Data set from chemical sensor array exposed to turbulent gas mixtures

A chemical detection platform composed of 8 chemo-resistive gas sensors was exposed to turbulent gas mixtures generated naturally in a wind tunnel. The acquired time series of the sensors are provided. The experimental setup was designed to test gas sensors in realistic environments. Traditionally, chemical detection systems based on chemo-resistive sensors include a gas chamber to control the sample air flow and minimize turbulence. Instead, we utilized a wind tunnel with two independent gas sources that generate two gas plumes. The plumes get naturally mixed along a turbulent flow and reproduce the gas concentration fluctuations observed in natural environments. Hence, the gas sensors can capture the spatio-temporal information contained in the gas plumes. The sensor array was exposed to binary mixtures of ethylene with either methane or carbon monoxide. Volatiles were released at four different rates to induce different concentration levels in the vicinity of the sensor array. Each configuration was repeated 6 times, for a total of 180 measurements. The data is related to "Chemical Discrimination in Turbulent Gas Mixtures with MOX Sensors Validated by Gas Chromatography-Mass Spectrometry", by Fonollosa et al. [1]. The dataset can be accessed publicly at the UCI repository upon citation of [1]: http://archive.ics.uci.edu/ml/datasets/Gas+senso+rarray+exposed+to+turbulent+gas+mixtures.This work has been supported by the California Institute for Telecommunications and Information Technology (CALIT2) under Grant Number 2014 CSRO 136

Electronic Noses and Tongues in Wine Industry

Producción CientíficaThe quality of wines is usually evaluated by a sensory panel formed of trained experts or traditional chemical analysis. Over the last few decades, electronic noses (e-noses) and electronic tongues have been developed to determine the quality of foods and beverages. They consist of arrays of sensors with cross-sensitivity, combined with pattern recognition software, which provide a fingerprint of the samples that can be used to discriminate or classify the samples. This holistic approach is inspired by the method used in mammals to recognize food through their senses. They have been widely applied to the analysis of wines, including quality control, aging control, or the detection of fraudulence, among others. In this paper, the current status of research and development in the field of e-noses and tongues applied to the analysis of wines is reviewed. Their potential applications in the wine industry are described. The review ends with a final comment about expected future developments.CM-P agradece a la Universidad de Valladolid por su beca PIF-UVa y CG-H por su contrato pre-doctoral JCYL (BOCYL-D-24112015-9).Ministerio de Economía, Industria y Competitividad – FEDER (Grant AGL2015-67482-R)Junta de Castilla y León (programa de apoyo a proyectos de investigación - Ref. VA-032U13

Exploiting plume structure to decode gas source distance using metal-oxide gas sensors

Estimating the distance of a gas source is important in many applications of chemical sensing, like e.g. environmental monitoring, or chemically-guided robot navigation. If an estimation of the gas concentration at the source is available, source proximity can be estimated from the time-averaged gas concentration at the sensing site. However, in turbulent environments, where fast concentration fluctuations dominate, comparably long measurements are required to obtain a reliable estimate. A lesser known feature that can be exploited for distance estimation in a turbulent environment lies in the relationship between source proximity and the temporal variance of the local gas concentration – the farther the source, the more intermittent are gas encounters. However, exploiting this feature requires measurement of changes in gas concentration on a comparably fast time scale, that have up to now only been achieved using photo-ionisation detectors. Here, we demonstrate that by appropriate signal processing, off-theshelf metal-oxide sensors are capable of extracting rapidly fluctuating features of gas plumes that strongly correlate with source distance. We show that with a straightforward analysis method it is possible to decode events of large, consistent changes in the measured signal, so-called ‘bouts’. The frequency of these bouts predicts the distance of a gas source in wind-tunnel experiments with good accuracy. In addition, we found that the variance of bout counts indicates cross-wind offset to the centreline of the gas plume. Our results offer an alternative approach to estimating gas source proximity that is largely independent of gas concentration, using off-the-shelf metal-oxide sensors. The analysis method we employ demands very few computational resources and is suitable for low-power microcontrollers

Environmental engineering applications of electronic nose systems based on MOX gas sensors

Nowadays, the electronic nose (e-nose) has gained a huge amount of attention due to its ability to detect and differentiate mixtures of various gases and odors using a limited number of sensors. Its applications in the environmental fields include analysis of the parameters for environmental control, process control, and confirming the efficiency of the odor-control systems. The e-nose has been developed by mimicking the olfactory system of mammals. This paper investigates e-noses and their sensors for the detection of environmental contaminants. Among different types of gas chemical sensors, metal oxide semiconductor sensors (MOXs) can be used for the detection of volatile compounds in air at ppm and sub-ppm levels. In this regard, the advantages and disadvantages of MOX sensors and the solutions to solve the problems arising upon these sensors’ applications are addressed, and the research works in the field of environmental contamination monitoring are overviewed. These studies have revealed the suitability of e-noses for most of the reported applications, especially when the tools were specifically developed for that application, e.g., in the facilities of water and wastewater management systems. As a general rule, the literature review discusses the aspects related to various applications as well as the development of effective solutions. However, the main limitation in the expansion of the use of e-noses as an environmental monitoring tool is their complexity and lack of specific standards, which can be corrected through appropriate data processing methods applications

Drift in a Popular Metal Oxide Sensor Dataset Reveals Limitations for Gas Classification Benchmarks

Funding Information: We thank A. J. Lilienthal, M. Psarrou and S. Sutton for fruitful discussions on multiple occasions, which led to valuable insights. MS was funded by the NSF/CIHR/DFG/FRQ/UKRI-MRC Next Generation Networks for Neuroscience Program (NSF award no. 2014217 , MRC award no. MR/T046759/1 ), and the EU Flagship Human Brain Project SGA3 (H2020 award no. 945539 ). JF acknowledges the Spanish Ministry of Economy and Competitiveness DPI2017-89827-R , Networking Biomedical Research Centre in the subject area of Bioengineering, Biomaterials and Nanomedicine, initiatives of Instituto de Investigación Carlos III, Share4Rare Project (Grant agreement 780262 ), and ACCIÓ (Innotec A CE014/20/000018 ). JF also acknowledges the CERCA Programme/Generalitat de Catalunya and the Serra Húnter Program . B2SLab is certified as 2017 SGR 952. Funding Information: We thank A. J. Lilienthal, M. Psarrou and S. Sutton for fruitful discussions on multiple occasions, which led to valuable insights. MS was funded by the NSF/CIHR/DFG/FRQ/UKRI-MRC Next Generation Networks for Neuroscience Program (NSF award no. 2014217, MRC award no. MR/T046759/1), and the EU Flagship Human Brain Project SGA3 (H2020 award no. 945539). JF acknowledges the Spanish Ministry of Economy and Competitiveness DPI2017-89827-R, Networking Biomedical Research Centre in the subject area of Bioengineering, Biomaterials and Nanomedicine, initiatives of Instituto de Investigaci?n Carlos III, Share4Rare Project (Grant agreement 780262), and ACCI? (Innotec ACE014/20/000018). JF also acknowledges the CERCA Programme/Generalitat de Catalunya and the Serra H?nter Program. B2SLab is certified as 2017 SGR 952. Publisher Copyright: © 2022Metal oxide (MOx) gas sensors are a popular choice for many applications, due to their tunable sensitivity, space efficiency and low cost. Publicly available sensor datasets are particularly valuable for the research community as they accelerate the development and evaluation of novel algorithms for gas sensor data analysis. A dataset published in 2013 by Vergara and colleagues contains recordings from MOx gas sensor arrays in a wind tunnel. It has since become a standard benchmark in the field. Here we report a latent property of this dataset that limits its suitability for gas classification studies. Measurement timestamps show that gases were recorded in separate, temporally clustered batches. Sensor baseline response before gas exposure were strongly correlated with the recording batch, to the extent that baseline response was largely sufficient to infer the gas used in a given trial. Zero-offset baseline compensation did not resolve the issue, since residual short-term drift still contained enough information for gas/trial identification using a machine learning classifier. A subset of the data recorded within a short period of time was minimally affected by drift and suitable for gas classification benchmarking after offset-compensation, but with much reduced classification performance compared to the full dataset. We found 18 publications where this dataset was used without precautions against the circumstances we describe, thus potentially overestimating the accuracy of gas classification algorithms. These observations highlight potential pitfalls in using previously recorded gas sensor data, which may have distorted widely reported results.Peer reviewe

Machine learning methods in electronic nose analysis

The main existent tool to monitor chemical environ- ments in a continuous mode is gas sensor arrays, which have been popularized as electronic noses (enoses). To design and validate these monitoring systems, it is necessary to make use of machine learning techniques to deal with large amounts of heterogeneous data and extract useful information from them. Therefore, enose data present several challenges for each of the steps involved in the design of a machine learning system. Some of the machine learning tasks involved in this area of research include generation of operational patterns, detection anomalies, or classification and discrimination of events. In this work, we will review some of the machine learning approaches adopted in the literature for enose data analysis, and their application to three different tasks: single gas classification under tightly-controlled operating conditions, gas binary mixtures classification in a wind tunnel with two independent gas sources, and human activity monitoring in a NASA spacecraft cabin simulator.Postprint (author's final draft

Application of an array of Metal-Oxide Semiconductor gas sensors in an assistant personal robot for early gas leak detection

This paper proposes the application of a low-cost gas sensor array in an assistant personal robot (APR) in order to extend the capabilities of the mobile robot as an early gas leak detector for safety purposes. The gas sensor array is composed of 16 low-cost metal-oxide (MOX) gas sensors, which are continuously in operation. The mobile robot was modified to keep the gas sensor array always switched on, even in the case of battery recharge. The gas sensor array provides 16 individual gas measurements and one output that is a cumulative summary of all measurements, used as an overall indicator of a gas concentration change. The results of preliminary experiments were used to train a partial least squares discriminant analysis (PLS-DA) classifier with air, ethanol, and acetone as output classes. Then, the mobile robot gas leak detection capabilities were experimentally evaluated in a public facility, by forcing the evaporation of (1) ethanol, (2) acetone, and (3) ethanol and acetone at different locations. The positive results obtained in different operation conditions over the course of one month confirmed the early detection capabilities of the proposed mobile system. For example, the APR was able to detect a gas leak produced inside a closed room from the external corridor due to small leakages under the door induced by the forced ventilation system of the building

Home monitoring for older singles: A gas sensor array system

Many residential environments have been equipped with sensing technologies both to provide assistance to older people who have opted for aging-in-place and to provide information to caregivers and family. However, such technologies are often accompanied by physical discomfort, privacy concerns, and complexity of use. We explored the feasibility of monitoring home activity using chemical sensors that pose fewer privacy concerns than, for example, video-cameras and which do not suffer from blind spots. We built a monitoring device that integrates a sensor array and IoT capabilities to gather the necessary data about a resident in his/her living space. Over a period of 3 months, we uninterruptedly measured the living space of a typical elder person living on his/her own. To record the level of activity during the same period and obtain a ground truth for the activity, a set of motion sensors were also deployed in the house. Home activity was extracted from a PCA space moving-window which translated sensor data into the event space; this also compensated for environmental and sensor drift. Our results show that it is possible to monitor the person’s home activity and detect sudden deviations from it using a low-cost, non-invasive, system based on gas sensors that gather data on the air composition in the living space. We made the dataset publicly available at https://archive.ics.uci.edu/ml/index.php2.This work was supported by the Spanish Ministry of Economy and Competitiveness (www.mineco.gob.es) PID2021-122952OB-I00, DPI2017-89827-R, Networking Biomedical Research Centre in the subject area of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), initiatives of Instituto de Investigación Carlos III (ISCIII), Share4Rare project (Grant Agreement 780262), ISCIII (grant AC22/00035), ACCIÓ (grant Innotec ACE014/20/000018) and Pla de Doctorats Industrials de la Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya (2022 DI 014), and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie (grant No. 101029808). JF also acknowledges the CERCA Program/Generalitat de Catalunya and the Serra Húnter Program. B2SLab is certified as 2017 SGR 952.Peer ReviewedPostprint (author's final draft

Methane oxidation and emission in Lake Lugano (Southern Switzerland) : a lipid biomarker and isotopic approach

Methane is an important greenhouse gas in Earth's atmosphere. The sources of atmospheric methane are largely biogenic, being produced under anoxic conditions by methanogenic Archaea. Wetlands, which include lakes, are important contributors to the atmospheric methane budget, since they commonly feature anoxic sediments or bottom water. Methane oxidising bacteria at the interface between oxic and anoxic sediments and water limit the efflux of methane. Furthermore, in the oceans, methane is oxidised anaerobically by Archaea, in a process coupled to sulfate reduction. In freshwater environments, where sulfate concentrations are orders of magnitude lower, this process is not thermodynamically favourable, and archaeal anaerobic oxidation of methane is often absent. It has been proposed in certain lake environments, however, that anaerobic oxidation of methane does take place. One lake in which anaerobic oxidation of methane was proposed is the northern basin of Lake Lugano, southern Switzerland. Anaerobic oxidation of methane in this basin is explored in chapter 2 of this PhD thesis. Indeed we found methane concentration and carbon isotopic composition profiles characteristic of methane oxidation in the anoxic hypolimnion, more than 30 m below the interface between the oxic and anoxic waters. In addition, microbial biomass at these depths showed carbon isotope signatures of methane-derived carbon (d13C-values as low as -70‰ in C16:1 fatty acids), indicating that methane is used as a carbon source. However, no methane oxidation took place in incubation experiments under anoxic conditions. Addition of alternative potential electron acceptors did not stimulate methane oxidation, and methane oxidation was only observed in the presence of oxygen. Instead, we propose that episodic introduction of oxygenated water into the anoxic hypolimnion sustains a community of aerobic methanotrophs. Carbon derived from methane oxidation has been shown in several studies to constitute an important carbon input to aquatic ecosystems. In the studies reported in chapters 2 and 3, compound specific stable carbon isotope analysis of lipid biomarkers was used to trace methane-derived carbon through the ecosystems at redox interfaces and in the anoxic hypolimnion of Lake Lugano. In the monomictic southern basin (chapter 3), an anoxic benthic nepheloid layer develops during the period of water column stratification. This layer was found to be derived from microbial production in the hypolimnion. Methane oxidising bacteria constituted up to 30% of total microbial cell numbers in the nepheloid layer, and 77% to 96% of the organic carbon in this layer was methane-derived. High rates of aerobic methane oxidation at the top of the anoxic nepheloid layer led to an oxygen consumption that was greater than the downward diffusion, causing the anoxic nepheloid layer to expand. Bacterial aerobic methanotrophs migrate upwards through the water column with the interface between the oxic hypolimnion and the anoxic nepheloid layer. The extent of emission of methane to the atmosphere depends on the totality of sinks and sources in the lake basin. In both the northern and the southern basin of Lake Lugano, large amounts of methane are emitted from the sediments into the bottom water. However, consumption by aerobic methanotrophs at the oxic-anoxic redoxcline is near complete, and during stratified conditions, no methane escapes to the epilimnion. On the other hand, methane super-saturation in the surface water was observed throughout the year. Chapter 4 describes the results of three mapping campaigns of surface water methane concentrations in the northern basin of Lake Lugano, in spring and autumn. Additionally, methane concentration and carbon isotopic composition were measured on depth profiles down to 40 m depth in transects across the lake basin. Methane fluxes to the atmosphere were calculated from surface water concentration and wind speed. At a standardised wind speed of 1.6 m s-1 (average wind speed during the period from May until October) fluxes to the atmosphere were significantly higher in autumn (44 and 97 micromol m-2 d-1 in October 2011 and October 2012, respectively) than in spring (7 micromol m-2 d-1, May 2012). This difference is in part due to higher concentrations in autumn than in spring, and in part a result of a stronger dependence of the transfer velocity on buoyancy flux when the surface water cools. The source of methane in the surface water could not be determined with certainty. It is possible that internal waves at the thermocline induce friction at the sediment-water interface in the littoral zone, which leads to increased outgassing of sedimentary methane. However, the northern basin of Lake Lugano has steep shores along large parts of the basin, which offer little space for deposition of sediments, and the possibility of in situ production of methane in the water column must be considered