Remote monitoring of Radon gas through different IoT communication technologies

Abstract

Radon is the second cause of lung cancer in the general population after tobacco [1]. Epidemiological studies have convincingly demonstrated an association between indoor radon exposure and lung cancer, even for the relatively low levels of radon that usually exist in residential buildings. Specifically, according to WHO (World Health Organization), the proportion of lung cancer cases at national level attributable to radon [2] "varies from 3% to 14%, depending on the national average radon concentration and the prevalence of tobacco use." Radon is a radioactive gas that emanates from rocks and soils and tends to concentrate in enclosed spaces such as underground mines or houses [3]. The infiltration of soil gases is recognized as the most important source of residential radon. Therefore, radon contributes significantly to the dose of ionizing radiation received by the general population. In this sense, radon measurements are relatively simple to perform and are essential to assess radon concentration in homes. However, the concentration of radon indoors varies depending on the construction of buildings and ventilation habits. In addition, the concentration varies substantially not only according to the seasons, but also from one day to another and even from one hour to another. Due to these fluctuations, estimate the annual average radon concentration in the air of indoor requires reliable measurements of the average radon concentration for at least three months, and preferably for longer. Short-term measurements only provide an indicative and unreliable indication of the actual radon concentration. It should be noted that today thanks to the opportunities offered by IoT, there are applications that allow data to be captured unattended, sent to the internet and subsequently processed to obtain indicators and dashboards to make decisions based on information in real time. In this project, an IoT vertical will be developed that allows to know the levels of Radon at the residential level, allowing each user to know the status of their home and thus facilitating the adoption of the pertinent corrective measures. This was achieved by integrating a radon sensor on a system with an Arduino board and a SIM which sends the data through Narrowband IoT so that it is stored on a network server and can be consulted from anywhere with a URL.