An Intelligent Weather Station.

Gonçalo Mestre,Hamid Khosravani,Sergio Silva,Antonio Ruano,Shabnam Pesteh,Helder Duarte,Pedro Ferreira,Ricardo Horta

doi:10.3390/s151229841

Gonçalo Mestre, Hamid Khosravani + Show 6 more

Open Access

https://doi.org/10.3390/s151229841

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Abstract

Accurate measurements of global solar radiation, atmospheric temperature and relative humidity, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight, self-powered and portable sensor was developed, using a nearest-neighbors (NEN) algorithm and artificial neural network (ANN) models as the time-series predictor mechanisms. The hardware and software design of the implemented prototype are described, as well as the forecasting performance related to the three atmospheric variables, using both approaches, over a prediction horizon of 48-steps-ahead.

Highlights

There are a number of different weather stations available in the market
The atmospheric variables are measured by sensors that usually are connected to a data logger
The conclusions that were drawn for air temperature apply to relative humidity: The best performance was obtained by the Radial Basis Function (RBF) Neural Network (NN) model, and the parameterization (21, 4) achieved the best NEN results, which are better than those obtained by the RBF at the last few instants of the prediction horizon

Summary

Introduction

There are a number of different weather stations available in the market. They provide measurements of atmospheric parameters such as solar radiation, air temperature and relative humidity, wind velocity and direction, atmospheric pressure and rainfall, the first three variables being the most common. With the weather station core selected, the development was shifted to the sensors employed to measure the atmospheric variables considered. A push button and a toggle button were incorporated in the weather station design The need for these buttons is due to the fact that the RPI does not have a power or reset button. The developed board provides a place holder for the Xbee and enables the communication, but it is ready to control its sleep state This is useful since this is a self-powered device and awaken 2.4 GHz or 868 MHz Xbee modules have a power consumption of about 37 and 60 mA, respectively. The circuit selected to implement this behavior was the LTC4417 from Linear Technology [26]

Software

Atmospheric Relative Humidity

Solar Radiation

Conclusions