Development of an Internet of Things Solution to Monitor and Analyse Indoor Air Quality

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Monitoring air quality is set to become more important at home, in the workplace and at social venues, particularly regarding promoting wellness and safeguarding social interaction. We present a didactic approach to implementing indoor air quality monitoring using an Internet of Things (IoT) solution, based upon low cost air quality sensors and edge computing nodes. We provide a tutorial that allows this solution to be replicated; similar solutions could have widespread use. Our test implementation monitored kitchen and study, each equipped with a Bosch BME680 sensor connected to a microcontroller for data transmission to a local server for storage on a database. A web based dashboard allowed for the feedback of sensor data. Two, 2-week data collection periods were undertaken to demonstrate the proof of concept. The first period was in the summer 2020 and the second in the autumn 2020 (during coronavirus ‘lockdown’ conditions). Analysis of the data showed a strong relationship between humidity and air quality (correlation coefficients of -0.624 in summer and -0.692 in autumn), with air quality degrading in the autumn. As humidity increases, air quality decreases; temperature has a weaker relationship with air quality. Further analysis showed that cleaning products can adversely impact on the air quality. Poor air quality can be mitigated by opening a window to speed up the dissipation rate of pollutants. The quantification of indoor air quality can inform activities such as cooking, heating, usage of disinfectants and monitoring of ventilation, which can potentially benefit of people with respiratory illness.
Original languageEnglish
Article number100392
Journal Internet of Things; Engineering Cyber Physical Human Systems
Early online date21 Apr 2021
Publication statusPublished (in print/issue) - 30 Jun 2021

Bibliographical note

Funding Information:
The authors wish to acknowledge support of tutors in MSc Internet of Things, in particular Dr Shuai Zhang, the Course Director, and Professor Chris Nugent the Head of School of Computing.

Publisher Copyright:
© 2021 The Authors


  • IoT
  • indoor
  • Air quality
  • Analytics
  • Tutorial


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