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Towards Self-Tracking Personal Pollu...

Sakhnini, Nina.

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Towards Self-Tracking Personal Pollution Exposure Using Wearables.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Towards Self-Tracking Personal Pollution Exposure Using Wearables./
Author:	Sakhnini, Nina.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	115 p.
Notes:	Source: Masters Abstracts International, Volume: 81-08.
Contained By:	Masters Abstracts International81-08.
Subject:	Computer science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27605390
ISBN:	9781687998347

Towards Self-Tracking Personal Pollution Exposure Using Wearables.
Sakhnini, Nina.

Towards Self-Tracking Personal Pollution Exposure Using Wearables. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 115 p.

Source: Masters Abstracts International, Volume: 81-08.

Thesis (M.S.)--University of Illinois at Chicago, 2019.

This item must not be sold to any third party vendors.

Recent epidemiological studies have shown that long-term exposure to air pollution is positively associated with mild cognitive impairment (MCI). Although interest in pollution monitoring is proliferating, self-tracking personal pollution exposure is little explored. In this thesis, I adopt a human-centered computing approach to explore the design space of personal pollution tracking wearables. This work makes three contributions to human-computer interaction: 1) design guidelines for rapid-prototyping low-cost, sub-optimal personal pollution tracking wearables and a physical prototype that measures pollutants shown to be associated with cognitive impairment in older adults: PM2.5 and ambient noise, 2) exploration of different calibration techniques to improve the accuracy of low-cost PM2.5 sensors, and 3) a characterization of how human interference, our day-to-day activities, significantly affect the operation of personal pollution tracking wearables. In sum, this thesis informs design guidelines about how to physically prototype personal pollution tracking wearables and where to wear them---beyond citizen-science efforts of data collection---rather toward monitoring personal long-term pollution exposures to mitigate the environmental risk factors for many illnesses such as early dementia.

ISBN: 9781687998347Subjects--Topical Terms:

523869
Computer science.
Subjects--Index Terms:

Pollution exposure management

Towards Self-Tracking Personal Pollution Exposure Using Wearables.
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520 $a Recent epidemiological studies have shown that long-term exposure to air pollution is positively associated with mild cognitive impairment (MCI). Although interest in pollution monitoring is proliferating, self-tracking personal pollution exposure is little explored. In this thesis, I adopt a human-centered computing approach to explore the design space of personal pollution tracking wearables. This work makes three contributions to human-computer interaction: 1) design guidelines for rapid-prototyping low-cost, sub-optimal personal pollution tracking wearables and a physical prototype that measures pollutants shown to be associated with cognitive impairment in older adults: PM2.5 and ambient noise, 2) exploration of different calibration techniques to improve the accuracy of low-cost PM2.5 sensors, and 3) a characterization of how human interference, our day-to-day activities, significantly affect the operation of personal pollution tracking wearables. In sum, this thesis informs design guidelines about how to physically prototype personal pollution tracking wearables and where to wear them---beyond citizen-science efforts of data collection---rather toward monitoring personal long-term pollution exposures to mitigate the environmental risk factors for many illnesses such as early dementia.
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