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. 2018 Feb 14;18(2):581.
doi: 10.3390/s18020581.

A Modular IoT Platform for Real-Time Indoor Air Quality Monitoring

Mohieddine Benammar  1 , Abderrazak Abdaoui  2 , Sabbir H M Ahmad  3 , Farid Touati  4 , Abdullah Kadri  5
Affiliations

A Modular IoT Platform for Real-Time Indoor Air Quality Monitoring

Mohieddine Benammar et al. Sensors (Basel). .

Abstract

The impact of air quality on health and on life comfort is well established. In many societies, vulnerable elderly and young populations spend most of their time indoors. Therefore, indoor air quality monitoring (IAQM) is of great importance to human health. Engineers and researchers are increasingly focusing their efforts on the design of real-time IAQM systems using wireless sensor networks. This paper presents an end-to-end IAQM system enabling measurement of CO₂, CO, SO₂, NO₂, O₃, Cl₂, ambient temperature, and relative humidity. In IAQM systems, remote users usually use a local gateway to connect wireless sensor nodes in a given monitoring site to the external world for ubiquitous access of data. In this work, the role of the gateway in processing collected air quality data and its reliable dissemination to end-users through a web-server is emphasized. A mechanism for the backup and the restoration of the collected data in the case of Internet outage is presented. The system is adapted to an open-source Internet-of-Things (IoT) web-server platform, called Emoncms, for live monitoring and long-term storage of the collected IAQM data. A modular IAQM architecture is adopted, which results in a smart scalable system that allows seamless integration of various sensing technologies, wireless sensor networks (WSNs) and smart mobile standards. The paper gives full hardware and software details of the proposed solution. Sample IAQM results collected in various locations are also presented to demonstrate the abilities of the system.

Keywords: Emoncms; Internet-of-Things; WSN; indoor air quality monitoring.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
IAQM system architecture.
Figure 2
Figure 2
Gas sensors node for IAQM.
Figure 3
Figure 3
NDIR-type CO2 sensor and its interface module.
Figure 4
Figure 4
Block diagrams of the interface modules for the: three-electrode (a); and four-electrode (b) electrochemical sensors.
Figure 5
Figure 5
Gateway.
Figure 6
Figure 6
Flowchart of the data processing at the gateway.
Figure 7
Figure 7
Message resubmission after Internet connection code Fragment.
Figure 8
Figure 8
The main scripts running in the gateway.
Figure 9
Figure 9
Shell script managing the periodic execution of the message resubmissions.
Figure 10
Figure 10
Floor plan of Qatar University library building used for evaluating packet loss of the radio transmission channel.
Figure 11
Figure 11
Percentage of packet loss for the various locations of the radio transmitter (shown in Figure 10).
Figure 12
Figure 12
Indoor air quality data (as displayed by the online Emoncms IoT) collected in an office space at Qatar University during December 2017.
Figure 13
Figure 13
Emoncms IoT-displayed indoor air quality data collected in a Chemical Engineering research lab of Qatar University (9 December 2017 to 9 January 2018).
See this image and copyright information in PMC

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