Search Results (815)

Precision agriculture and sustainable farming practices require autonomous environmental monitoring systems capable of operating in remote areas with limited energy and connectivity. However, the high cost of existing professional technology remains a significant barrier to widespread adoption. This study presents the development of a solar-powered smart sensing node designed for autonomous operation that integrates TinyML and dual-mode wireless connectivity via LoRaWAN and Wi-Fi for intelligent monitoring. The system features a custom-designed cup anemometer and multispectral sensing capabilities integrated into a compact single-tower architecture. All structural components, including radiation shields and a modular PVC frame, were designed for low-cost manufacturing and mass production. A single hermetic housing protects the core control electronics and is designed to improve durability in harsh outdoor environments. A Multi-Layer Perceptron model was implemented on the edge to enable intelligent data fusion and compensation, while a dynamic sampling strategy optimized power consumption. Experimental results demonstrate the feasibility of the proposed architecture through adaptive spectral acquisition over a daily illumination cycle, embedded MLP-based sensor fusion, and telemetry-oriented data compression that substantially reduces the number of transmitted samples. The main contribution of this work is a system-level architecture that integrates sensing, embedded intelligence, solar-energy harvesting, hybrid wireless communication, and telemetry optimization into a compact, low-cost, and field-deployable prototype IoT platform for sustainable precision agriculture. Full article

Measuring the water table level is a critical factor in irrigated agriculture in arid regions, as it can significantly influence the exchange of water and nutrients with crops. This work presents the design, implementation, and field validation of an open-source, solar-powered IoT device for autonomous groundwater level monitoring, combining long-range low-power LoRa communication, a non-contact pressure-based level sensor using the trapped-air capillary method, and an efficient power management stage that seamlessly switches between solar and battery power. Unlike existing commercial leveloggers, which are costly and lack integrated wireless telemetry and solar-based autonomy, the proposed platform is presented as a fully open-source, low-cost alternative purpose-built for unattended deployment in areas without grid power or cellular coverage. The system was validated through a multi-day field trial and dedicated communication tests, demonstrating a stable power conversion efficiency of 84–90%, a five-day autonomous operation without any deep-discharge event, high linearity ($R^2$ = 0.9998) of the level module over a 0–2 m range with a resolution of approximately 1.94 mm per ADC count, and a reliable LoRa link of up to 8.51 km in an urban/suburban environment despite non-line-of-sight conditions. With an estimated hardware cost of approximately $100 USD per unit, the device represents a low-cost, low-maintenance tool capable of generating knowledge about water resources to optimize irrigation and crop management in the face of climate change. Full article

Developing efficient, stable, and low-cost photocatalysts is the key to achieving large-scale photocatalytic hydrogen production. Herein, a universal fluoride-induced sulfur vacancy engineering strategy is proposed for the full Mn_xCd_1−xS solid solution series (x = 0.1–0.9), with Mn_0.6Cd_0.4S selected as the representative optimal sample. By introducing ammonium fluoride during the hydrothermal process, controllable sulfur vacancies are generated to enable efficient separation and transfer of photogenerated charge carriers for high-efficiency hydrogen production. Impressively, the optimal fluoride-modified Mn_0.6Cd_0.4S (F-MCS) photocatalyst shows the fastest hydrogen production rate up to 8.08 mmol·g⁻¹·h⁻¹, which is 1.5 times that of pure MCS nanoparticles, as well as enhanced photochemical stability. Quantitative EDS elemental analysis verifies that 1.2 at.% fluorine is incorporated into the lattice of F-MCS, rather than being physically adsorbed as residual ammonium fluoride precursors. Experimental results reveal that the introduction of NH₄F can effectively facilitate the sulfur vacancy formation in MCS, which alters the band position of MCS nanoflakes for increased light harvesting, and serves carrier separation centers for promoting the efficient transfer of photogenerated charge carriers. This study provides valuable insights into the design of a solid solution-based photocatalyst for efficient solar-driven hydrogen production for sustainable energy applications. Full article

The building envelope is a key lever for reducing energy demand and carbon emissions in the built environment. However, conventional envelope systems remain largely static and are unable to respond effectively to changing climatic conditions. Biomimetics has emerged as a promising approach for the development of climate-adaptive envelope solutions. Nevertheless, research in this field remains fragmented across disciplines, and its evolution and technological maturity have not yet been systematically assessed. This study proposes an integrated analytical framework combining a bibliometric analysis of 2.007 Scopus-indexed documents, based on a VOSviewer keyword co-occurrence network, with a cluster-guided state of the art review, and a Technology Readiness Level (TRL) assessment of selected biomimetic envelope solutions. The TRL assessment is conducted using explicit operational criteria. The analysis identifies three main research clusters: (C1) environmental-performative, focusing on energy efficiency and envelope optimisation; (C2) material-experimental, addressing biomimetic composites and innovative materials; and (C3) technological fabrication, centred on digital fabrication, smart materials, and 4D printing. Temporal trends reveal a shift after 2018 from materials science-oriented studies towards computational design and adaptive manufacturing, providing quantitative evidence of a transition previously described mainly in qualitative terms. The review highlights a strong focus on solar-shading applications, while energy harvesting and passive thermoregulation remain comparatively underexplored. The TRL assessment shows that more than 80% of the analysed solutions are concentrated at TRL 3, indicating an early stage of technological development. The main barriers include limited material durability, non-standardised production costs, and regulatory constraints. The findings suggest that future progress will depend less on the identification of new biological inspirations and more on advancing the technological maturity and industrial scalability of existing concepts. This will require integrated developments in materials, parametric design, life-cycle assessment, and regulatory frameworks. Full article

The practical performance of building-integrated solar systems in cold climates is strongly governed by temperature-grade matching between solar energy output and space-heating demand. However, year-round field evidence comparing solar thermal collectors, photovoltaic systems, and photovoltaic/thermal systems under the same building, climatic, and heating-network boundary conditions remains limited. This study conducted a year-round field evaluation of solar collector (SC), photovoltaic (PV), and photovoltaic/thermal (PVT) systems installed in an office building in Tianjin, China. Continuous operating data collected from November 2022 to October 2023 were used to assess seasonal thermal output, electricity generation, effective heat supply, solar utilization efficiency, carbon reduction, and payback period. During the heating season, SC exhibited the strongest direct-heating capability among the investigated systems, delivering 817.50 MJ/m² of useful heat. In contrast, under the investigated system configuration without heat-pump assistance, the outlet temperature of the PVT subsystem remained below the 45 °C direct-heating threshold, and its thermal output could not be directly utilized for winter space heating. This result is specific to the investigated operating conditions and does not exclude the potential application of PVT systems coupled with heat pumps or low-temperature heating terminals. During the non-heating season, the investigated PVT subsystem simultaneously produced electricity and usable low-temperature heat, with heat and electricity accounting for 61.3% and 38.7% of its useful output, respectively, indicating its potential for combined energy harvesting. Under the investigated climatic, system, cost, and energy-demand conditions, the entropy-weighted TOPSIS assessment ranked SC highest when non-heating-season heat demand was present, whereas PV was more suitable when such heat demand was absent. Furthermore, a demand–output matching method was developed to support SC/PV area allocation for different building types. Under the investigated climatic and energy-demand assumptions, the recommended PV area ratios were 54.5%, 67.4%, and 79.7% for residential, office, and commercial buildings, respectively. These results provide field evidence for effective heat evaluation, temperature-grade matching, and component selection in solar-assisted heating systems for cold-climate buildings. Full article

Global requirement of clean, cost-effective and sustainable energy has stimulated massive research and development in photocatalytic materials that have the potential to harvest solar based energy while mitigating the environmental issues. Among various materials, perovskite oxides have emerged as a promising energy resource. Owing to the structural versatility, optical and electrical properties, chemical inertness allows the use of material of multifunctional prospects. Currently Strontium titanate (SrTiO₃), a vital perovskite oxide having a band gap nearly ~3.2 eV, is showing significant function for photocatalytic water splitting, carbon dioxide conversion and degradation of organic pollutants. Though within the UV spectrum, its intrinsic photocatalytic behavior is limited to approaches such as graphene junctions, noble-metal support, and post-synthetic heat treatment seem to promote the adsorption within visible-light. Strontium titanate also demonstrates photo charge separation efficiency, and long-term catalytic durability. Moreover, modifications and hydrothermal synthesis have proven extremely efficient for nano-based engineering, control over crystal diameter, defects, and shape, which can result in magnificent composites that can be promising substitutes. Therefore, further research is imperative regarding these material application prospects. This comprehensive review provides insights into details on the potential of nanoengineering and composite approaches to reduce the inherent limitations of perovskite oxides, especially Strontium titanate, and enabling additional applications in next-generation photovoltaic and solar energy harvesting technologies. Full article

High-efficiency perfect absorption, spanning the entire visible region, plays an increasingly significant role in applications such as solar energy harvesting, photodetection, and thermal radiation management. However, the complexity and manufacturing difficulty of the currently proposed structures hinder large-scale application. In this work, we propose a broadband perfect absorber based on a tungsten–silicon nitride–tungsten (W-Si₃N₄-W) sandwich multilayer film. We combine the unique broadband absorption capability and high-temperature stability of material W with the low-loss characteristic of material Si₃N₄. By optimizing the geometrical parameters of the structure, we successfully achieved an average absorption efficiency exceeding 94% across a wide wavelength ranging from 500 nm to 900 nm. This work paves the way for developing high-performance, stable, and broadband absorption devices. Full article

We report the study of Cur@HKUST-1 composites, obtained through one-pot infiltration of HKUST-1 with curcumin (Cur) as a guest-sensitizing molecule. Cur features a HOMO energy above the valence band (VB) of HKUST-1, enabling modulation of the electronic structure of the host framework by introducing additional energy states within the bandgap. Structural characterization, including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA), confirmed successful guest incorporation and preservation of HKUST-1 crystallinity. An initial Cur amount of 50% (relative to the BTC linker) was added to the synthetic mixture, and differential UV-vis analysis has shown an infiltration efficiency of 28.0%, corresponding to an infiltration degree of 14% in the Cur@HKUST-1 composite, highlighting a challenging loading process, primarily due to the size and conformations of the Cur structure. Textural analysis revealed a reduction in surface area and pore volume, consistent with a high degree of guest infiltration. Optical properties evaluated by diffuse reflectance UV-vis spectroscopy revealed new absorption bands and a notable decrease of 1.83 eV in the bandgap energy from 3.68 eV (HKUST-1) to 1.85 eV (Cur@HKUST-1) due to guest molecule infiltration. Density functional theory (DFT) calculations supported the experimental findings, showing that guest HOMOs promoted the formation of a new valence band (VB), while the original VB remains lower in energy. Density-of-states analysis confirmed that the new VB originates from 2p orbitals belonging to the guest, while the conduction band remains predominantly Cu-based from the HKUST-1 framework. Photoelectrochemical characterization revealed that the guest-modified material exhibits an enhanced photocurrent response compared to HKUST-1. Cur@HKUST-1 displayed higher stability and stronger photocurrent density, attributed to its narrower bandgap and increased charge carrier density. These results demonstrate the potential of rational guest selection to engineer band structure and improve the light-harvesting performance of MOFs in solar-driven applications. Full article

With the rapid development of commercial aerospace, emerging applications such as satellite constellations, space-based communications, and orbital computing platforms have significantly increased the demand for efficient and reliable spacecraft power systems. Abundant exploitable energy exists in the space environment, including Air Mass Zero (AM0) solar radiation, spacecraft surface temperature gradients, ambient electromagnetic radiation, and radioisotope thermal energy, making multi-source energy harvesting a promising approach for improving satellite energy autonomy and system redundancy. This paper reviews the following four key space energy harvesting technologies: photovoltaic power generation, radio frequency (RF) energy harvesting, thermoelectric energy harvesting, and radioisotope thermoelectric generators (RTGs). The impacts of harsh space environmental factors on device performance and reliability are analyzed, and the applicability of different technologies in low Earth orbit (LEO), geostationary orbit (GEO), and deep-space missions is discussed. Furthermore, a multi-source self-powered satellite energy architecture integrating energy harvesting, energy storage, and power management is proposed. Finally, the major challenges and future development trends of satellite energy harvesting systems are summarized. Full article

Optoelectronic devices are emerging as a cornerstone of advanced renewable energy technologies, offering innovative routes for energy harvesting, conversion, and management with high efficiency and versatility. This review summarizes recent advances in the semiconductor materials engineering field, device configurations, and light–matter interaction mechanisms that underpin advanced optoelectronic systems for solar energy harvesting, solar-driven chemical conversion, and smart grid integration, among others. Emphasis is placed on the breakthroughs achieved in the perovskite and hybrid photovoltaics, photoelectrochemical energy conversion, and nanostructured optoelectronic platforms that enable much-increased light absorption, reduced recombination losses, and scalable large-scale fabrications. Moreover, the challenges closely linked with long-term stability, environmental durability and benevolence, and worldwide deployment are critically addressed, together with the emerging opportunities in AI design, tandem device technological solutions, integrated energy systems, and machine learning approaches for optimizing device performance, thermal management, and energy storage capabilities. Finally, the present review concludes by outlining the future research directions that could accelerate the transition toward high-performance, cost-effective, and sustainable optoelectronic solutions responsive to global renewable energy requirements. Full article

This study proposes a novel simulation-driven intelligent framework for the performance and reliability assessment of renewable energy-integrated pavement systems by unifying coupled multiphysics finite element modeling, structured dataset generation, and graph-based artificial intelligence within a single computational paradigm. The proposed pavement is formulated as a seven-layer multifunctional infrastructure system comprising the asphalt surface, intermediate binder, base layer, thermoelectric energy layer, piezoelectric insert zone, subbase, and subgrade soil, thereby enabling simultaneous consideration of structural load transfer, thermal gradient-driven energy harvesting, moisture-sensitive support behavior, and reliability-oriented performance interpretation. A three-dimensional thermo-hydro-mechanical Abaqus model was developed to simulate the concurrent effects of moving wheel load, solar heat flux, rainfall infiltration, and internal moisture diffusion, and it was subsequently used to construct an AI-ready dataset containing 6000 simulation cases and 68 variables spanning geometric, material, environmental, traffic, uncertainty, structural, thermal, hydraulic, renewable-energy, and probabilistic reliability descriptors. To preserve the physical hierarchy of the layered pavement within the learning process, a Layer-Coupled Reliability Graph Operator Network (LaRGO-Net) was proposed, in which pavement layers are represented as interacting graph nodes linked through adaptive interlayer coupling and optimized through multi-task, physics-aware, and coupling-consistent learning. Experimental evaluation across nine progressive configurations demonstrated a monotonic improvement from baseline dense and graph-convolution models to the full LaRGO-Net formulation. The final model achieved the best overall performance with mean RMSE = 0.040, mean MAE = 0.028, mean $R^2=0.994$, and reliability prediction accuracy characterized by F1 = 99.21 and AUC = 99.53. These results confirm that the proposed framework provides a highly accurate, physically interpretable, and reliability-aware surrogate for next-generation pavement systems capable of simultaneously supporting structural serviceability, renewable-energy functionality, and intelligent decision-making. Full article

Two semiflexible piezoelectric composite plate structures were developed, incorporating 1 × 9 and 2 × 9 arrays of PZT elements mounted on brass discs and mechanically secured by pop rivets within a thin plastic foil spacer positioned between two copper-clad PCB layers. This configuration provides reliable electrical contact, adequate mechanical compliance, and efficient conversion of mechanical vibration energy into electrical energy. In addition, a multifunctional thermoelectric device was realized, consisting of four cubic modules arranged around a rectangular tube and enabling both handheld operation and coupling to hot or cold surfaces. Each cube is equipped with optimized finned heat sinks and integrates four thermoelectric elements on each face. Experimental results show that each cube generates approximately 6 mW, when handheld and with icy water injected into the central tube, demonstrating its suitability as a compact and versatile thermal energy harvester. Under low-light conditions, a solar panel is supplemented by this hybrid piezoelectric–thermoelectric energy harvesting system that combines the output of a piezoelectric composite plate with the dual outputs of a thermoelectric device using an electronically isolated summing block to ensure source decoupling. Energy storage and management are implemented using a capacitor buffer for the piezoelectric device, two voltage boosters for the thermoelectric outputs, and an automatic ultra-low-power pulse width modulation buck regulator for charging supercapacitors at 5 V. Full article

Wireless sensor networks (WSNs) deployed for seismic monitoring must sustain long-term operation under strict energy constraints, where premature node failure degrades spatial coverage and detection reliability. This paper presents a safety-constrained reinforcement learning framework for transmission scheduling in energy-harvesting seismic WSNs. The proposed approach integrates Proximal Policy Optimisation (PPO) with action masking and a runtime guard-layer safety filter that enforces battery-preservation and load-balancing constraints without retraining. The guard layer intercepts policy actions and substitutes safe alternatives when constraint violations are detected, using a scoring function that combines battery headroom with network-wide load equity. Experiments across three network scales (10, 15, and 30 nodes) with solar energy harvesting demonstrate that the guard-enhanced PPO achieves 99.46% transmission success at 30 nodes while maintaining 66.47% node survival—a 58.3% improvement in survival over the highest-reward baseline (Closest) at the cost of only a 6.2% reduction in cumulative reward. Crucially, the guard-enhanced policy outperforms the unconstrained PPO baseline simultaneously on cumulative reward ($+11.4\%$), transmission success ($+0.8$ pp), and node survival ($+15.4\%$), demonstrating that hard safety constraints, when properly aligned with the system’s energy model, provide both performance and safety gains rather than a fundamental trade-off. Sensitivity analysis across event rates ($p_{\mathrm{event}}=0.5$ and $0.9$) confirms that the guard layer’s advantage persists under both moderate and extreme monitoring conditions. Analysis across scales reveals distinct operational regimes: at 10 nodes, heuristic baselines are near-optimal; at 30 nodes, learned policies dominate, and safety filtering becomes critical for sustained operation. Full article

This paper addresses the problem of efficient federated learning in energy-harvesting AIoT systems, where time-varying energy availability may lead to device blackouts and unstable learning performance. To address this issue, we propose an energy-adaptive multi-dimensional learning control framework that jointly determines model complexity and training intensity based on the real-time energy state of each device. This method integrates multiple control dimensions, including model pruning, quantization, knowledge distillation, and adaptive local training, into a unified decision mechanism under an energy constraint. Each device determines its participation in federated learning based on its residual energy relative to an energy threshold. When participating, the device selects a feasible learning configuration that jointly considers training intensity (e.g., epoch size and batch size) and lightweight learning operations to maximize learning effectiveness while preventing energy depletion. The proposed framework was implemented on a real-world testbed using NVIDIA Jetson Orin Nano devices under solar-energy-harvesting conditions. Our experimental results demonstrate that the proposed method significantly reduces device blackout while maintaining competitive model accuracy with respect to energy-unconstrained scenarios. These results highlight that joint control of multiple learning-cost factors is essential for achieving stable and efficient federated learning in energy-harvesting AIoT environments. Full article

This paper presents an experimental investigation of a spherical photovoltaic (SPV) system enhanced with an integrated paraboloid reflector and monitored via an Internet of Things (IoT) platform. The SPV’s omnidirectional geometry enables improved light absorption from multiple angles, maximizing energy capture throughout the day and under diverse weather conditions, particularly in extreme climates such as in Qatar. A prototype was developed using photovoltaic cells mounted on a 30 cm diameter spherical frame, paired with a reflector constructed from Styrofoam covered with mini glass mirrors. Performance was benchmarked against a conventional flat photovoltaic (FPV) panel with an equal number of cells. Real-time IoT monitoring captured voltage, temperature, and irradiance data, enabling precise performance evaluation. Results demonstrate that the SPV system achieved a 32.2% higher weekly energy output than the FPV panel, with reflector-assisted gains ranging from 14.8% to 39.7%. The SPV operated at 8–12 °C cooler, producing more stable voltage outputs (24–28 V vs. 17–25 V). Additionally, the design reduced dust accumulation by 27% and required ~35% less installation area per watt. IoT integration facilitated automated monitoring and alerts for critical conditions such as overheating (>50 °C) or voltage drops (<12 V). These findings highlight the SPV system as a compact, efficient, and intelligent solution for next-generation solar energy harvesting in urban and extreme-environment applications. Full article