Proposal for weather stations on raspberry pi to measure climate in micro-zones

Abstract

The introduction of technology into various aspects of human life has been a long-standing and ongoing endeavor in the modern era. The study of climate behavior has been a concern of human beings for millennia. However, in the past two centuries, significant advancements have been made in the field of climate prediction, aiming to enhance the accuracy and efficiency of this process. Nevertheless, in the country, it occupies a marginal position and is even less utilized. In some cases, the necessity for precise atmospheric data, which can be obtained through the use of cutting-edge technologies, as well as a substantial network of meteorological stations that measure and determine values with greater accuracy and precision, has led to significant investments in these technologies. In the contemporary era, these perspectives have undergone a transformation, with the climate field now perceived as a potential source of economic growth and development in the country. In light of the aforementioned considerations, the objective is to present a proposal for the use of cutting-edge technological solutions, namely artificial intelligence (AI), which is based on machines that are capable of self-learning (machine learning) and are adept at analyzing vast quantities of information, thereby facilitating the advancement of knowledge in this field and enabling more accurate climate behavior prediction in Colombia. The principal objective is to facilitate the utilization of technologies as a predictive tool for climate behavior, with the aim of accurately simulating climate predictions and analyses through computational technologies and expert input. This will entail the convergence of multiple variables to present values that are as close to reality as possible.The objective of this paper is to present a technology based on the Raspberry Pi, software, and sensors, including the configuration of a basic and cost-effective weather station for the collection of climate data on a large scale. This project aims to ensure that technology is utilized with a defined objective to facilitate the study of climate from academic to practical contexts.