, improving sampling success will help increase the availability of high-quality outdoor air pollution data necessary to reduce global air pollution exposure. Full article
(This article belongs to the Special Issue Recent Trends in Air Quality Sensing)
15 pages, 3175 KiB  
Article
Creep Deformation Mechanisms of Gas-Bearing Coal in Deep Mining Environments: Experimental Characterization and Constitutive Modeling
by Xiaolei Sun, Xueqiu He, Liming Qiu, Qiang Liu, Limin Qie and Qian Sun
Processes 2025, 13(8), 2466; https://doi.org/10.3390/pr13082466 - 4 Aug 2025
Abstract
The impact mechanism of long-term creep in gas-containing coal on coal and gas outbursts has not been fully elucidated and remains insufficiently understood for the purpose of disaster engineering control. This investigation conducted triaxial creep experiments on raw coal specimens under controlled confining [...] Read more.
The impact mechanism of long-term creep in gas-containing coal on coal and gas outbursts has not been fully elucidated and remains insufficiently understood for the purpose of disaster engineering control. This investigation conducted triaxial creep experiments on raw coal specimens under controlled confining pressures, axial stresses, and gas pressures. Through systematic analysis of coal’s physical responses across different loading conditions, we developed and validated a novel creep damage constitutive model for gas-saturated coal through laboratory data calibration. The key findings reveal three characteristic creep regimes: (1) a decelerating phase dominates under low stress conditions, (2) progressive transitions to combined decelerating–steady-state creep with increasing stress, and (3) triphasic decelerating–steady–accelerating behavior at critical stress levels. Comparative analysis shows that gas-free specimens exhibit lower cumulative strain than the 0.5 MPa gas-saturated counterparts, with gas presence accelerating creep progression and reducing the time to failure. Measured creep rates demonstrate stress-dependent behavior: primary creep progresses at 0.002–0.011%/min, decaying exponentially to secondary creep rates below 0.001%/min. Steady-state creep rates follow a power law relationship when subject to deviatoric stress (R2 = 0.96). Through the integration of Burgers viscoelastic model with the effective stress principle for porous media, we propose an enhanced constitutive model, incorporating gas adsorption-induced dilatational stresses. This advancement provides a theoretical foundation for predicting time-dependent deformation in deep coal reservoirs and informs monitoring strategies concerning gas-bearing strata stability. This study contributes to the theoretical understanding and engineering monitoring of creep behavior in deep coal rocks. Full article
Show Figures

Figure 1

20 pages, 10490 KiB  
Article
A Web-Based Distribution Network Geographic Information System with Protective Coordination Functionality
by Jheng-Lun Jiang, Tung-Sheng Zhan and Ming-Tang Tsai
Energies 2025, 18(15), 4127; https://doi.org/10.3390/en18154127 (registering DOI) - 4 Aug 2025
Abstract
In the modern era of smart grids, integrating advanced Geographic Information Systems (GISs) with protection coordination functionalities is pivotal for enhancing the reliability and efficiency of distribution networks. This paper presents an implementation of a web-based distribution network GIS platform that seamlessly integrates [...] Read more.
In the modern era of smart grids, integrating advanced Geographic Information Systems (GISs) with protection coordination functionalities is pivotal for enhancing the reliability and efficiency of distribution networks. This paper presents an implementation of a web-based distribution network GIS platform that seamlessly integrates distribution system feeder GIS monitoring with the system model file layout, fault current analysis, and coordination simulation functions. The system can provide scalable and accessible solutions for power utilities, ensuring that protective devices operate in a coordinated manner to minimize outage impacts and improve service restoration times. The proposed GIS platform has demonstrated significant improvements in fault management and relay coordination through extensive simulation and field testing. This research advances the capabilities of distribution network management and sets a foundation for future enhancements in smart grid technology. Full article
Show Figures

Figure 1

17 pages, 5658 KiB  
Communication
When DNA Tells the Tale: High-Resolution Melting as a Forensic Tool for Mediterranean Cetacean Identification
by Mariangela Norcia, Alessia Illiano, Barbara Mussi, Fabio Di Nocera, Emanuele Esposito, Anna Di Cosmo, Domenico Fulgione and Valeria Maselli
Int. J. Mol. Sci. 2025, 26(15), 7517; https://doi.org/10.3390/ijms26157517 (registering DOI) - 4 Aug 2025
Abstract
Effective species identification is crucial for the conservation and management of marine mammals, particularly in regions such as the Mediterranean Sea, where several cetacean populations are endangered or vulnerable. In this study, we developed and validated a High-Resolution Melting (HRM) analysis protocol for [...] Read more.
Effective species identification is crucial for the conservation and management of marine mammals, particularly in regions such as the Mediterranean Sea, where several cetacean populations are endangered or vulnerable. In this study, we developed and validated a High-Resolution Melting (HRM) analysis protocol for the rapid, cost-effective, and reliable identification of the four representative marine cetacean species that occur in the Mediterranean Sea: the bottlenose dolphin (Tursiops truncatus), the striped dolphin (Stenella coeruleoalba), the sperm whale (Physeter macrocephalus), and the fin whale (Balaenoptera physalus). Species-specific primers targeting mitochondrial DNA regions (cytochrome b and D-loop) were designed to generate distinct melting profiles. The protocol was tested on both tissue and fecal samples, demonstrating high sensitivity, reproducibility, and discrimination power. The results confirmed the robustness of the method, with melting curve profiles clearly distinguishing the target species and achieving a success rate > 95% in identifying unknown samples. The use of HRM offers several advantages over traditional sequencing methods, including reduced cost, speed, portability, and suitability for degraded samples, such as those from the stranded individuals. This approach provides a valuable tool for non-invasive genetic surveys and real-time species monitoring, contributing to more effective conservation strategies for cetaceans and enforcement of regulations against illegal trade. Full article
(This article belongs to the Special Issue Molecular Insights into Zoology)
Show Figures

Figure 1

37 pages, 3005 KiB  
Review
Printed Sensors for Environmental Monitoring: Advancements, Challenges, and Future Directions
by Amal M. Al-Amri
Chemosensors 2025, 13(8), 285; https://doi.org/10.3390/chemosensors13080285 - 4 Aug 2025
Abstract
Environmental monitoring plays a key role in understanding and mitigating the effects of climate change, pollution, and resource mismanagement. The growth of printed sensor technologies offers an innovative approach to addressing these challenges due to their low cost, flexibility, and scalability. Printed sensors [...] Read more.
Environmental monitoring plays a key role in understanding and mitigating the effects of climate change, pollution, and resource mismanagement. The growth of printed sensor technologies offers an innovative approach to addressing these challenges due to their low cost, flexibility, and scalability. Printed sensors enable the real-time monitoring of air, water, soil, and climate, providing significant data for data-driven decision-making technologies and policy development to improve the quality of the environment. The development of new materials, such as graphene, conductive polymers, and biodegradable substrates, has significantly enhanced the environmental applications of printed sensors by improving sensitivity, enabling flexible designs, and supporting eco-friendly and disposable solutions. The development of inkjet, screen, and roll-to-roll printing technologies has also contributed to the achievement of mass production without sacrificing quality or performance. This review presents the current progress in printed sensors for environmental applications, with a focus on technological advances, challenges, applications, and future directions. Moreover, the paper also discusses the challenges that still exist due to several issues, e.g., sensitivity, stability, power supply, and environmental sustainability. Printed sensors have the potential to revolutionize ecological monitoring, as evidenced by recent innovations such as Internet of Things (IoT) integration, self-powered designs, and AI-enhanced data analytics. By addressing these issues, printed sensors can develop a better understanding of environmental systems and help promote the UN sustainable development goals. Full article
(This article belongs to the Section Electrochemical Devices and Sensors)
Show Figures

Figure 1

12 pages, 1178 KiB  
Systematic Review
Exploring the Preventive Effects of Omega-3 Polyunsaturated Fatty Acids Supplementation on Global Cognition: A Systematic Review and Meta-Analysis of Cognitively Unimpaired Older Adults
by Roberta Mulargia, Federica Ribaldi, Sophie Mutel, Ozge Sayin, Giorgi Khachvani, Gabriele Volpara, Giulia Remoli, Umberto Nencha, Stefano Gianonni-Luza, Stefano Cappa, Giovanni B. Frisoni and Augusto J. Mendes
Clin. Transl. Neurosci. 2025, 9(3), 34; https://doi.org/10.3390/ctn9030034 - 4 Aug 2025
Abstract
Dementia prevention is a global public health priority, and lifestyle interventions, including nutrition, have gained interest for their potential to maintain cognitive health. Among nutritional interventions, omega-3 polyunsaturated fatty acids (n-3 FA), particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), have been widely [...] Read more.
Dementia prevention is a global public health priority, and lifestyle interventions, including nutrition, have gained interest for their potential to maintain cognitive health. Among nutritional interventions, omega-3 polyunsaturated fatty acids (n-3 FA), particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), have been widely studied for their potential to support cognitive health. This systematic review evaluated whether n-3 FA supplementation improves global cognition in cognitively unimpaired older adults. Nineteen randomized controlled trials (RCTs) met inclusion criteria, of which five reported significant improvements in global cognition. A random-effects meta-analysis of 11 placebo-controlled RCTs showed no significant effect (SMD = −0.02, 95% CI: −0.07 to 0.04). Heterogeneity in supplement type, dosage, duration, and outcome measures may have contributed to inconsistent findings and limited comparability. Furthermore, methodological quality of the trials was generally low. While current evidence does not demonstrate a significant effect of n-3 FA supplementation on global cognition, future research should prioritize well-powered, longer-duration RCTs that incorporate biomarker monitoring and more appropriate doses. Clarifying the role of n-3 FA in cognitive aging remains essential for informing nutrition-based dementia prevention strategies. Full article
(This article belongs to the Special Issue Brain Health)
Show Figures

Figure 1

22 pages, 3275 KiB  
Article
Research on Q-Learning-Based Cooperative Optimization Methodology for Dynamic Task Scheduling and Energy Consumption in Underwater Pan-Tilt Systems
by Shan Tao, Lei Yang, Xiaobo Zhang, Shengya Zhao, Kun Liu, Xinran Tian and Hengxin Xu
Sensors 2025, 25(15), 4785; https://doi.org/10.3390/s25154785 (registering DOI) - 3 Aug 2025
Abstract
Given the harsh working conditions of underwater pan-tilt systems, their energy consumption management is particularly crucial. This study proposes an underwater pan-tilt operation method with an automatic wake-up mechanism, which activates only upon target detection, replacing conventional timer-based triggering. Furthermore, departing from fixed-duration [...] Read more.
Given the harsh working conditions of underwater pan-tilt systems, their energy consumption management is particularly crucial. This study proposes an underwater pan-tilt operation method with an automatic wake-up mechanism, which activates only upon target detection, replacing conventional timer-based triggering. Furthermore, departing from fixed-duration observation strategies, we introduce a Q-learning algorithm to optimize operational modes. The algorithm dynamically adjusts working modes based on surrounding biological activity frequency: employing a low-power mode (reduced energy consumption with lower monitoring intensity) during periods of sparse biological presence and switching to a high-performance mode (extended observation duration, higher energy consumption, and enhanced monitoring intensity) during frequent biological activity. Simulation results demonstrate that compared to fixed-duration observation schemes, the proposed optimization strategy achieves a 11.11% improvement in monitoring effectiveness while achieving 16.21% energy savings. Full article
(This article belongs to the Section Intelligent Sensors)
Show Figures

Figure 1

21 pages, 11558 KiB  
Article
First Steps Towards Site Characterization Activities at the CSTH Broad-Band Station of the Campi Flegrei’s Seismic Monitoring Network (Italy)
by Lucia Nardone, Rebecca Sveva Morelli, Guido Gaudiosi, Francesco Liguoro, Danilo Galluzzo and Massimo Orazi
Sensors 2025, 25(15), 4787; https://doi.org/10.3390/s25154787 (registering DOI) - 3 Aug 2025
Abstract
Local site conditions can significantly influence the amplitude, duration, and frequency content of seismic recordings, making the characterization of subsoil properties a critical component in seismic hazard assessment. However, despite extensive research, standardized methodologies for assessing site effects are still lacking. This study [...] Read more.
Local site conditions can significantly influence the amplitude, duration, and frequency content of seismic recordings, making the characterization of subsoil properties a critical component in seismic hazard assessment. However, despite extensive research, standardized methodologies for assessing site effects are still lacking. This study presents preliminary steps in the site characterization of a small area of Campi Flegrei caldera (Italy), with the aim of enhancing understanding of local lithology and seismic wave propagation. The analysis focuses on the broad-band seismic station CSTH, installed in 2021, and incorporates data from a temporary 2D array of five short-period sensors deployed around the station. These sensors recorded both ambient noise and seismic events associated with caldera dynamics. To improve the robustness of the characterization, data from two additional permanent broad-band stations (CPIS and CSOB) of the Istituto Nazionale di Geofisica e Vulcanologia—Osservatorio Vesuviano’s monitoring network, also located nearby a hydrothermal field, were included. Spectral analyses such as Power Spectral Density (PSD), Horizontal-to-Vertical (H/V) spectral ratios, and f-k array technique were performed to evaluate the frequency-dependent response of the site and to support the development of a comprehensive seismic site model. Full article
(This article belongs to the Section Remote Sensors)
Show Figures

Figure 1

24 pages, 4382 KiB  
Article
MTL-PlotCounter: Multitask Driven Soybean Seedling Counting at the Plot Scale Based on UAV Imagery
by Xiaoqin Xue, Chenfei Li, Zonglin Liu, Yile Sun, Xuru Li and Haiyan Song
Remote Sens. 2025, 17(15), 2688; https://doi.org/10.3390/rs17152688 - 3 Aug 2025
Abstract
Accurate and timely estimation of soybean emergence at the plot scale using unmanned aerial vehicle (UAV) remote sensing imagery is essential for germplasm evaluation in breeding programs, where breeders prioritize overall plot-scale emergence rates over subimage-based counts. This study proposes PlotCounter, a deep [...] Read more.
Accurate and timely estimation of soybean emergence at the plot scale using unmanned aerial vehicle (UAV) remote sensing imagery is essential for germplasm evaluation in breeding programs, where breeders prioritize overall plot-scale emergence rates over subimage-based counts. This study proposes PlotCounter, a deep learning regression model based on the TasselNetV2++ architecture, designed for plot-scale soybean seedling counting. It employs a patch-based training strategy combined with full-plot validation to achieve reliable performance with limited breeding plot data. To incorporate additional agronomic information, PlotCounter is extended into a multitask learning framework (MTL-PlotCounter) that integrates sowing metadata such as variety, number of seeds per hole, and sowing density as auxiliary classification tasks. RGB images of 54 breeding plots were captured in 2023 using a DJI Mavic 2 Pro UAV and processed into an orthomosaic for model development and evaluation, showing effective performance. PlotCounter achieves a root mean square error (RMSE) of 6.98 and a relative RMSE (rRMSE) of 6.93%. The variety-integrated MTL-PlotCounter, V-MTL-PlotCounter, performs the best, with relative reductions of 8.74% in RMSE and 3.03% in rRMSE compared to PlotCounter, and outperforms representative YOLO-based models. Additionally, both PlotCounter and V-MTL-PlotCounter are deployed on a web-based platform, enabling users to upload images via an interactive interface, automatically count seedlings, and analyze plot-scale emergence, powered by a multimodal large language model. This study highlights the potential of integrating UAV remote sensing, agronomic metadata, specialized deep learning models, and multimodal large language models for advanced crop monitoring. Full article
(This article belongs to the Special Issue Recent Advances in Multimodal Hyperspectral Remote Sensing)
Show Figures

Figure 1

17 pages, 1318 KiB  
Article
Mobile and Wireless Autofluorescence Detection Systems and Their Application for Skin Tissues
by Yizhen Wang, Yuyang Zhang, Yunfei Li and Fuhong Cai
Biosensors 2025, 15(8), 501; https://doi.org/10.3390/bios15080501 (registering DOI) - 3 Aug 2025
Abstract
Skin autofluorescence (SAF) detection technology represents a noninvasive, convenient, and cost-effective optical detection approach. It can be employed for the differentiation of various diseases, including metabolic diseases and dermatitis, as well as for monitoring the treatment efficacy. Distinct from diffuse reflection signals, the [...] Read more.
Skin autofluorescence (SAF) detection technology represents a noninvasive, convenient, and cost-effective optical detection approach. It can be employed for the differentiation of various diseases, including metabolic diseases and dermatitis, as well as for monitoring the treatment efficacy. Distinct from diffuse reflection signals, the autofluorescence signals of biological tissues are relatively weak, making them challenging to be captured by photoelectric sensors. Moreover, the absorption and scattering properties of biological tissues lead to a substantial attenuation of the autofluorescence of biological tissues, thereby worsening the signal-to-noise ratio. This has also imposed limitations on the development and application of compact-sized autofluorescence detection systems. In this study, a compact LED light source and a CMOS sensor were utilized as the excitation and detection devices for skin tissue autofluorescence, respectively, to construct a mobile and wireless skin tissue autofluorescence detection system. This system can achieve the detection of skin tissue autofluorescence with a high signal-to-noise ratio under the drive of a simple power supply and a single-chip microcontroller. The detection time is less than 0.1 s. To enhance the stability of the system, a pressure sensor was incorporated. This pressure sensor can monitor the pressure exerted by the skin on the detection system during the testing process, thereby improving the accuracy of the detection signal. The developed system features a compact structure, user-friendliness, and a favorable signal-to-noise ratio of the detection signal, holding significant application potential in future assessments of skin aging and the risk of diabetic complications. Full article
31 pages, 9769 KiB  
Review
Recent Advances of Hybrid Nanogenerators for Sustainable Ocean Energy Harvesting: Performance, Applications, and Challenges
by Enrique Delgado-Alvarado, Enrique A. Morales-Gonzalez, José Amir Gonzalez-Calderon, Ma. Cristina Irma Peréz-Peréz, Jesús Delgado-Maciel, Mariana G. Peña-Juarez, José Hernandez-Hernandez, Ernesto A. Elvira-Hernandez, Maximo A. Figueroa-Navarro and Agustin L. Herrera-May
Technologies 2025, 13(8), 336; https://doi.org/10.3390/technologies13080336 - 2 Aug 2025
Abstract
Ocean energy is an abundant, eco-friendly, and renewable energy resource that is useful for powering sensor networks connected to the maritime Internet of Things (MIoT). These sensor networks can be used to measure different marine environmental parameters that affect ocean infrastructure integrity and [...] Read more.
Ocean energy is an abundant, eco-friendly, and renewable energy resource that is useful for powering sensor networks connected to the maritime Internet of Things (MIoT). These sensor networks can be used to measure different marine environmental parameters that affect ocean infrastructure integrity and harm marine ecosystems. This ocean energy can be harnessed through hybrid nanogenerators that combine triboelectric nanogenerators, electromagnetic generators, piezoelectric nanogenerators, and pyroelectric generators. These nanogenerators have advantages such as high-power density, robust design, easy operating principle, and cost-effective fabrication. However, the performance of these nanogenerators can be affected by the wear of their main components, reduction of wave frequency and amplitude, extreme corrosion, and sea storms. To address these challenges, future research on hybrid nanogenerators must improve their mechanical strength, including materials and packages with anti-corrosion coatings. Herein, we present recent advances in the performance of different hybrid nanogenerators to harvest ocean energy, including various transduction mechanisms. Furthermore, this review reports potential applications of hybrid nanogenerators to power devices in marine infrastructure or serve as self-powered MIoT monitoring sensor networks. This review discusses key challenges that must be addressed to achieve the commercial success of these nanogenerators, regarding design strategies with advanced simulation models or digital twins. Also, these strategies must incorporate new materials that improve the performance, reliability, and integration of future nanogenerator array systems. Thus, optimized hybrid nanogenerators can represent a promising technology for ocean energy harvesting with application in the maritime industry. Full article
(This article belongs to the Special Issue Technological Advances in Science, Medicine, and Engineering 2024)
Show Figures

Graphical abstract

20 pages, 10013 KiB  
Article
Addressing Challenges in Rds,on Measurement for Cloud-Connected Condition Monitoring in WBG Power Converter Applications
by Farzad Hosseinabadi, Sachin Kumar Bhoi, Hakan Polat, Sajib Chakraborty and Omar Hegazy
Electronics 2025, 14(15), 3093; https://doi.org/10.3390/electronics14153093 - 2 Aug 2025
Viewed by 50
Abstract
This paper presents the design, implementation, and experimental validation of a Condition Monitoring (CM) circuit for SiC-based Power Electronics Converters (PECs). The paper leverages in situ drain–source resistance (Rds,on) measurements, interfaced with cloud connectivity for data processing and lifetime assessment, [...] Read more.
This paper presents the design, implementation, and experimental validation of a Condition Monitoring (CM) circuit for SiC-based Power Electronics Converters (PECs). The paper leverages in situ drain–source resistance (Rds,on) measurements, interfaced with cloud connectivity for data processing and lifetime assessment, addressing key limitations in current state-of-the-art (SOTA) methods. Traditional approaches rely on expensive data acquisition systems under controlled laboratory conditions, making them unsuitable for real-world applications due to component variability, time delay, and noise sensitivity. Furthermore, these methods lack cloud interfacing for real-time data analysis and fail to provide comprehensive reliability metrics such as Remaining Useful Life (RUL). Additionally, the proposed CM method benefits from noise mitigation during switching transitions by utilizing delay circuits to ensure stable and accurate data capture. Moreover, collected data are transmitted to the cloud for long-term health assessment and damage evaluation. In this paper, experimental validation follows a structured design involving signal acquisition, filtering, cloud transmission, and temperature and thermal degradation tracking. Experimental testing has been conducted at different temperatures and operating conditions, considering coolant temperature variations (40 °C to 80 °C), and an output power of 7 kW. Results have demonstrated a clear correlation between temperature rise and Rds,on variations, validating the ability of the proposed method to predict device degradation. Finally, by leveraging cloud computing, this work provides a practical solution for real-world Wide Band Gap (WBG)-based PEC reliability and lifetime assessment. Full article
(This article belongs to the Section Industrial Electronics)
25 pages, 2100 KiB  
Article
Flexible Demand Side Management in Smart Cities: Integrating Diverse User Profiles and Multiple Objectives
by Nuno Souza e Silva and Paulo Ferrão
Energies 2025, 18(15), 4107; https://doi.org/10.3390/en18154107 (registering DOI) - 2 Aug 2025
Viewed by 119
Abstract
Demand Side Management (DSM) plays a crucial role in modern energy systems, enabling more efficient use of energy resources and contributing to the sustainability of the power grid. This study examines DSM strategies within a multi-environment context encompassing residential, commercial, and industrial sectors, [...] Read more.
Demand Side Management (DSM) plays a crucial role in modern energy systems, enabling more efficient use of energy resources and contributing to the sustainability of the power grid. This study examines DSM strategies within a multi-environment context encompassing residential, commercial, and industrial sectors, with a focus on diverse appliance types that exhibit distinct operational characteristics and user preferences. Initially, a single-objective optimization approach using Genetic Algorithms (GAs) is employed to minimize the total energy cost under a real Time-of-Use (ToU) pricing scheme. This heuristic method allows for the effective scheduling of appliance operations while factoring in their unique characteristics such as power consumption, usage duration, and user-defined operational flexibility. This study extends the optimization problem to a multi-objective framework that incorporates the minimization of CO2 emissions under a real annual energy mix while also accounting for user discomfort. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is utilized for this purpose, providing a Pareto-optimal set of solutions that balances these competing objectives. The inclusion of multiple objectives ensures a comprehensive assessment of DSM strategies, aiming to reduce environmental impact and enhance user satisfaction. Additionally, this study monitors the Peak-to-Average Ratio (PAR) to evaluate the impact of DSM strategies on load balancing and grid stability. It also analyzes the impact of considering different periods of the year with the associated ToU hourly schedule and CO2 emissions hourly profile. A key innovation of this research is the integration of detailed, category-specific metrics that enable the disaggregation of costs, emissions, and user discomfort across residential, commercial, and industrial appliances. This granularity enables stakeholders to implement tailored strategies that align with specific operational goals and regulatory compliance. Also, the emphasis on a user discomfort indicator allows us to explore the flexibility available in such DSM mechanisms. The results demonstrate the effectiveness of the proposed multi-objective optimization approach in achieving significant cost savings that may reach 20% for industrial applications, while the order of magnitude of the trade-offs involved in terms of emissions reduction, improvement in discomfort, and PAR reduction is quantified for different frameworks. The outcomes not only underscore the efficacy of applying advanced optimization frameworks to real-world problems but also point to pathways for future research in smart energy management. This comprehensive analysis highlights the potential of advanced DSM techniques to enhance the sustainability and resilience of energy systems while also offering valuable policy implications. Full article
Show Figures

Figure 1

Back to TopTop