Developing a Smartphone Software Package for Predicting Atmospheric Pollutant Concentrations at Mobile Locations

Larkin, Andrew; Williams, David E.; Kile, Molly L.; Baird, William M.

doi:10.1093/comjnl/bxu067

Cited by 14 publications

(8 citation statements)

References 12 publications

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“…Phones offer a broad range of uses, in addition to staying in touch with loved ones, games, or connecting to the world through the Internet. They offer selfmonitoring applications, including personal health tracking (27)(28)(29)(30)(31)(32), environmental exposures (33,34), and weather monitoring, and therefore we spend a lot of time on our phones. New applications increase the amount of time we spend on our phones (in part because this is an explicit goal of many application developers).…”

mentioning

confidence: 99%

Lifestyle chemistries from phones for individual profiling

Bouslimani

Melnik

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Imagine a scenario where personal belongings such as pens, keys, phones, or handbags are found at an investigative site. It is often valuable to the investigative team that is trying to trace back the belongings to an individual to understand their personal habits, even when DNA evidence is also available. Here, we develop an approach to translate chemistries recovered from personal objects such as phones into a lifestyle sketch of the owner, using mass spectrometry and informatics approaches. Our results show that phones' chemistries reflect a personalized lifestyle profile. The collective repertoire of molecules found on these objects provides a sketch of the lifestyle of an individual by highlighting the type of hygiene/beauty products the person uses, diet, medical status, and even the location where this person may have been. These findings introduce an additional form of trace evidence from skin-associated lifestyle chemicals found on personal belongings. Such information could help a criminal investigator narrowing down the owner of an object found at a crime scene, such as a suspect or missing person.skin | phones | lifestyle chemistries | trace evidence

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mentioning

confidence: 99%

Lifestyle chemistries from phones for individual profiling

Bouslimani

Melnik

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…Wearable sensors/monitors integrated into different mobile or electronic devices (including Global Positioning System-enabled models) [119][120][121] may be a cost-effective way to determine air pollution levels and potential risk at the individual level [122,123]. A software program using smartphone technology coupled with predictive environmental air pollution models provided personal exposures to air pollution and calculated health risks [124]. Affordable access to such devices (and associated data) can lend a sense of empowerment that may motivate protective behaviour [125].…”

Section: Background and Evidencementioning

confidence: 99%

Personal strategies to minimise effects of air pollution on respiratory health: advice for providers, patients and the public

Salvi²,

et al. 2020

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As global awareness of air pollution rises, so does the imperative to provide evidence-based recommendations for strategies to mitigate its impact. While public policy has a central role in reducing air pollution, exposure can also be reduced by personal choices. Qualified evidence supports limiting physical exertion outdoors on high air pollution days and near air pollution sources, reducing near-roadway exposure while commuting, utilising air quality alert systems to plan activities, and wearing facemasks in prescribed circumstances. Other strategies include avoiding cooking with solid fuels, ventilating and isolating cooking areas, and using portable air cleaners fitted with high-efficiency particulate air filters. We detail recommendations to assist providers and public health officials when advising patients and the public regarding personal-level strategies to mitigate risk imposed by air pollution, while recognising that well-designed prospective studies are urgently needed to better establish and validate interventions that benefit respiratory health in this context.

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“…The program allows users to access historical data, add spatial meta data, and create maps and plots for viewing community monitoring data [28]. Larkin et al (2015) developed a smartphone software package for predicting air pollutant concentrations at mobile locations. They observed PM 10 and PM 2.5 [29].…”

Section: Process Of Multi-item Air Quality Monitoring Systemmentioning

confidence: 99%

Development of Multi-Item Air Quality Monitoring System Based on Real-Time Data

et al. 2021

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Many air pollutants are inhaled by human breathing, increasing the prevalence of respiratory disease and even mortality. With the recent COVID-19 issue, the number of air pollutants affecting humans is demands further investigation. However, there are not many adequate air measuring devices that can cover a variety of air pollutants. In this study, the developed air measurement system is able to measure sixteen air pollutants (PM10, PM2.5, PM4.0, PM1.0, CO2, CH4, temperature, humidity, VOCs, O2, H2S, NH3, SO2, CO, O3, NO2) in real time. The developed ‘multi-item air quality monitoring system’ can measure sixteen air pollutants in real time and transmit them to the server and the smartphone application at the same time. It was developed to reduce air pollutant damage to humans by emergency alerts using the smartphone application. The development system is composed of hardware development (measurement device) and software development (smartphone application, server). To verify the reliability of the developed equipment, a comparative test, temperature–humidity accuracy test, and operating temperature test were conducted. In the comparative test, difference ratios of ±5% for PM10, ±6% for PM2.5, ±4% for O3, ±5% for NO2, ±7% for CO, and ±7% for SO2 were found compared to the professional measuring devices. The temperature and humidity accuracy test result showed high reliability at ±1% and humidity ± 2%. The result of the operating temperature test showed that there was no problem in normal operation, However, further tests including the long-term comparative test and the closed chamber test will be carried out for all sensors. Additional work including a long-term test for more clear reliability of the device and closed chamber accuracy test for all 16-item sensors, data acquisition rate, and data transmit rate are in progress for commercializing the device.

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Developing a Smartphone Software Package for Predicting Atmospheric Pollutant Concentrations at Mobile Locations

Cited by 14 publications

References 12 publications

Lifestyle chemistries from phones for individual profiling

Lifestyle chemistries from phones for individual profiling

Personal strategies to minimise effects of air pollution on respiratory health: advice for providers, patients and the public

Development of Multi-Item Air Quality Monitoring System Based on Real-Time Data

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