Biological material detection identification and monitoring: combining point and standoff sensors technologies

Buteau, Sylvie; Rowsell, Susan

doi:10.1117/12.2241133

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…Though standoff distances have been increased continuously for chemical and explosive detection applying mid-infrared laser excitation and photo-acoustic or photo-thermal effects, main applications for bio-detection at large standoff distances seem to be challenging in this wavelength region. Laser-induced fluorescence (LIF) [18][19][20][21][22][23] is commonly used as a standard technique in biological, quantitative and qualitative analyses. In comparison to the techniques above, LIF's main advantage is the combination of high sensitivity and low pulse energies of the exciting laser at low to moderate costs.…”

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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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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show abstract

“…These techniques are able to localize a thread quickly and map the spread of clouds and its propagation, as has been shown in different field trials. Depending on the scenario a promising approach is to combine standoff detectors with point sensors to increase the detection confidence [10].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2018

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In an effort to reduce the potential risk of human exposure to chemical and biological hazardous materials, the demand increases for a detection system which rapidly identifies possible threats from a distance to avoid direct human contact to these materials. In this scope, we present a novel detection system which is able to measure simultaneously spectrally and temporally resolved laser induced fluorescence (LIF) signals excited by two consecutive laser pulses with different central wavelengths at 266 nm and 355 nm. As shown in this paper, the setup enables fast data acquisition that provides a complete dataset in less than a few milliseconds at repetition rates of 100 Hz. Furthermore, with its modular design it can be transported easily for operation at different locations. First measurements indicate a high performance with an accuracy of more than 97% in the distinguishability of bacterial specimen within a limited set of three representative bacterial species, namely Bacillus thuringiensis, Micrococcus luteus and Oligella urethralis. Together with the consecutive classification procedure, the setup promises to become a valuable tool for standoff detection of bio-hazards.

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Biological material detection identification and monitoring: combining point and standoff sensors technologies

Cited by 2 publications

References 2 publications

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

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

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

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