Search Results (153)

Low-cost miniaturized gas sensors are increasingly considered for outdoor air quality monitoring, yet their performance under real-world environmental conditions remains insufficiently characterized. This work evaluates the dynamic gas response of the Bosch BME688 sensor, whose metal oxide sensing layer is based on tin dioxide (SnO₂) material, focusing on its sensitivity, selectivity, and dynamic response to four representative air pollutants: nitrogen dioxide (NO₂), carbon monoxide (CO), sulfur dioxide (SO₂), and isobutylene. This study provides both quantitative performance metrics and a physicochemical interpretation of the sensing mechanism. Controlled experiments were conducted in a custom test chamber to facilitate the precise regulation of temperature, humidity, and gas concentrations in the ppm to sub-ppm range. Despite large variability in the baseline resistance across devices, normalization yields consistent behavior, enabling cross-sensor comparability. The results show that the optimum operating temperatures fall in the range of 360–400 °C, where response and recovery times are reduced to a few minutes, compatible with mobile sensing requirements. Moreover, humidity strongly influences sensor behavior: it generally decreases sensitivity but improves kinetics, and in the case of CO, it enables enhanced responses through additional hydroxyl-mediated pathways. These findings confirm the feasibility of deploying BME688 sensors in distributed outdoor monitoring platforms, provided that humidity and temperature effects are properly addressed through calibration or compensation strategies. In addition, the variability observed in baseline resistance highlights the need for normalization and, consequently, individual calibration steps for each sensor under reference conditions in order to ensure cross-sensor comparability. The findings provided in this study provide support for the design of robust, low-cost air monitoring networks. Full article

This study evaluates the application of an electronic nose (E-nose) system as a non-destructive tool for the early detection of Monilinia laxa infection in yellow nectarines (Prunus persica var. nectarine, cv. “Kinolea”) through the analysis of volatile organic compounds (VOCs). Two experimental groups were established: a control group of healthy fruit and a treatment group inoculated with the pathogen. The VOCs emitted by both groups were identified and quantified using gas chromatography-mass spectrometry (GC-MS). Simultaneously, the responses of the E-nose were recorded at three critical stages of fungal development: early, intermediate, and advanced. The electronic nose used consists of a set of 11 commercial metal oxide semiconductor (MOX) sensors. The signals from these sensors showed a strong correlation with the VOC profiles associated with fungal deterioration. Linear discriminant analysis (LDA) models based on E-nose data successfully distinguished between healthy and infected samples with 97% accuracy. Furthermore, the system accurately classified samples into three stages of contamination—control, early infection, and advanced infection—with 96% classification accuracy. These findings demonstrate that E-nose technology is an effective, rapid, and non-invasive method for the real-time monitoring of post-harvest fungal contamination in nectarines, offering significant potential for improving quality control during storage and distribution. Full article

Metal oxide semiconductor (MOX) sensors are emerging as a groundbreaking technology due to their remarkable features: high sensitivity, rapid response time, low cost, and potential for miniaturization. Their ability to detect volatile organic compounds (VOCs) in real time makes them ideal tools for applications across various fields, including environmental monitoring, medicine, and the food industry. This paper explores the evolution and growing utilization of MOX sensors, with a particular focus on atmospheric pollution monitoring, non-invasive disease diagnostics through the analysis of volatile compounds emitted by the human body, and food quality assessment. The crucial role of MOX sensors in monitoring the freshness of food and water, detecting chemical and biological contamination, and identifying food fraud is specifically examined. The rapid advancement of this technology offers new opportunities to improve quality of life, food safety, and public health, positioning MOX sensors as a key tool to address future challenges in these vital sectors. Full article

The quantification of methane concentrations in air is essential for the quantification of methane emissions, which in turn is necessary to determine absolute emissions and the efficacy of emission mitigation strategies. These are essential if countries are to meet climate goals. Large-scale deployment of methane analyzers across millions of emission sites is prohibitively expensive, and lower-cost instrumentation has been recently developed as an alternative. Currently, it is unclear how cheaper instrumentation will affect measurement resolution or accuracy. To test this, the Wireless Autonomous Transportable Methane Emission Reporting System (WATCH₄ERS) has been developed, comprising four commercially available sensing technologies: metal oxide (MOx,), Non-dispersion Infrared (NDIR), integrated infrared (INIR), and tunable diode laser absorption spectrometer (TDLAS). WATCHERS is the accumulated knowledge of several long-term methane measurement projects at Colorado State University’s Methane Emission Technology Evaluation Center (METEC), and this study describes the integration of these sensors into a single unit and reports initial instrument response to calibration procedures and controlled release experiments. Specifically, this paper aims to describe the development of the WATCH₄ERS unit, report initial sensor responses, and describe future research goals. Meanwhile, future work will use data gathered by multiple WATCH₄ERS units to 1. better understand the cost–benefit balance of methane sensors, and 2. identify how decreasing instrumentation costs could increase deployment coverage and therefore inform large-scale methane monitoring strategies. Both calibration and response experiments indicate the INIR has little practical use for measuring methane concentrations less than 500 ppm. The MOx sensor is shown to have a logarithmic response to methane concentration change between background and 600 ppm but it is strongly suggested that passively sampling MOx sensors cannot respond fast enough to report concentrations that change in a sub-minute time frame. The NDIR sensor reported a linear change to methane concentration between background and 600 ppm, although there was a noticeable lag in reporting changing concentration, especially at higher values, and individual peaks could be observed throughout the experiment even when the plumes were released 5 s apart. The TDLAS sensor reported all changes in concentration but remains prohibitively expensive. Our findings suggest that each sensor technology could be optimized by either operational design or deployment location to quantify methane emissions. The WATCH₄ERS units will be deployed in real-world environments to investigate the utility of each in the future. Full article

Gouda-type cheese originated in the Netherlands, but is now produced all over the world. Analogue cheeses are cheese-like products with a lower price level that are based on non-dairy fats and proteins. The market demand for analogue cheese is currently also growing due to customers’ preference for low-fat foods. In this report, samples of Gouda-type cheese and its analogues produced by a dairy cooperative (Warmian-Masurian Voivodeship, Poland) were used as the subject of analysis; their volatile profiles were analyzed by gas chromatography coupled with mass spectrometry (GC-MS). In addition, measurements were carried out using a low-cost electronic nose based on MOX sensors. The results showed a richer chemical composition of the cheese volatiles compared to the analogue product. The measurements with the electronic nose made it possible to differentiate between the sample categories but also revealed similarities between them. The research demonstrated that both methods could be used for the assessment of the volatile profiles of the products. Full article

ZnO/MO_x (M = Fe^III, Co^II,III, Ni^II, Sn^IV, In^III, Ga^III; [M]/([Zn] + [M]) = 15 mol%) nanofiber heterostructures were obtained by co-electrospinning and characterized by X-ray diffraction, scanning electron microscopy and X-ray fluorescence spectroscopy. The sensor properties of ZnO and ZnO/MO_x nanofibers were studied toward reducing gases CO (20 ppm), methanol (20 ppm), acetone (20 ppm), and oxidizing gas NO₂ (1 ppm) in dry air. It was demonstrated that the temperature of the maximum sensor response of ZnO/MO_x nanofibers toward reducing gases is primarily influenced by the binding energy of chemisorbed oxygen with the surface of the modifier’s oxides. When detecting oxidizing gas NO₂, high sensitivity at a low measurement temperature can be achieved with a high concentration of free electrons in the near-surface layer of zinc oxide grains, which is determined by the band bending at the ZnO/MO_x interface characterized by the difference in the electron work function of ZnO and MO_x. Full article

Background/Objectives: Measuring the physical functioning of older hip fracture patients using wearables is desirable, with physical activity monitoring offering a promising approach. However, it is first important to assess physical activity in healthy older adults. This study quantifies physical functioning with physical activity parameters and assesses those parameters in community-dwelling older adults. The results are compared with the results from one case participant 2 months post-hip fracture surgery. Methods: Twenty-four community-dwelling older adults (aged ≥ 80) participated. The acts of moving around the house, toileting, getting in/out of bed, and preparing meals was quantified by total time, time spent sitting, standing, and walking, number of transfers, and intensity of physical activity. MOX and APDM sensors measured the intensity of physical activity, with the tasks performed in a living lab while video-recorded. The case participant’s total time and intensity of physical activity were measured for walking to a door and getting in/out of bed. Results: Preparing meals showed the longest total time and time spent standing/walking, while moving around the house and getting in/out of bed had the highest intensity of physical activity. Only getting in/out of bed required sitting. The physical activity parameters varied among participants, with very active participants completing tasks faster. The case participant had longer total times and lower intensities of physical activity two months post-surgery compared to before the fracture. Conclusions: This study provides initial insights into the physical activity levels of community-dwelling older adults. It represents the beginning of more efficient and continuous monitoring of physical functioning. Full article

Active mobility and light vehicles, such as e-bikes, are gaining increasing attention as sustainable transportation alternatives to internal combustion solutions. In this context, collecting comprehensive data on environmental conditions, vehicle performance, and user interaction is crucial for improving system efficiency and user experience. This paper presents a data acquisition system designed to collect data from multiple sensor platforms. The architecture is optimized to maintain low power consumption and operate within limited computational resources, making it suitable for real-time data acquisition on light vehicles. To achieve this, a data acquisition module was developed using a single-board computer integrated with a custom shield, which also captures data related to the assistance of an e-bike motor through a wireless interface. The paper provides an in-depth discussion of the architecture and software development, along with a detailed overview of the sensors used. A demonstrator was created to verify the system architecture idea and prove the potentialities of the system overall. The demonstrator has been qualified by professional and semi-professional riders in the framework of the Giro-E, a cyclist event which took place in May 2024, on the same roads of the Giro d’Italia. Finally, some preliminary analyses on the data acquired are provided to show the performance of the system, particularly in reconstructing the user behavior, the environmental parameters, and the type of road. Full article

Accurately obtaining a patient’s respiratory rate is crucial for promptly identifying any sudden changes in their condition during emergencies. Typically, the respiratory rate is assessed through a combination of impedance change measurements and electrocardiography (ECG). However, impedance measurements are prone to interference from body movements. Conversely, a capnometer coupled with a ventilator offers a method of measuring the respiratory rate that is unaffected by body movements. However, capnometers are mainly used to evaluate respiration when using a ventilator or an Ambu bag by measuring the CO₂ concentration at the breathing circuit, and they are not used only to measure the respiratory rate. Furthermore, capnometers are not suitable as wearable devices because they require intubation or a mask that covers the nose and mouth to prevent air leaks during the measurement. In this study, we developed a reliable system for measuring the respiratory rate utilizing a small wearable MOx sensor that is unaffected by body movements and not connected to the breathing circuit. Subsequently, we conducted experimental assessments to gauge the accuracy of the rate estimation achieved by the system. In order to avoid the effects of abnormal states on the estimation accuracy, we also evaluated the classification performance for distinguishing between normal and abnormal respiration using a one-class SVM-based approach. The developed system achieved 80% for both true positive and true negative rates. Our experimental findings reveal that the respiratory rate can be precisely determined without being influenced by body movements. Full article

Humidity is a well-known interference factor in metal oxide (MOX) gas sensors, significantly impacting their performance in various applications such as environmental monitoring and medical diagnostics. This study investigates the effects of adsorbed water on MOX conductivity using two different materials: pure tin oxide (SnO₂) and a tin–titanium–niobium oxide mixture (SnTiNb)_xO₂ (STN). The results reveal that (SnTiNb)_xO₂ sensors exhibit reduced sensitivity to humidity compared to pure tin oxide, rendering them more suitable for applications where humidity presence is critical. We aimed to shed light on a still controversial debate over the mechanisms involved in the water surface interactions for the aforementioned materials also by exploring theoretical studies in the literature. Experimental analysis involves varying temperatures (100 to 800 °C) to understand the kinetics of surface reactions. Additionally, a brief high-temperature heating method is demonstrated to effectively remove adsorbed humidity from sensor surfaces. The study employs Arrhenius-like plots for graphical interpretation, providing insights into various water adsorption/desorption phenomena. Overall, this research contributes to a deeper understanding of the role of humidity in MOX gas sensor mechanisms and offers practical insights for sensor design and optimization. Full article

Incorporating insect meals into poultry diets has emerged as a sustainable alternative to conventional feed sources, offering nutritional, welfare benefits, and environmental advantages. This study aims to monitor and compare volatile compounds emitted from raw poultry carcasses and subsequently from cooked chicken pieces from animals fed with different diets, including the utilization of insect-based feed ingredients. Alongside the use of traditional analytical techniques, like solid-phase microextraction combined with gas chromatography-mass spectrometry (SPME-GC-MS), to explore the changes in VOC emissions, we investigate the potential of S3+ technology. This small device, which uses an array of six metal oxide semiconductor gas sensors (MOXs), can differentiate poultry products based on their volatile profiles. By testing MOX sensors in this context, we can develop a portable, cheap, rapid, non-invasive, and non-destructive method for assessing food quality and safety. Indeed, understanding changes in volatile compounds is crucial to assessing control measures in poultry production along the entire supply chain, from the field to the fork. Linear discriminant analysis (LDA) was applied using MOX sensor readings as predictor variables and different gas classes as target variables, successfully discriminating the various samples based on their total volatile profiles. By optimizing feed composition and monitoring volatile compounds, poultry producers can enhance both the sustainability and safety of poultry production systems, contributing to a more efficient and environmentally friendly poultry industry. Full article

Noxious gases such as sulfur-containing compounds can inflict several different adverse effects on human health even when present at extremely low concentrations. The accurate detection of these gases at sub-parts per million levels is imperative, particularly in fields where maintaining optimal air quality is crucial. In this study, we harnessed the capabilities of nanostructured metal-oxide semiconducting materials to detect sulfur dioxide, since they have been extensively explored starting from the last decades for their effectiveness in monitoring toxic gases. We systematically characterized the sensing performance of seven chemoresistive devices. As a result, the SnO₂:Au sensor demonstrated to be the most promising candidate for sulfur dioxide detection, owing to its highly sensitivity (0.5–10 ppm), humidity-independent behavior (30 RH% onwards), and selectivity vs. different gases at an operating temperature of 400 °C. This comprehensive investigation facilitates a detailed performance comparison to other devices explored for the SO₂ sensing, supporting advancements in gas detection technology for enhanced workplace and environmental safety. Full article

New process developments linked to Power to X (energy storage or energy conversion to another form of energy) require tools to perform process monitoring. The main gases involved in these types of processes are H₂, CO, CH₄, and CO₂. Because of the non-selectivity of the sensors, a multi-sensor matrix has been built in this work based on commercial sensors having very different transduction principles, and, therefore, providing richer information. To treat the data provided by the sensor array and extract gas mixture composition (nature and concentration), linear (Multi Linear Regression—Ordinary Least Square “MLR-OLS” and Multi Linear Regression—Partial Least Square “MLR-PLS”) and non-linear (Artificial Neural Network “ANN”) models have been built. The MLR-OLS model was disqualified during the training phase since it did not show good results even in the training phase, which could not lead to effective predictions during the validation phase. Then, the performances of MLR-PLS and ANN were evaluated with validation data. Good concentration predictions were obtained in both cases for all the involved analytes. However, in the case of methane, better prediction performances were obtained with ANN, which is consistent with the fact that the MOX sensor’s response to CH₄ is logarithmic, whereas only linear sensor responses were obtained for the other analytes. Finally, prediction tests performed on one-year aged sensor platforms revealed that PLS model predictions on aged platforms mainly suffered from concentration offsets and that ANN predictions mainly suffered from a drop of sensitivity. Full article

Light and active mobility, as well as multimodal mobility, could significantly contribute to decarbonization. Air quality is a key parameter to monitor the environment in terms of health and leisure benefits. In a possible scenario, wearables and recharge stations could supply information about a distributed monitoring system of air quality. The availability of low-power, smart, low-cost, compact embedded systems, such as Arduino Nicla Sense ME, based on BME688 by Bosch, Reutlingen, Germany, and powered by suitable software tools, can provide the hardware to be easily integrated into wearables as well as in solar-powered EVSE (Electric Vehicle Supply Equipment) for scooters and e-bikes. In this way, each e-vehicle, bike, or EVSE can contribute to a distributed monitoring network providing real-time information about micro-climate and pollution. This work experimentally investigates the capability of the BME688 environmental sensor to provide useful and detailed information about air quality. Initial experimental results from measurements in non-controlled and controlled environments show that BME688 is suited to detect the human-perceived air quality. CO₂ readout can also be significant for other gas (e.g., CO), while IAQ (Index for Air Quality, from 0 to 500) is heavily affected by relative humidity, and its significance below 250 is quite low for an outdoor uncontrolled environment. Full article

Certain biomarkers in exhaled breath are indicators of diseases in the human body. The non-invasive detection of such biomarkers in human breath increases the demand for simple and cost-effective gas sensors to replace state-of-the-art gas chromatography (GC) machines. The use of metal oxide (MOX) gas sensors based on thin-film structures solves the current limitations of breath detectors. However, the response at high humidity levels, i.e., in the case of exhaled human breath, significantly decreases the sensitivity of MOX sensors, making it difficult to detect small traces of biomarkers. We have introduced, in previous work, the concept of a hybrid gas sensor, in which thin-film-based MOX gas sensors are combined with an ultra-thin (20–30 nm) polymer top layer deposited by solvent-free initiated chemical vapor deposition (iCVD). The hydrophobic top layer enables sensor measurement in high-humidity conditions as well as the precise tuning of selectivity and sensitivity. In this paper, we present a way to increase the hydrogen (H₂) sensitivity of hybrid sensors through chemical modification of the polymer top layer. A poly(1,3,5,7-tetramethyl-tetravinylcyclotetrasiloxane) (PV4D4) thin film, already applied in one of our previous studies, is transformed into a silsesquioxane-containing top layer by a simple heating step. The transformation results in a significant increase in the gas response for H₂ ~709% at an operating temperature of 350 °C, which we investigate based on the underlying sensing mechanism. These results reveal new pathways in the biomedical application field for the analysis of exhaled breath, where H₂ indicates gastrointestinal diseases. Full article