Internet of things and temperature and humidity variations inside a site
The knowledge and control of the behavior of temperature and humidity inside a SITE or Data Center is an important topic when one needs to avoid the existence of risky situations in the SITE such as, for example, oxidations, overheating, or firing of devices or computers. Diverse organizations where...
| Authors: | , , , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 2022 |
| Country: | México |
| Institution: | UNIVERSIDAD AUTÓNOMA DEL ESTADO DE HIDALGO |
| Repository: | PÄDI Boletín Científico de Ciencias Básicas e Ingeniería del ICBI |
| Language: | Spanish |
| OAI Identifier: | oai:repository.uaeh.edu.mx:article/9006 |
| Online Access: | https://repository.uaeh.edu.mx/revistas/index.php/icbi/article/view/9006 |
| Access Level: | Open access |
| Keyword: | Temperature Humidity Sensor Internet of Things Temperatura humedad Internet de las Cosas |
| Summary: | The knowledge and control of the behavior of temperature and humidity inside a SITE or Data Center is an important topic when one needs to avoid the existence of risky situations in the SITE such as, for example, oxidations, overheating, or firing of devices or computers. Diverse organizations where computer equipment supports their services require the finding of solutions to these problems. A closed room called SITE or Data Center, inside the same organization, contains the computer devices. In this paper and at this stage of the research project, one makes experimental measures of humidity and temperature inside and outside of the SITE to acquire information about theoretical procedures modeling the temperature and humidity behaviors inside the Data Center, about how to get reliable data with experimental procedures, and about the IoT procedures to obtain a better understanding of the behavior of the variables and how this technology can help to acquire and control these variables. The experimental data acquisition through the Internet of Things technology, the statistical analysis of the obtained data to describe their reliability, and the study of the predictive and the control capability of an artificial neural network define the applied methodology. These characteristics look for techniques to homogenize temperatures and humidities inside the SITE. The obtained results are promising since, as shown here, there is a strong correlation between the temperatures in two different spatial points inside the SITE, where the temperatures are also functions of the time. A similar situation occurs with humidity. These facts make relatively simple the variable homogenization, although one needs to make clear that the experiment needs to use more sensors to get statistically acceptable fields of temperature and humidity so that to make possible the validation of their distribution models. |
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