The determination of the levels of solar radiation incident on the terrestrial surface (W·m⁻²) is essential for several areas such as architecture, agriculture, health, power generation, telecommunications, and climate forecasting models. The high cost of acquiring and maintaining radiometric equipment makes it difficult to create and expand monitoring networks. It contributes to the limited Brazilian radiometric network and affects the understanding and availability of this variable. This paper presents the development of a new surface solar radiation measurement system based on silicon photodiodes (Si) with a spectral range between 300 nm and 1400 nm incorporating Internet of Things (IoT) technology with an estimated cost of USD 200. The proposed system can provide instantaneous surface solar radiation levels, connectivity to wireless networks and an exclusive web system for monitoring data. For the sake of comparison, the results were compared with those provided by a government meteorology station (INMet). The prototype validation resulted in determination coefficients (R²) greater than 0.95 while the statistical analysis referred to the results and uncertainties for the range of ±500 kJ·m⁻², less than 4.0% for the developed prototypes. The proposed system operates similarly to pyranometers based on thermopiles providing reliable readings, a low acquisition and maintenance cost, autonomous operation, and applicability in the most varied climatological and energy research types. The developed system is pending a patent at the National Institute of Industrial Property under registration BR1020200199846.

With the expansion of electronics in recent decades, it is notorious to observe that embedded systems are increasingly necessary to improve people’s quality of life and to facilitate the diagnosis of systems in general, ranging from pacemakers to control systems. The increased use of electronic components for technological support, such as telemetry systems, electronic injection, and automotive diagnostic scanners, enhances the perspective of data analysis through an embedded system aimed at vehicular systems. Thus, this work aims to design and implement an embedded data acquisition system for the analysis of vehicle vertical dynamics. The methodology for this study was structured into several stages: mathematical modeling of a motorcycle’s mass-spring-damper system, coding for the Arduino microcontroller, computational data analysis supported by MATLAB software version 9.6, electronic prototyping of the embedded system, implementation on the vehicle, and the analysis of motorcycle vertical dynamics parameters. In addition, a mathematical modeling of the mass-spring-damper system was performed using the state-space method. The system was implemented on the Arduino microcontroller platform, enabling real-time data transfer from a motorcycle. The experimental results have successfully validated the proposed data acquisition system.

This paper presented an autonomous electronic system for sunshine duration (SD) monitoring based on the contrast method and developed to operate on a horizontal surface. The prototype uses four photoresistors arranged at 90° in a 20 mm diameter circumference separated by a shading structure used to create a shadow pattern on the detection element. Photoresistors are inserted in individual signal conditioning circuits based on the association between Wheatstone bridges and operational amplifiers to provide an analog signal to the microcontroller unit. The determination of SD occurs through the implementation of fuzzy logic with numerical calculation methods to estimate the probability (f) of solar disk obstruction and estimate SD values. The system does not require additional adjustments after installation or use of energy sources for operation due to the use of an internal battery with charge recovery by solar panels. Experimental results of the proposed system were validated with the ones provided by a government meteorology station. Statistical analysis of the results showed a confidence index (c) greater than 90%, with a precision of 94.26%. The proposed system is a feasible low-cost solution to the available commercial systems for the measurement of sunshine duration.

The Earth is permanently surrounded by cloud cover that, particularly, is an essential component in the planet’s energy balance. In turn, cloud cover intervenes in the main conditioning factor for soil temperature: solar radiation. In particular, the soil thermal amplitude should be dampened with the attenuation of solar radiation. However, the scientific community rarely analyzes this relationship, neglecting the model that is used to estimate the soil temperature. In this context, the present study seeks to reformulate the model by inserting a variable referent to cloud cover. Thus, to achieve this objective, a physical-mathematical review of the heat flow in the vertical profile of soil is performed. The reformulated model indicates the influence of cloud cover, intervening for both the soil’s heating (nighttime period) and cooling (daytime period). Finally, the reformulated model should be employed to estimate the soil thermal behavior (in particular, on “overcast sky” days).

The current article elucidates a study centered on the development of an anemometer leveraging an inertial sensor for wind speed measurement in the northeast region of Brazil, focusing on renewable energy generation. The study encompassed a series of experiments aimed at calibrating the anemometer, analyzing the noise generated by the inertial sensor, and scrutinizing the data acquired during wind speed measurement. The calibration process unfolded in three stages: initial noise analysis, subsequent inertial data analysis, and the derivation of calibration curves. The first two stages involved experiments conducted at an average sampling rate of 10 Hz. Simultaneously, the third stage incorporated data collected over a 1 h duration while maintaining the same sampling rate. The outcomes underscore the suitability of the anemometer based on an inertial sensor for wind energy systems and diverse applications. While the wind readings from the prototype exhibit considerable fluctuations, a three-length moving average filter is applied to the prototype’s output to mitigate these fluctuations. The calibration surface was established using observational data, and the resultant surface is detailed. Data analysis assumes paramount significance in wind speed measurement, and the K-NN algorithm demonstrated superior efficacy in estimating the correspondence between measured and control data.