Abstract
ABSTRACT Increasing the efficiency of solar dryers with ensuring that the system remains accessible to all users can be achieved with their automation through low-cost and easy-to-use technique sensors. The objective was to develop, implement and evaluate an automatic system for monitoring drying parameters in a hybrid solar-electric dryer (HSED). Initially, an automated data acquisition system for collecting the parameters of sample mass, air temperature, and relative air humidity was developed and installed. The automatic mass data acquisition system was calibrated in the hybrid solar-electric dryer. The automated system was validated by comparing it with conventional devices for measuring the parameters under study. The data obtained were subjected to analysis of variance, Tukey test and linear regression at p ≤ 0.05. The system to turn on/off the exhaust worked efficiently, helping to reduce the errors related to the mass measurement. The GERAR Mobile App showed easy to be used since it has intuitive icons and compatibility with the most used operating systems for mobile devices. The responses in communication via Bluetooth were fast. The use of Arduino, a low-cost microcontroller, to automate the monitoring activity allowed estimating the mass of the product and collecting the drying air temperature and relative air humidity data through the DHT22. This sensor showed a good correlation of mass and air temperature readings between the automatic and conventional system, but low correlation for relative air humidity. In general, the automatic data acquisition system monitored in real time the parameters for drying agricultural products in the HSED.
Highlights
Several countries have started to concentrate efforts to expand the use of solar energy in various sectors to reduce the use of fossil fuels (Chen et al, 2019; Pelda et al, 2020; Lipińskia et al, 2021)
Solar energy makes it possible to perform drying with a dryer that has low costs of installation and maintenance, in a clean way, with no risk of contaminating the environment and agricultural products (Kumar & Singh, 2020; Paes et al, 2020; Nukulwar & Tungikar, 2020)
The analysis of variance for the relative error between measured mass and standard mass indicates a significant effect at p ≤ 0.05 by the F test for the variables position of the load cells (P), air temperature (T), and interaction between P and T (Table 1)
Summary
Several countries have started to concentrate efforts to expand the use of solar energy in various sectors to reduce the use of fossil fuels (Chen et al, 2019; Pelda et al, 2020; Lipińskia et al, 2021). Solar energy makes it possible to perform drying with a dryer that has low costs of installation and maintenance, in a clean way, with no risk of contaminating the environment and agricultural products (Kumar & Singh, 2020; Paes et al, 2020; Nukulwar & Tungikar, 2020). One way to overcome this problem may be automating the acquisition of data collected along the drying process (Goméz & Fernández, 2019). After a survey in the national and international literature, there was a scarcity in the study of collection of drying parameters through the automation of a solar dryer with Arduino, making it necessary for its dissemination throughout the scientific community
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