DEVELOPMENT, IMPLEMENTATION AND VALIDATION OF NA AUTOMATIC BOARDED WEATHER STATION BASEAD ON IOT TECHNOLOGY
In order to offer an alternative in relation to the methods and technology classically used in the acquisition of meteorological data, this article aimed to develop an validate an embedded automatic weather station using the IoT platform ThingSpeak platform in the city of Belém - PA. For the acquisi...
| Authors: | , , , , , |
|---|---|
| Format: | article |
| Status: | Published version |
| Publication Date: | 2024 |
| Country: | Brasil |
| Institution: | Universidade Federal de Mato Grosso (UFMT) |
| Repository: | Nativa (Sinop) |
| Language: | Portuguese |
| OAI Identifier: | oai:periodicoscientificos.ufmt.br:article/16796 |
| Online Access: | https://periodicoscientificos.ufmt.br/ojs/index.php/nativa/article/view/16796 |
| Access Level: | Open access |
| Keyword: | meteorology microcontrollers Internet of Things meteorologia microcontroladores Internet das Coisas ThingSpeak |
| Summary: | In order to offer an alternative in relation to the methods and technology classically used in the acquisition of meteorological data, this article aimed to develop an validate an embedded automatic weather station using the IoT platform ThingSpeak platform in the city of Belém - PA. For the acquisition of temperature, humidity, wind speed and precipitation data, the AM2301 temperature and humidity sensor, the SEN0170 anemometer and a tipping bucket rain gauge were used, with the storage and visualization of the acquired data being done through the ThingSpeak platform. To infer the reliability of the data obtained by the sensors used, statistical analysis methods and residual estimation error indicators were applied. The values found for the obtained indices were classified, for the most part, as 'Very Good' and 'Good', validating the functionality of the station, even considering that the values of unfavorable indices include the instrumental errors of the sensors and the spatial and temporal distribution of the observed variables, such errors cannot be inferred only to the sensors, suggesting methodological approximations that reduce the errors only to the instrumental error. |
|---|