Novel standoff detection system for the classification of chemical and biological hazardous substances combining temporal and spectral laser-induced fluorescence techniques⋆

Gebert, Florian; Kraus, Marian; Fellner, Lea; Walter, Arne; Pargmann, Carsten; Grünewald, Karin; Duschek, Frank

doi:10.1140/epjp/i2018-12147-2

Cited by 18 publications

(11 citation statements)

References 16 publications

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“…Further work will focus on improving the sensor to provide additional information on pathogen type, thus allowing the mitigation strategy to be appropriately optimized. Laser-induced fluorescence 25 is promising for this purpose. The on-board algorithm for deploying the mitigation technique can also be improved.…”

Section: Discussionmentioning

confidence: 99%

A smart mask for active defense against airborne pathogens

Kalavakonda

Masna

Mandal

et al. 2021

Sci Rep

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Face masks are a primary preventive measure against airborne pathogens. Thus, they have become one of the keys to controlling the spread of the COVID-19 virus. Common examples, including N95 masks, surgical masks, and face coverings, are passive devices that minimize the spread of suspended pathogens by inserting an aerosol-filtering barrier between the user’s nasal and oral cavities and the environment. However, the filtering process does not adapt to changing pathogen levels or other environmental factors, which reduces its effectiveness in real-world scenarios. This paper addresses the limitations of passive masks by proposing ADAPT, a smart IoT-enabled “active mask”. This wearable device contains a real-time closed-loop control system that senses airborne particles of different sizes near the mask by using an on-board particulate matter (PM) sensor. It then intelligently mitigates the threat by using mist spray, generated by a piezoelectric actuator, to load nearby aerosol particles such that they rapidly fall to the ground. The system is controlled by an on-board micro-controller unit that collects sensor data, analyzes it, and activates the mist generator as necessary. A custom smartphone application enables the user to remotely control the device and also receive real-time alerts related to recharging, refilling, and/or decontamination of the mask before reuse. Experimental results on a working prototype confirm that aerosol clouds rapidly fall to the ground when the mask is activated, thus significantly reducing PM counts near the user. Also, usage of the mask significantly increases local relative humidity levels.

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Section: Discussionmentioning

confidence: 99%

A smart mask for active defense against airborne pathogens

Kalavakonda

Masna

Mandal

et al. 2021

Sci Rep

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“…The laser system in Figure was described in detail in a previous work, so only a short summary of the main components is presented here. LIF is excited by frequency converted laser pulses of a Nd:YAG laser (InnoLas Picolo Magna EVO III) with wavelengths of 266 and 355 nm, pulse widths of 0.7 ns (FWHM), and a repetition rate of 100 pulses per second.…”

Section: Methodsmentioning

confidence: 99%

Online discrimination of chemical substances using standoff laser‐induced fluorescence signals

Kraus

Gebert

Walter

et al. 2019

Journal of Chemometrics

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Chemical contamination of objects and surfaces, caused by accident or on purpose, is a common security issue. Immediate countermeasures depend on the class of risk and consequently on the characteristics of the substances.Laser-based standoff detection techniques can help to provide information about the thread without direct contact of humans to the hazardous materials.This article explains a data acquisition and classification procedure for laserinduced fluorescence spectra of several chemical agents. The substances are excited from a distance of 3.5 m by laser pulses of two UV wavelengths (266 and 355 nm) with less than 0.1 mJ per laser pulse and a repetition rate of 100 Hz. Each pair of simultaneously emitted laser pulses is separated using an optical delay line. Every measurement consists of a dataset of 100 spectra per wavelength containing the signal intensities in the spectral range from 250 to 680 nm, recorded by a 32-channel photo multiplying tube array. Based on this dataset, three classification algorithms are trained which can distinguish the samples by their single spectra with an accuracy of over 98%. These predictive models, generated with decision trees, support vector machines, and neural networks, can identify all agents (eg, benzaldehyde, isoproturon, and piperine) within the current set of substances.

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“…Following a development by Gebert et al [29], this work aims at including simultaneous measurements of fluorescence lifetimes into acquired spectral data sets. Recent results acquired with an improved setup [29] The evaluation of the data focuses on additional information gain from these time-dependent fluorescence measurements of biological agents and an improvement of the classification of the substance level.…”

Section: Introductionmentioning

confidence: 99%

Multispectral LIF-Based Standoff Detection System for the Classification of CBE Hazards by Spectral and Temporal Features

Fellner

Kraus

Gebert

et al. 2020

Sensors

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Laser-induced fluorescence (LIF) is a well-established technique for monitoring chemical processes and for the standoff detection of biological substances because of its simple technical implementation and high sensitivity. Frequently, standoff LIF spectra from large molecules and bio-agents are only slightly structured and a gain of deeper information, such as classification, let alone identification, might become challenging. Improving the LIF technology by recording spectral and additionally time-resolved fluorescence emission, a significant gain of information can be achieved. This work presents results from a LIF based detection system and an analysis of the influence of time-resolved data on the classification accuracy. A multi-wavelength sub-nanosecond laser source is used to acquire spectral and time-resolved data from a standoff distance of 3.5 m. The data set contains data from seven different bacterial species and six types of oil. Classification is performed with a decision tree algorithm separately for spectral data, time-resolved data and the combination of both. The first findings show a valuable contribution of time-resolved fluorescence data to the classification of the investigated chemical and biological agents to their species level. Temporal and spectral data have been proven as partly complementary. The classification accuracy is increased from 86% for spectral data only to more than 92%.

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Novel standoff detection system for the classification of chemical and biological hazardous substances combining temporal and spectral laser-induced fluorescence techniques⋆

Cited by 18 publications

References 16 publications

A smart mask for active defense against airborne pathogens

A smart mask for active defense against airborne pathogens

Online discrimination of chemical substances using standoff laser‐induced fluorescence signals

Multispectral LIF-Based Standoff Detection System for the Classification of CBE Hazards by Spectral and Temporal Features

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