Research Article

An IoT Based Air Quality Measurement and Warning System for Ambient Assisted Living

Number: 16 August 31, 2019
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An IoT Based Air Quality Measurement and Warning System for Ambient Assisted Living

Abstract

Indoor air quality parameters are extremely important for creating an efficient and healthy Ambient Assisted Living (AAL) environment, but mostly indoor air quality parameters are well above the values defined as healthy. We spend most of our lives indoors. Detecting air quality problems and improving air quality is only possible by monitoring air quality in real time. Today, smart home automation has become a popular trend, and consumers are increasingly aware of new technologies developed in this area, hence the demand for smart homes is growing. In this study, with the IoT-based indoor air quality measurement and warning system, an AAL system was proposed to help especially elderly and children, to  live safely in their homes. The proposed AAL system consists of a ESP32 controller with a new generation embedded system architecture and low cost different air quality sensors. In addition, the AAL system provides real-time monitoring of indoor air quality parameters such as CO2, CO, PM10, NO2, temperature and humidity via the mobile user interface developed with the Blynk IoT platform. The mobile application sends warning notifications to users if the indoor air quality parameters exceeded the specified threshold values. Thanks to these notifications, households can take the necessary measures as soon as possible against the factors that threaten the health of the elderly and children with simple measures such as natural ventilation. The results showed that the proposed measurement system can contribute significantly to AAL systems with its low cost, open source technology, easy installation and mobility.

Keywords

References

  1. Air quality in Europe, 2018 report, European Environment Agency https://www.eea.europa.eu/publications/air-quality-in-europe-2018/download, (accessed date, 04.08.2019).
  2. Benammar, M., Abdaoui, A., Ahmad, S., Touati, F., & Kadri, A. (2018). A modular IoT platform for real-time indoor air quality monitoring. Sensors, 18(2), 581.
  3. Bianchi, V., Bassoli, M., Lombardo, G., Fornacciari, P., Mordonini, M., & De Munari, I. (2019). IoT Wearable Sensor and Deep Learning: an Integrated Approach for Personalized Human Activity Recognition in a Smart Home Environment. IEEE Internet of Things Journal.
  4. Bröring, A., Schmid, S., Schindhelm, C. K., Khelil, A., Kabisch, S., Kramer, D., López, E. (2017). Enabling IoT ecosystems through platform interoperability. IEEE software, 34(1), 54-61.
  5. Cho, H. (2017). An Air Quality and Event Detection System with Life Logging for Monitoring Household Environments. In Smart Sensors at the IoT Frontier (pp. 251-270). Springer, Cham.
  6. Darwish, M., Senn, E., Lohr, C., & Kermarrec, Y. (2014). A comparison between ambient assisted living systems. In International Conference on Smart Homes and Health Telematics (pp. 231-237). Springer, Cham.
  7. ESP32 Series Microcontrollers, Version 3.1 Espressif Systems, https://www.espressif.com/sites/default/files/documentation/esp32_datasheet_en.pdf, (accessed date, 04.08.2019).
  8. Fioccola, G. B., Sommese, R., Tufano, I., Canonico, R., & Ventre, G. (2016). Polluino: An efficient cloud-based management of IoT devices for air quality monitoring. In 2016 IEEE 2nd International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI) (pp. 1-6). IEEE.

Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Publication Date

August 31, 2019

Submission Date

June 1, 2019

Acceptance Date

August 30, 2019

Published in Issue

Year 2019 Number: 16

APA
Taştan, M. (2019). An IoT Based Air Quality Measurement and Warning System for Ambient Assisted Living. Avrupa Bilim Ve Teknoloji Dergisi, 16, 960-968. https://doi.org/10.31590/ejosat.607434
AMA
1.Taştan M. An IoT Based Air Quality Measurement and Warning System for Ambient Assisted Living. EJOSAT. 2019;(16):960-968. doi:10.31590/ejosat.607434
Chicago
Taştan, Mehmet. 2019. “An IoT Based Air Quality Measurement and Warning System for Ambient Assisted Living”. Avrupa Bilim Ve Teknoloji Dergisi, nos. 16: 960-68. https://doi.org/10.31590/ejosat.607434.
EndNote
Taştan M (August 1, 2019) An IoT Based Air Quality Measurement and Warning System for Ambient Assisted Living. Avrupa Bilim ve Teknoloji Dergisi 16 960–968.
IEEE
[1]M. Taştan, “An IoT Based Air Quality Measurement and Warning System for Ambient Assisted Living”, EJOSAT, no. 16, pp. 960–968, Aug. 2019, doi: 10.31590/ejosat.607434.
ISNAD
Taştan, Mehmet. “An IoT Based Air Quality Measurement and Warning System for Ambient Assisted Living”. Avrupa Bilim ve Teknoloji Dergisi. 16 (August 1, 2019): 960-968. https://doi.org/10.31590/ejosat.607434.
JAMA
1.Taştan M. An IoT Based Air Quality Measurement and Warning System for Ambient Assisted Living. EJOSAT. 2019;:960–968.
MLA
Taştan, Mehmet. “An IoT Based Air Quality Measurement and Warning System for Ambient Assisted Living”. Avrupa Bilim Ve Teknoloji Dergisi, no. 16, Aug. 2019, pp. 960-8, doi:10.31590/ejosat.607434.
Vancouver
1.Mehmet Taştan. An IoT Based Air Quality Measurement and Warning System for Ambient Assisted Living. EJOSAT. 2019 Aug. 1;(16):960-8. doi:10.31590/ejosat.607434

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