Demand Control Ventilation Strategy by Tracing the Radon Concentration in Smart Buildings

• Roberto Casado-Vara ^[1] ; David García-Retuerta ^[1] ; Alvaro Bartolomé ^[1] ; Esteban Jove ^[2] ; Jose Luis Calvo-Rolle ^[2] ; Angel Martin-del Rey ^{[1] [1]} ; Corchado, Juan M. ^[3]
  1. [1] Universidad de Salamanca

     Universidad de Salamanca

     Salamanca, España

     
  2. [2] Universidade da Coruña

     Universidade da Coruña

     A Coruña, España

     
  3. [3] IoT Digital Innovation Hub (Spain), Air Institute, Calle Segunda 4, 37188 Salamanca

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• Localización: 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020 / coord. por Álvaro Herrero Cosío, Carlos Cambra Baseca, Daniel Urda Muñoz, Javier Sedano Franco, Héctor Quintián Pardo, Emilio Santiago Corchado Rodríguez, 2021, ISBN 978-3-030-57802-2, págs. 374-382
• Idioma: inglés
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• Resumen

  • Ensuring air quality should be a mandatory premise in every building, since if not, its occupants are on high risk. In fact, Radon pollutants are stated to be the second main cause among all lung cancer patients in the United States. Radon is a noble gas which seeps up through the ground and accumulates there, making it hard to be identified. A proper ventilation system needs to be installed on industrial plants so that the Radon exhaled from building materials is properly dispelled, ensuring fresh, quality air. In order to keep a proper air quality level in smart buildings, a control ventilation strategy should be defined so that the exhaled Radon is ensured to be dispelled keeping the indoor air quality high. In the proposed paper, the diffusion-advecntion method has been studied in order to propose a solution on Radon concentration tracing on smart buildings ventilation system. Diffusion-advecntion is a mathematical method that will determine whether Radon will propagate or not, based on the concentration of Radon, the diffusion constant and the advecntion velocity of the indoor air, which can lead to a recommendation for the smart building ventilation system to be activated or not, respectively. In this paper a new ventilation strategy for smart buildings based on the Diffusion-advecntion equation has been proposed to improve air quality. The results of this new ventilation strategy have been tested in a real case study in a smart building in the city of Salamanca. The main outcome of this new strategy is the improvement in response times of the current systems.