by Keyword: Sensor system
Burgués, J, Esclapez, MD, Doñate, S, Marco, S, (2021). RHINOS: A lightweight portable electronic nose for real-time odor quantification in wastewater treatment plants Iscience 24, 103371 
Quantification of odor emissions in wastewater treatment plants (WWTPs) is key to minimize odor impact to surrounding communities. Odor measurements in WWTPs are usually performed via either expensive and discontinuous olfactometry hydrogen sulfide detectors or via fixed electronic noses. We propose a portable lightweight electronic nose specially designed for real-time odor monitoring in WWTPs using small drones. The so-called RHINOS e-nose allows odor measurements with high spatial resolution, and its accuracy is only slightly worse than that of dynamic olfactometry. The device has been calibrated using odor samples collected in a WWTP in Spain over a period of six months and validated in the same WWTP three weeks after calibration. The promising results obtained support the suitability of the proposed instrument to identify the odor sources having the highest emissions, which may give a useful indication to the plant managers as regards odor control and abatement.© 2021 The Author(s).
JTD Keywords: biofiltration, calibration transfer, chemical sensor arrays, chemistry, drift compensation, engineering, environmental chemical engineering, h2s, model, oxide gas sensors, removal, sensor, system, Chemistry, Engineering, Environmental chemical engineering, Sensor, Sensor system, Variable selection methods
Solorzano, A., Fonollosa, J., Fernandez, L., Eichmann, J., Marco, S., (2017). Fire detection using a gas sensor array with sensor fusion algorithms IEEE Conference Publications 
ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) , IEEE (Montreal, Canada) , 1-3
Conventional fire alarms are based on smoke detection. Nevertheless, in some fire scenarios volatiles are released before smoke. Fire detectors based only on chemical sensors have already been proposed as they may provide faster response, but they are still prone to false alarms in the presence of nuisances. These systems rely heavily on pattern recognition techniques to discriminate fires from nuisances. In this context, it is important to test the systems according to international standards for fires and testing the system against a diversity of nuisances. In this work, we investigate the behavior of a gas sensor array coupled to sensor fusion algorithms for fire detection when exposed to standardized fires and several nuisances. Results confirmed the ability to detect fires (97% Sensitivity), although the system still produces a significant rate of false alarms (35%) for nuisances not presented in the training set.
JTD Keywords: Fire alarm, Gas sensor array, Machine Olfaction, Multisensor system, Sensor fusion
Marco, S., Gutierrez-Galvez, A., (2012). Signal and data processing for machine olfaction and chemical sensing: A review IEEE Sensors Journal 12, (11), 3189-3214
Signal and data processing are essential elements in electronic noses as well as in most chemical sensing instruments. The multivariate responses obtained by chemical sensor arrays require signal and data processing to carry out the fundamental tasks of odor identification (classification), concentration estimation (regression), and grouping of similar odors (clustering). In the last decade, important advances have shown that proper processing can improve the robustness of the instruments against diverse perturbations, namely, environmental variables, background changes, drift, etc. This article reviews the advances made in recent years in signal and data processing for machine olfaction and chemical sensing.
JTD Keywords: Chemical sensors, Electronic nose, Intelligent sensors, Measurement techniques, Sensor arrays, Sensor systems
