{"title":"Holographic Air-quality Monitor (HAM)","authors":"Nicholas Bravo-Frank, Lei Feng, Jiarong Hong","doi":"arxiv-2409.04435","DOIUrl":null,"url":null,"abstract":"We introduce the holographic air-quality monitor (HAM) system, uniquely\ntailored for monitoring large particulate matter (PM) over 10 um in diameter,\ni.e., particles critical for disease transmission and public health but\noverlooked by most commercial PM sensors. The HAM system utilizes a lensless\ndigital inline holography (DIH) sensor combined with a deep learning model,\nenabling real-time detection of PMs, with greater than 97% true positive rate\nat less than 0.6% false positive rate, and analysis of PMs by size and\nmorphology at a sampling rate of 26 liters per minute (LPM), for a wide range\nof particle concentrations up to 4000 particles/L. Such throughput not only\nsignificantly outperforms traditional imaging-based sensors but also rivals\nsome lower-fidelity, non-imaging sensors. Additionally, the HAM system is\nequipped with additional sensors for smaller PMs and various air quality\nconditions, ensuring a comprehensive assessment of indoor air quality. The\nperformance of the DIH sensor within the HAM system was evaluated through\ncomparison with brightfield microscopy, showing high concordance in size\nmeasurements. The efficacy of the DIH sensor was also demonstrated in two\ntwo-hour experiments under different environments simulating practical\nconditions with one involving distinct PM-generating events. These tests\nhighlighted the HAM system's advanced capability to differentiate PM events\nfrom background noise and its exceptional sensitivity to irregular, large-sized\nPMs of low concentration.","PeriodicalId":501374,"journal":{"name":"arXiv - PHYS - Instrumentation and Detectors","volume":"279 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Instrumentation and Detectors","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.04435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We introduce the holographic air-quality monitor (HAM) system, uniquely
tailored for monitoring large particulate matter (PM) over 10 um in diameter,
i.e., particles critical for disease transmission and public health but
overlooked by most commercial PM sensors. The HAM system utilizes a lensless
digital inline holography (DIH) sensor combined with a deep learning model,
enabling real-time detection of PMs, with greater than 97% true positive rate
at less than 0.6% false positive rate, and analysis of PMs by size and
morphology at a sampling rate of 26 liters per minute (LPM), for a wide range
of particle concentrations up to 4000 particles/L. Such throughput not only
significantly outperforms traditional imaging-based sensors but also rivals
some lower-fidelity, non-imaging sensors. Additionally, the HAM system is
equipped with additional sensors for smaller PMs and various air quality
conditions, ensuring a comprehensive assessment of indoor air quality. The
performance of the DIH sensor within the HAM system was evaluated through
comparison with brightfield microscopy, showing high concordance in size
measurements. The efficacy of the DIH sensor was also demonstrated in two
two-hour experiments under different environments simulating practical
conditions with one involving distinct PM-generating events. These tests
highlighted the HAM system's advanced capability to differentiate PM events
from background noise and its exceptional sensitivity to irregular, large-sized
PMs of low concentration.