Detection of vehicle-based improvised explosives using ultra-trace detection equipment

Fisher, Mark; Sikes, John; Prather, Mark; Wichert, Clint

doi:10.1117/12.606668

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…Prevention and proactive responses to terrorist attacks, criminal activities, and even hazardous chemical accidents require effective detection of explosives and other dangerous materials. Many detection methods are available, from straightforward visual observation to cutting-edge systems, that can identify minute quantities of explosives and their precursors (Sharma et al, 2023;Klapec et al, 2020;Military Aerospace, 2020;Fisher, 2005). The most common method for finding explosives and hazardous materials features X-ray scanners, which produce images of the interiors of bags, packages, and other containers, enabling security officers to inspect suspicious objects or materials visually.…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence technologies utilization for detecting explosive materials

Alshahrani

2024

10.5267/j.ijdns

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Explosive material detection considers the identification and classification of explosive materials using techniques from traditional sniffer dogs to cutting-edge sensing technology like thermal imaging, X-ray scanners, and chemical sensors. Explosive detection is applied in various locations, including airports, government buildings, and public areas, to prevent terrorist attacks and criminal actions that attempt to employ explosive devices. The effectiveness of these procedures is dependent on the detection materials, equipment, and environment, so new techniques are continuously explored to increase precision, sensitivity, and detection speed. Because explosive substances present a critical risk to infrastructure, security, and public safety, extensive analysis of existing detection methods is needed. This paper highlights key areas for further research and development in explosive materials detection by addressing identified limitations and challenges. Specifically, advancements in technology, interdisciplinary collaboration, and the integration of AI techniques offer significant opportunities for improving detection accuracy, reducing false positives, and ensuring safer environments for individuals and society.

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Section: Introductionmentioning

confidence: 99%

Artificial intelligence technologies utilization for detecting explosive materials

Alshahrani

2024

10.5267/j.ijdns

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“…They have recently reported successful detection of simulated vehicleborne ion energy distribution (IED) targets using both vapor and swipe sampling. 12 Cross-reactive chemical sensors using fluorescent polymers with both narrow and broad specificity are being utilized in an artificial olfactory system for land mine detection. 13 These devices rely on the transport of trace vapor, but active air movement can produce detection within a few seconds.…”

Section: Introductionmentioning

confidence: 99%

A portable fluorescence detector for fast ultra trace detection of explosive vapors

Xin

Wang

et al. 2011

Review of Scientific Instruments

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This paper developed a portable detector based on a specific material-based fluorescent sensing film for an ultra trace detection of explosives, such as 2,4,6-trinitrotoluene (TNT) or its derivate 2,4-dinitrotoluene (DNT), in ambient air or on objects tainted by explosives. The fluorescent sensing films are based on single-layer chemistry and the signal amplification effect of conjugated polymers, which exhibited higher sensitivity and shorter response time to TNT or DNT at their vapor pressures. Due to application of the light emitting diode and the solid state photomultiplier and the cross-correlation-based circuit design technology, the device has the advantages of low-power, low-cost, small size, and an improved signal to noise ratio. The results of the experiments showed that the detector can real-time detect and identify of explosive vapors at extremely low levels; it is suitable for the identification of suspect luggage, forensic analyses, or battlefields clearing.

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“…14,15 Current detection methods include gas chromatography-mass spectroscopy (GC-MS), 16 ion mobility spectroscopy (IMS), 17 electrochemistry, 18 canines, 19 and most recently electronic noses. 20,21,22 Although each detection method has advantages, there is still a need for new and improved methods for detecting explosives.…”

Section: Introductionmentioning

confidence: 99%

Fluorescence Detection and Identification of Tagging Agents and Impurities Found in Explosives

et al. 2008

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The detection and identification of 2,4,6-trinitrotoluene (TNT), 1,3,5-trinitro-1,3,5-triazacyclohexane (RDX), and pentaerythritol tetranitrate (PETN) vapors have proven to be difficult and challenging due to the low vapor pressures of these high explosives. Detecting higher vapor pressure impurity compounds found in TNT and possible tagging agents mandated to be added to plastic explosives (RDX and PETN) would allow for easier vapor detection. The higher vapor pressure nitro compounds of interest are considered to be non-fluorescent; however, once reduced to their amino analogs, they have relatively high quantum yields. The standard reduction products, the reduction products obtained in solution, and the reduction products obtained in vapor phase were analyzed by conventional fluorescence, synchronous luminescence, and derivative spectroscopy. The nitro analogs of the isomers 1,3-diaminobenzene, 1,2-diaminobenzene, and 1,4-diaminobenzene are found as impurities in TNT. We provide for the first time the synchronous luminescence derivative spectra of these isomers; including their individual spectra and a spectrum of an isomeric mixture of the three. Using the standard reduction products associated with these isomers and other aromatic amines, our data suggest that the vapors of two signature impurities, 1,3-dinitrobenzene and 2,4-dinitrotoluene (2,4-DNT), minor impurity compounds, and two possible tagging agents, 2-nitrotoluene (2-NT) and 4-nitrotoluene (4-NT), can be detected and selectively identified using our fluorescence approach. To prove our methodology, we show that we were able to generate, collect, and reduce 2-NT, 4-NT, and 2,4-DNT vapors to their amino analogs. Using our fluorescence approach, these vapors could be detected and selectively identified both individually and in a mixture. Collectively, our data indicate that our method of detecting and identifying higher vapor pressure explosive-like compounds could potentially be used to detect and identify low vapor pressure explosives such as TNT, RDX, and PETN.

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Detection of vehicle-based improvised explosives using ultra-trace detection equipment

Cited by 3 publications

References 7 publications

Artificial intelligence technologies utilization for detecting explosive materials

Artificial intelligence technologies utilization for detecting explosive materials

A portable fluorescence detector for fast ultra trace detection of explosive vapors

Fluorescence Detection and Identification of Tagging Agents and Impurities Found in Explosives

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