Designing a low-cost IoT sensing platform for VOC material classification

Jungmo Ahn, Hyungi Kim, Eunha Kim, Jeonggil Ko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Improvements in small sized sensors allow us to easily detect the presence of Volatile Organic Compounds (VOCs) in the air using easy-to-deploy Internet of Things (IoT)-scale devices. However, classifying what VOC exists in the environment still remains as a complex task. Knowing what VOCs are in the air can help us remove the main cause that vents VOC materials in order to maintain clean air quality. In this work, we present VOCkit, an IoT sensor kit for non-chemical experts to easily detect and classify different types of VOCs. VOCkit combines miniature chemically-designed fluorometric sensors for recognizing VOCs with an embedded imaging system for classification. Exposing the fluorometric sensors with various VOCs, result in photophysical property change of each fluorescent compound, which composes the sensors, and the synergistic combination of the changes create unique individual fluorescent color patterns respectively to the VOC material. The fluorescent color change pattern is captured using a camera and the images are processed with machine learning algorithms on the embedded platform for VOC classification. Using 500 fluorometric sensor images collected for five different commonly contactable VOCs, we show the feasibility of performing VOC classification on small-sized IoT devices. For the VOC types of our interest, our results show a classification accuracy of 97%, implying the potential applicability of VOCkit for real-world usage.

Original languageEnglish
Title of host publicationProceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages82-89
Number of pages8
ISBN (Electronic)9781728105703
DOIs
Publication statusPublished - 2019 May
Event15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019 - Santorini Island, Greece
Duration: 2019 May 292019 May 31

Publication series

NameProceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019

Conference

Conference15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019
CountryGreece
CitySantorini Island
Period19/5/2919/5/31

Fingerprint

Volatile Organic Compounds
volatile organic compounds
Volatile organic compounds
Internet
platforms
Costs and Cost Analysis
air
costs
Costs
sensors
Sensors
Air
expert
cause
Internet of things
Color
learning
color
Equipment and Supplies
machine learning

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Health Informatics
  • Instrumentation
  • Transportation
  • Communication

Cite this

Ahn, J., Kim, H., Kim, E., & Ko, J. (2019). Designing a low-cost IoT sensing platform for VOC material classification. In Proceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019 (pp. 82-89). [8804838] (Proceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DCOSS.2019.00034
Ahn, Jungmo ; Kim, Hyungi ; Kim, Eunha ; Ko, Jeonggil. / Designing a low-cost IoT sensing platform for VOC material classification. Proceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 82-89 (Proceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019).
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abstract = "Improvements in small sized sensors allow us to easily detect the presence of Volatile Organic Compounds (VOCs) in the air using easy-to-deploy Internet of Things (IoT)-scale devices. However, classifying what VOC exists in the environment still remains as a complex task. Knowing what VOCs are in the air can help us remove the main cause that vents VOC materials in order to maintain clean air quality. In this work, we present VOCkit, an IoT sensor kit for non-chemical experts to easily detect and classify different types of VOCs. VOCkit combines miniature chemically-designed fluorometric sensors for recognizing VOCs with an embedded imaging system for classification. Exposing the fluorometric sensors with various VOCs, result in photophysical property change of each fluorescent compound, which composes the sensors, and the synergistic combination of the changes create unique individual fluorescent color patterns respectively to the VOC material. The fluorescent color change pattern is captured using a camera and the images are processed with machine learning algorithms on the embedded platform for VOC classification. Using 500 fluorometric sensor images collected for five different commonly contactable VOCs, we show the feasibility of performing VOC classification on small-sized IoT devices. For the VOC types of our interest, our results show a classification accuracy of 97{\%}, implying the potential applicability of VOCkit for real-world usage.",
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Ahn, J, Kim, H, Kim, E & Ko, J 2019, Designing a low-cost IoT sensing platform for VOC material classification. in Proceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019., 8804838, Proceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019, Institute of Electrical and Electronics Engineers Inc., pp. 82-89, 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019, Santorini Island, Greece, 19/5/29. https://doi.org/10.1109/DCOSS.2019.00034

Designing a low-cost IoT sensing platform for VOC material classification. / Ahn, Jungmo; Kim, Hyungi; Kim, Eunha; Ko, Jeonggil.

Proceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 82-89 8804838 (Proceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Ahn J, Kim H, Kim E, Ko J. Designing a low-cost IoT sensing platform for VOC material classification. In Proceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 82-89. 8804838. (Proceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019). https://doi.org/10.1109/DCOSS.2019.00034