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. 2018 Jul 8;18(7):2198.
doi: 10.3390/s18072198.

A Cost-Effective IoT System for Monitoring Indoor Radon Gas Concentration

Oscar Blanco-Novoa  1 , Tiago M Fernández-Caramés  2 , Paula Fraga-Lamas  3 , Luis Castedo  4
Affiliations

A Cost-Effective IoT System for Monitoring Indoor Radon Gas Concentration

Oscar Blanco-Novoa et al. Sensors (Basel). .

Abstract

Radon is a noble gas originating from the radioactive decay chain of uranium or thorium. Most radon emanates naturally from the soil and from some building materials, so it can be found in many places around the world, in particular in regions with soils containing granite or slate. It is almost impossible for a person to detect radon gas without proper tools, since it is invisible, odorless, tasteless and colorless. The problem is that a correlation has been established between the presence of high radon gas concentrations and the incidence of lung cancer. In fact, the World Health Organization (WHO) has stated that the exposure to radon is the second most common cause of lung cancer after smoking, and it is the primary cause of lung cancer among people who have never smoked. Although there are commercial radon detectors, most of them are either expensive or provide very limited monitoring capabilities. To tackle such an issue, this article presents a cost-effective IoT radon gas remote monitoring system able to obtain accurate concentration measurements. It can also trigger events to prevent dangerous situations and to warn users about them. Moreover, the proposed solution can activate mitigation devices (e.g., forced ventilation) to decrease radon gas concentration. In order to show its performance, the system was evaluated in three different scenarios corresponding to representative buildings in Galicia (Spain), a region where high radon gas concentrations are common due to the composition of the soil. In addition, the influence of using external hardware (i.e., WiFi transceivers and an embedded System-on-Chip (SoC)) next to the radon gas sensor is studied, concluding that, in the tested scenarios, they do not interfere with the measurements.

Keywords: IoT; WSN; domotics; home automation; radon; sensors; smart home; wireless sensor networks.

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Conflict of interest statement

The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses or interpretation of data; in the writing of the manuscript; nor in the decision to publish the results.

Figures

Figure 1
Figure 1
Possible radon entry points in a building.
Figure 2
Figure 2
Communications architecture.
Figure 3
Figure 3
Subsystems that form the radon monitoring system.
Figure 4
Figure 4
Interface with the sensor used to obtain the data.
Figure 5
Figure 5
Components of the radon gas sensor.
Figure 6
Figure 6
Radon sensor with the 3D-printed black box that contains the added electronics.
Figure 7
Figure 7
Dashboard of the radon gas monitoring system.
Figure 8
Figure 8
Sequence diagram about the sensor value collection and user interaction.
Figure 9
Figure 9
Telegram notification about radon gas concentration.
Figure 10
Figure 10
Control flow of the tested system.
Figure 11
Figure 11
Radon gas concentration in an urban home.
Figure 12
Figure 12
Radon gas concentration in a rural home.
Figure 13
Figure 13
Radon gas concentration over 26 consecutive days.
Figure 14
Figure 14
Manual data (without ESP) vs. ESP with WiFi enabled.
Figure 15
Figure 15
ESP8266 with WiFi enabled vs. ESP8266 with WiFi disabled.
Figure 16
Figure 16
ESP8266 with WiFi disabled vs. ESP8266 with WiFi enabled and high traffic.
See this image and copyright information in PMC

References

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