E. Ladino-Moreno, C. A. García, Eduardo Zamudio-Huertas
{"title":"Transient DynamicWeather Isolines Generated via IoT Temperature and Relative Humidity Analysis Using the NodeMCU ESP8266 in Bogotá","authors":"E. Ladino-Moreno, C. A. García, Eduardo Zamudio-Huertas","doi":"10.14483/23448393.19667","DOIUrl":null,"url":null,"abstract":"Context: This article presents the real-time estimation of temperature (°C) and relative humidity ( %) (interval of 16 seconds) for the city of Bogota DC via the Internet of Things (IoT).\nMethod: This prototype is based on the Arduino ESP8266 NodeMCU module and the DHT11 sensor, as well as on a server-client HTPP communication protocol viaWi-Fi, with remote access to information. 16 sensors were installed in Bogota DC. These sensors send the observed data to the MATLAB storage cloud (ThingSpeak) via theWi-Fi module and can be downloaded in real-time. The temperature (°C) and relative humidity ( %) values were calibrated based on measurements made by the TTH002-certified digital thermo-hygrometer.\nResults: Based on the average temperature and relative humidity obtained, two maps were elaborated by implementing QGis: one with the isotherms and another one with isohumes. The inverse distance weighting (IDW) interpolation algorithm was used.\nConclusions: The use of monitoring devices based on the IoT significantly contributes to automating meteorological data and structuring and utilizing robust databases in the field of Civil Engineering. Thus, the real-time transmission of temperature and relative humidity data allows for the online analysis of variables. Finally, the term adaptive dynamic cartography is proposed, which is associated with the generation of maps via the IoT, through which changes in the observed variables are displayed in real time, which allows monitoring the variables making adjustments based on an interpolation algorithm, as well as automatically and instantaneously generating isolines, which significantly reduces the uncertainty implied by the spatial-temporal resolution of current cartography.","PeriodicalId":41509,"journal":{"name":"Ingenieria","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ingenieria","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14483/23448393.19667","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Context: This article presents the real-time estimation of temperature (°C) and relative humidity ( %) (interval of 16 seconds) for the city of Bogota DC via the Internet of Things (IoT).
Method: This prototype is based on the Arduino ESP8266 NodeMCU module and the DHT11 sensor, as well as on a server-client HTPP communication protocol viaWi-Fi, with remote access to information. 16 sensors were installed in Bogota DC. These sensors send the observed data to the MATLAB storage cloud (ThingSpeak) via theWi-Fi module and can be downloaded in real-time. The temperature (°C) and relative humidity ( %) values were calibrated based on measurements made by the TTH002-certified digital thermo-hygrometer.
Results: Based on the average temperature and relative humidity obtained, two maps were elaborated by implementing QGis: one with the isotherms and another one with isohumes. The inverse distance weighting (IDW) interpolation algorithm was used.
Conclusions: The use of monitoring devices based on the IoT significantly contributes to automating meteorological data and structuring and utilizing robust databases in the field of Civil Engineering. Thus, the real-time transmission of temperature and relative humidity data allows for the online analysis of variables. Finally, the term adaptive dynamic cartography is proposed, which is associated with the generation of maps via the IoT, through which changes in the observed variables are displayed in real time, which allows monitoring the variables making adjustments based on an interpolation algorithm, as well as automatically and instantaneously generating isolines, which significantly reduces the uncertainty implied by the spatial-temporal resolution of current cartography.