Search Results (6,549)

This work presents the design, the development and the experimental validation of a portable, low-cost sensing system for the detection of waterborne pollutants. The proposed system is based on Electrochemical Impedance Spectroscopy and PPF+Ni nanomembrane sensors. Designed in response to the increasing demand for in situ water quality monitoring, the system integrates a simplified, scalable EIS acquisition architecture compatible with microcontroller-based platforms. The sensing configuration utilises the voltage divider principle, ensuring simplicity in signal conditioning by allowing compatibility with different electrode types through passive impedance matching. In addition, new merit figures have been proposed and implemented to analyse the measures. The proposed platform was experimentally characterised for its measurement stability, accuracy and environmental robustness. Sensitivity tests using benzoquinone as a target analyte demonstrated the capability of detecting concentrations as low as 0.1 mM with a monotonic response over increasing concentrations. A comparative study with a commercial electrochemical system (PalmSens4) under identical conditions highlighted the higher resolution and practical advantages of the proposed method despite operating with a lower impedance range. Additionally, the system exhibited reliable discrimination across tested concentrations and greater adaptability for integration into field-deployable environmental monitoring platforms. Future developments will focus on optimising selectivity through new sensor materials and analytical modelling of uncertainty propagation in the analysis based on defined figures of merit. Full article

Metal-organic frameworks (MOFs), a class of crystalline porous materials featuring a high specific surface area, tunable pore structures, and functional surfaces, exhibit remarkable potential in fluorescent sensing. This review systematically summarizes recent advances in the construction strategies, sensing mechanisms, and applications of MOF-based fluorescent sensors. It begins by highlighting the diverse degradation pathways that MOFs encounter in practical applications, including hydrolysis, acid/base attack, ligand displacement by coordinating anions, photodegradation, redox processes, and biofouling, followed by a detailed discussion of corresponding stabilization strategies. Subsequently, the review elaborates on the construction of sensors based on individual MOFs and their composites with metal nanomaterials, MOF-on-MOF heterostructures, covalent organic frameworks (COFs), quantum dots (QDs), and fluorescent dyes, emphasizing the synergistic effects of composite structures in enhancing sensor performance. Furthermore, key sensing mechanisms such as fluorescence quenching, fluorescence enhancement, Stokes shift, and multi-mechanism coupling are thoroughly examined, with examples provided of their application in detecting biological analytes, environmental pollutants, and food contaminants. Finally, future directions for MOF-based fluorescent sensors in food safety, environmental monitoring, and clinical diagnostics are outlined, pointing to the development of high-performance, low-cost MOFs; the integration of multi-technology platforms; and the construction of intelligent sensing systems as key to enabling their practical deployment and commercialization. Full article

Organic–inorganic hybrid metal halides (OIMHs) have attracted widespread attention due to their unique chemical properties, excellent electronic performance, and low-cost fabrication processes. These hybrid materials impose fewer size constraints on the organic components, providing an exciting platform for the molecular-level design of new materials and functionalities. In this review, we discuss the latest progress in OIMHs. Specifically, we summarize recent advances in their structures, synthetic strategies, and luminescence mechanisms, and highlight their applications in light-emitting diodes (LEDs), information encryption and anti-counterfeiting, sensors, and X-ray imaging. Finally, we discuss the challenges related to structural design, mechanistic understanding, and stability, along with perspectives on future opportunities for OIMHs. Full article

Metal oxide semiconductor (MOS) gas sensors offer several advantages, including low cost, high accuracy, and ease of miniaturization. Thus, they are excellent candidates for environmental monitoring and food spoilage detection applications, particularly in the safe Internet of Things field or for portable instruments. Typically, there are two general routes for realizing low-power-consumption MOS gas sensors: room-temperature MOS gas sensors or MEMS MOS gas sensors. The review focuses on the detection of four typical gases, namely methane, hydrogen, carbon monoxide, and nitrogen dioxide, systematically summarizing and analyzing the most recent results of low-power-consumption MOS gas sensors. The 2D materials, MOS composites, and 3D structured composites exhibit excellent room-temperature gas detection capabilities. The mechanism of the room-temperature gas sensors is also discussed in detail. Another route is MEMS MOS gas sensors. First, the progress of the micro-hotplate research is introduced. Then, several of the latest reported MEMS MOS gas sensors are shown and compared. The gas sensing mechanism of these MEMS MOS gas sensors is also given. The paper will provide a valuable guide for researchers in the MOS gas sensor field, particularly for those working towards low-power-consumption MOS gas sensors. Full article

This study presents a comparative performance analysis of three sensor technologies—microphone, magnetic pickup, and laser Doppler vibrometer—for capturing string vibration under varied excitation conditions: striking, plectrum plucking, and wire plucking. Two different magnetic pickups are included in the comparison. Measurements were taken at multiple excitation levels on a simplified electric guitar mounted on a stable platform with repeatable excitation mechanisms. The analysis focuses on each sensor’s capacity to resolve fine-scale waveform features during the initial attack while also taking into account its capability to measure general changes in instrument dynamics and timbre. We evaluate their ability to distinguish vibro-acoustic phenomena resulting from changes in excitation method and strength as well as measurement location. Our findings highlight the significant influence of sensor choice on observable string vibration. While the microphone captures the overall radiated sound, it lacks the required spatial selectivity and offers poor SNR performance 34 dB lower then other methods. Magnetic pickups enable precise string-specific measurements, offering a compelling balance of accuracy and cost-effectiveness. Results show that their low-pass frequency characteristic limits temporal fidelity and must be accounted for when analysing general sound timbre. Laser Doppler vibrometers provide superior micro-temporal fidelity, which can have critical implications for physical modeling, instrument design, and advanced audio signal processing, but have severe practical limitations. Critically, we demonstrate that the required optical target, even when weighing as little as 0.1% of the string’s mass, alters the string’s vibratory characteristics by influencing RMS energy and spectral content. Full article

Zinc oxide (ZnO) nanomaterials have emerged as promising candidates for gas sensing applications due to their high sensitivity, fast response–recovery cycles, thermal and chemical stability, and low fabrication cost. However, the performance of pristine ZnO remains limited by high operating temperatures, poor selectivity, and suboptimal detection at low gas concentrations. To address these limitations, significant research efforts have focused on dopant incorporation and polymer hybridization. This review summarizes recent advances in dopant engineering using elements such as Al, Ga, Mg, In, Sn, and transition metals (Co, Ni, Cu), which modulate ZnO’s crystal structure, defect density, carrier concentration, and surface activity—resulting in enhanced gas adsorption and electron transport. Furthermore, ZnO–polymer nanocomposites (e.g., with polyaniline, polypyrrole, PEG, and chitosan) exhibit improved flexibility, surface functionality, and room-temperature responsiveness due to the presence of active functional groups and tunable porosity. The synergistic combination of dopants and polymers facilitates enhanced charge transfer, increased surface area, and stronger gas–molecule interactions. Where applicable, sol–gel-based studies are explicitly highlighted and contrasted with non-sol–gel routes to show how synthesis controls defect chemistry, morphology, and sensing metrics. This review provides a comprehensive understanding of the structure–function relationships in doped ZnO and ZnO–polymer hybrids and offers guidelines for the rational design of next-generation, low-power, and selective gas sensors for environmental and industrial applications. Full article

This paper presents the development of a modular and low-cost IoT (Internet of Things) system for remote monitoring of essential parameters during wine fermentation, designed for small and medium-sized wineries—Winnie. The system combines distributed embedded sensing units with centralized colorimetric analysis and real-time data transmission to a remote server. Barrel-mounted devices measure wine and cellar parameters (temperature, humidity, and CO₂ concentration), while a central hub performs colorimetric SO₂ analysis using an RGB color sensor and automated fluid handling. Communication between the Barrel and Hub device relies on the RS-485 protocol, providing robustness in harsh winery conditions. All measurements are securely transferred via Wi-Fi. A hash-based integrity check ensures continuous and reliable data collection. The modular design, simple installation, and user-friendly web interface make the system accessible to winemakers. This technology provides a scalable method for digitalizing conventional winemaking processes by reducing the cost and complexity of wine quality monitoring. Full article

This study proposes and demonstrates a highly sensitive displacement sensor based on a flexible random laser. The sensor utilizes a polydimethylsiloxane (PDMS) film where a self-assembled surface grating structure is formed via oxygen plasma surface treatment combined with bending prestress. This structure acts as a photon-trapping microcavity and multiple scattering feedback center, integrated with embedded laser dye PM597 as the gain medium to form a flexible grating random laser. Experiments show that the device generates random lasing emission under 532 nm pumping (threshold ~21 mJ/cm²) with a linewidth of ~0.25 nm and a degree of polarization of ~0.82. Applying micro-displacement alters the PDMS film curvature, subsequently changing the grating morphology (height, angle). This modifies photon trapping efficiency and geometric deflection loss within the equivalent resonator cavity, leading to significant modulation of the random laser output intensity. A linear correspondence between displacement and lasing intensity was established (R² ≈ 0.91), successfully demonstrating displacement sensing functionality. This scheme not only provides a low-cost method for fabricating flexible grating random lasers but also leverages the extreme sensitivity of random lasing modes to local disordered structural changes, paving the way for novel high-sensitivity mechanical sensors and on-chip integrated photonic devices. Full article

In the heating, ventilation, and air conditioning (HVAC) systems of mushroom growing control rooms, traditional rule-based control methods are commonly adopted. However, these methods are characterized by response delays, leading to underutilization of energy-saving potential and energy costs that constitute a disproportionately high share of overall production costs. Therefore, minimizing the running time of the air conditioning system is crucial while maintaining the optimal growing environment for mushrooms. To address the aforementioned issues, this paper proposed a sensor optimization method based on the combination of principal component analysis (PCA) and information entropy. Furthermore, model predictive control (MPC) was implemented using a gated recurrent unit (GRU) neural network with an attention mechanism (GRU-Attention) as the prediction model to optimize the air conditioning system. First, a method combining PCA and information entropy was proposed to select the three most representative sensors from the 16 sensors in the mushroom room, thus eliminating redundant information and correlations. Then, a temperature prediction model based on GRU-Attention was adopted, with its hyperparameters optimized using the Optuna framework. Finally, an improved crayfish optimization algorithm (ICOA) was proposed as an optimizer for MPC. Its objective was to solve the control sequence with high accuracy and low energy consumption. The average energy consumption was reduced by approximately 11.2%, achieving a more stable temperature control effect. Full article

Albendazole (ABZ) is a broad-spectrum anthelmintic drug whose residual presence in food and the environment raises public health concerns, requiring rapid and sensitive methods of detection. In this work, a sensitive Fabry–Pérot interferometer (FPI) probe was fabricated by realizing a cavity located at the tip of a single-mode optical fiber core with a molecularly imprinted polymer (MIP) for ABZ detection. The fabrication process involved the development of a photoresist-based micro-hole filled by the specific MIP via thermal polymerization. Interferometric measurements obtained using the proposed sensor system have demonstrated a limit of detection (LOD) of 27 nM, a dynamic concentration range spanning from 27 nM (LOD) to 250 nM, and a linear response at the nanomolar level (27 nM–100 nM). The selectivity test demonstrated no signal when interfering molecules were present, and the application of the sensor for ABZ quantification in a commercial pharmaceutical sample provided good recovery, in accordance with bioanalytical validation standard methods. These results demonstrate the capability of a MIP layer-based FPI probe to provide low-cost and selective optical-sensing strategies, proposing a competitive approach to traditional analytical techniques for ABZ monitoring. Full article

Anaerobic digestion of manures, crop residues, food waste, and sludge frequently yields biogas with elevated hydrogen sulfide concentrations, which accelerate corrosion and reduce biogas quality. Microaeration, defined as the controlled addition of oxygen at 1 to 5% of the biogas production rate, has been investigated as a low-cost desulfurization strategy. This review synthesizes studies from 2015 to 2025 spanning laboratory, pilot, and full-scale anaerobic digester systems. Continuous sludge digesters supplied with ambient air at 0.28–14 m³ h⁻¹ routinely achieved 90 to 99% H₂S removal, while a full-scale dairy manure system reported a 68% reduction at 20 m³ air d⁻¹. Pure oxygen dosing at 0.2–0.25 m³ O₂ (standard conditions) per m³ reactor volume resulted in greater than 99% removal. Reported methane yield improvements ranged from 5 to 20%, depending on substrate characteristics, operating temperature, and aeration control. Excessive oxygen, however, reduced methane yields in some cases by inhibiting methanogens or diverting carbon to CO₂. Documented benefits of microaeration include accelerated hydrolysis of lignocellulosic substrates, mitigation of sulfide inhibition, and stimulation of sulfur-oxidizing bacteria that convert sulfide to elemental sulfur or sulfate. Optimal redox conditions were generally maintained between −300 and −150 mV, though monitoring was limited by low-resolution oxygen sensors. Recent extensions of the Anaerobic Digestion Model No. 1 (ADM1), a mathematical framework developed by the International Water Association, incorporate oxygen transfer and sulfur pathways, enhancing its ability to predict gas quality and process stability under microaeration. Economic analyses estimate microaeration costs at 0.0015–0.0045 USD m⁻³ biogas, substantially lower than chemical scrubbing. Future research should focus on refining oxygen transfer models, quantifying microbial shifts under long-term operation, assessing effects on digestate quality and nitrogen emissions, and developing adaptive control strategies that enable reliable application across diverse substrates and reactor configurations. Full article

Water-quality monitoring plays a vital role in protecting and managing water resources, maintaining ecological balance and safeguarding human health. At present, the traditional monitoring technology is associated with risks of low sampling efficiency, long response time, high economic cost and secondary pollution of water samples, and cannot guarantee the accuracy and real-time determination of monitoring data. Remote sensing (RS) technology and sensors are used to automatically realize the real-time monitoring of water quality. In this paper, the principles and composition of remote monitoring systems are systematically summarized. For the RS technology, indicators including chlorophyll-a, turbidity and total suspended matter/solids, colored dissolved organic matter, electrical conductivity (EC), dissolved oxygen (DO), temperature and pH value were considered, and for sensors monitoring, the parameters of pH value, temperature, oxidation reduction potential, DO, turbidity, EC and salinity, and total dissolved solids were analyzed. The practical applications of remote monitoring in surface water, marine water and wastewater are introduced in this context. In addition, the advantages and disadvantages of remote monitoring systems are evaluated, which provides some basis for the selection of remote monitoring systems in the future. Full article

Electrochemical aptasensors have been successfully applied in a number of fields, including food safety, environmental monitoring, and the health sector. They offer a robust and environmentally friendly alternative to antibody-based detection, with the added benefits of flexible design, high chemical and thermal stability, and low immunogenicity. In this work, we present an electrochemical aptasensor based on a semiconducting mesoporous TiO₂:Mn working electrode (WE) for the sensitive detection of tetracycline (TET). The TiO₂:Mn electrodes were fabricated using a scalable screen-printing process, providing a cost-efficient and reproducible platform for sensor development. Specifically, a 5 μM solution of the DNA aptamer with the sequence 5′-CCC CCG GCA GGC CAC GGC TTG GGTTGG TCC CAC TGC GCG-3′ was utilized for the detection of tetracycline (TET) in spiked aqueous samples, across a concentration range of 0.3 to 25.0 ng/mL. Detection was performed via differential pulse voltammetry (DPV) using a Pt wire cathode. The buffer used in the experiment was Tris–HCl (20 mM, pH 7.6), 100 mM of NaCl, MgCl₂ (2 mM), KCl (5 mM), and CaCl₂ (1 mM). The limit of detection (LOD) was calculated to be approximately 1 ng/mL. Full article

Children with intoeing gait are at increased risk of tripping and consequent injury, reduced mobility, and psychological issues. Quantification of tripping is needed outside the gait lab during daily life for improved clinical assessment and treatment evaluation and to enrich the database for artificial intelligence (AI) learning. This paper presents the development of a low-cost, wearable tripping monitor to log a child’s Tripping Hazard Events (THEs) and steps taken during two weeks of everyday activity. A combination of sensors results in a high probability of THE detection, even during rapid gait, while guarding against false positives and minimizing power and therefore monitor size. A THE is logged when the feet come closer than a predefined threshold during the intoeing foot swing phase. Foot proximity is determined by a Radio Frequency Identification (RFID) reader in “sniffer” mode on the intoeing foot and a target of passive Near-Field Communication (NFC) tags on the contralateral foot. A Force Sensitive Resistor (FSR) in the intoeing shoe sets a time window for sniffing during gait and enables step counting. Data are stored in 15 min epochs. Laboratory testing and an IRB-approved human participant study validated system performance and identified the need for improved mechanical robustness, prompting a redesign of the monitor. A custom Python (version 3.10.13)-based Graphical User Interface (GUI) lets clinicians initiate recording sessions and view time records of THEs and steps. The monitor’s flexible design supports broader applications to real-world activity detection. Full article

Forest fires pose significant threats to ecosystems, human life, and the global climate, necessitating rapid and reliable detection systems. Traditional fire detection approaches, including sensor networks, satellite monitoring, and centralized image analysis, often suffer from delayed response, high false positives, and limited deployment in remote areas. Recent deep learning-based methods offer high classification accuracy but are typically computationally intensive and unsuitable for low-power, real-time edge devices. This study presents an autonomous, edge-based forest fire and smoke detection system using a lightweight MobileNetV2 convolutional neural network. The model is trained on a balanced dataset of fire, smoke, and non-fire images and optimized for deployment on resource-constrained edge devices. The system performs near real-time inference, achieving a test accuracy of 97.98% with an average end-to-end prediction latency of 0.77 s per frame (approximately 1.3 FPS) on the Raspberry Pi 5 edge device. Predictions include the class label, confidence score, and timestamp, all generated locally without reliance on cloud connectivity, thereby enhancing security and robustness against potential cyber threats. Experimental results demonstrate that the proposed solution maintains high predictive performance comparable to state-of-the-art methods while providing efficient, offline operation suitable for real-world environmental monitoring and early wildfire mitigation. This approach enables cost-effective, scalable deployment in remote forest regions, combining accuracy, speed, and autonomous edge processing for timely fire and smoke detection. Full article