Combining standoff tomography with point detection: a game changer for the identification of airborne toxic chemicals

鉴定(生物学) 点(几何) 计算机科学 遥感 计算机视觉 人工智能 环境科学 地质学 数学 植物 几何学 生物
作者
Frank Wilsenack,Maria Allers,Fabian Meyer,Thomas Wolf,Torbjörn Tjärnhage,Lars Landström,Arne Ficks
标识
DOI:10.1117/12.3013427
摘要

Volatile chemicals can form expansive toxic gas clouds after an accidental or deliberate large-scale release. The emerging toxic clouds may be invisible to the optical spectrum of the bare eye, but they are generally detectable using suitable standoff or point detectors. Standoff detectors are particularly suited for monitoring a large area within their line of sight, whereas remotely controlled point detectors may be used to survey specific areas of strategic interest. A favorable spatial and temporal detection resolution is usually achieved using standoff Fourier Transform Infrared (FTIR) spectrometers. To obtain a proper spatial resolution beyond a mere imaging view, at least two imaging systems must operate concurrently with an adequate opening angle concerning the distance of reconnaissance. During a field trial in Umeå, Sweden, we utilized an appropriate setup for standoff tomography to detect and identify comparatively small-scale chemical releases of gaseous substances and evaporating aerosols. We reached high resolutions in space and time at a standoff distance of over a kilometer. Thus, we have shown that a targeted early warning and short response times for emerging threats are possible while operators remain at a safe location. Additionally, the field trial revealed the significant influence of the properties and concentration of the deployed chemicals, wind shear, and turbulence on the detection result. In support of spatially and temporally resolved standoff detection, targeted drones carrying fast and sensitive point detectors, such as ion mobility spectrometers, may be used as an orthogonal technique to independently confirm identification.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
yvejune应助胡巴采纳,获得10
刚刚
英俊的铭应助小毕可乐采纳,获得10
1秒前
ZWGS发布了新的文献求助10
1秒前
范啦啦啦发布了新的文献求助10
1秒前
bing完成签到,获得积分10
3秒前
xixia发布了新的文献求助10
3秒前
铭泽发布了新的文献求助10
3秒前
3秒前
脑洞疼应助shor0414采纳,获得10
4秒前
默默的三问完成签到,获得积分10
4秒前
纳兰若微应助younger~采纳,获得10
4秒前
CodeCraft应助云宝采纳,获得10
4秒前
深情安青应助伟伟采纳,获得10
5秒前
pluto应助小周碎碎念采纳,获得30
6秒前
6秒前
英勇涔发布了新的文献求助10
8秒前
深情安青应助lxn采纳,获得30
9秒前
Hello应助ZWGS采纳,获得10
9秒前
10秒前
10秒前
10秒前
10秒前
幸福遥完成签到,获得积分10
10秒前
文轩发布了新的文献求助10
12秒前
小毕可乐发布了新的文献求助10
13秒前
14秒前
zpq发布了新的文献求助30
14秒前
Akim应助yangxt-iga采纳,获得10
15秒前
younger~完成签到,获得积分20
15秒前
123qwe发布了新的文献求助10
15秒前
bing发布了新的文献求助10
16秒前
思源应助夕夕口口采纳,获得10
16秒前
香蕉觅云应助kk采纳,获得10
16秒前
我是老大应助shor0414采纳,获得10
17秒前
淡淡的飞雪应助朴素海亦采纳,获得10
17秒前
18秒前
fleee完成签到,获得积分10
18秒前
牛肉面应助zhangst采纳,获得20
19秒前
科研通AI2S应助失眠觅云采纳,获得10
19秒前
19秒前
高分求助中
Licensing Deals in Pharmaceuticals 2019-2024 3000
Effect of reactor temperature on FCC yield 2000
Very-high-order BVD Schemes Using β-variable THINC Method 1020
Near Infrared Spectra of Origin-defined and Real-world Textiles (NIR-SORT): A spectroscopic and materials characterization dataset for known provenance and post-consumer fabrics 610
Mission to Mao: Us Intelligence and the Chinese Communists in World War II 600
Cognitive Paradigms in Knowledge Organisation 500
Promoting women's entrepreneurship in developing countries: the case of the world's largest women-owned community-based enterprise 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3306889
求助须知:如何正确求助?哪些是违规求助? 2940724
关于积分的说明 8498169
捐赠科研通 2614869
什么是DOI,文献DOI怎么找? 1428544
科研通“疑难数据库(出版商)”最低求助积分说明 663445
邀请新用户注册赠送积分活动 648283