Indoor condensation prediction based on a surface temperature estimation

Abstract

Summary Since indoor condensation occurs for a variety of complex reasons, it is difficult to find a fundamental solution to prevent it. Indoor condensation, which is caused by environmental changes (an increase in internal humidity or a low ambient temperature), is difficult to prevent in an occupied residential structure based on the design of the structure. In this paper, we propose a new model for predicting indoor dew condensation that occurs in a residential environment with IoT technology. First, a basic dataset in the condensation environment is collected through a test bed, and a surface temperature estimation method that uses the machine learning model used to evaluate the dataset. In addition to the surface temperature estimation technique, which achieves a low RMSE of 0.97 in the field test, an associated condensation time prediction algorithm is proposed. The proposed method is a new method for determining the intersection point between two temperature changes based on the real‐time rate of change of the surface temperature and the dew point temperature. The high condensation prediction accuracy of the proposed method is experimentally demonstrated.

Emerging ICT applications and services—Big data, IoT, and cloud computing

“…Hwang et al 6 proposed a novel algorithm for predicting indoor condensation time with a minimal number of IoT nodes in a residential environment. The test bed collected an essential data set in the condensation environment and evaluated it with a machine learning model.…”

Window seals as a source of yeast contamination

“…If the building surface temperature is lower than the air dew point temperature, moisture condenses on them next to a wall or window (Hwang et al . 2021; Kempton et al . 2021).…”

“…Places with increased humidity occur near moisturerelated sources to the use methods (shower, toilet bowl, fridge) and in areas where water condenses on surfaces. If the building surface temperature is lower than the air dew point temperature, moisture condenses on them next to a wall or window (Hwang et al 2021;Kempton et al 2021). The water condensing on the window glass and flowing drops collect organic and inorganic contaminations that have settled on the glass (Rymsza 2005).…”

Nested Buildings: An Innovative Strategy for the Integrated Seismic and Energy Retrofit of Existing Masonry Buildings with CLT Panels

“…The phenomenon of mold growth and moisture mainly depends on three parameters: the inner temperature, the internal humidity, and the inner surface temperature [72,73]. The development of condensation and mold occurs when the surface temperature is lower than the related dew temperature, which represent the saturation point of air [74]. The dew temperature can be evaluated through the psychrometric chart [75], also known as Carrier's chart, which is a graphical representation of the main parameters of humid air at a constant pressure (i.e., dry-bulb temperature, humidity ratio, wet bulb, or saturation temperature).…”