Abstract
In order to address many issues, such as the inconsistent and unreliable seeding process in traditional mechanical garlic seed metering systems (SMS), as well as the lack of ability to monitor the effectiveness of the seeding, a highly accurate electric-driven metering system (EDMS) was developed and created specifically for garlic seed planters. This study provided a description of the overall structure and functioning principle, as well as an analysis of the mechanism for smooth transit and delivery. A combination of an infrared (IR) sensor, Arduino Mega board, stepper motor, speed sensor, and a Wi-Fi module was employed to operate the EDMS, as well as monitor and count the quantity of garlic seeds during the planting process and determine the qualified rate (QR) and missing rate (MR). A monitoring system of the planting quality of garlic seeds was created based on the IoT concept. Then, the performance of the EDMS was validated in a laboratory setting utilizing a bench test at six operating velocities of 10, 20, 30, 40, 50, and 60 rpm of the EDMS. The obtained results showed that the correlation coefficient between the actual and detected garlic seed using the garlic seed monitoring and counting system (GSMCS) was 0.9723. Additionally, the EDMS observed a maximum QR of 96.23% at an operating velocity of 20 rpm, with a standard division and standard error of 1.61030 and 0.72015, respectively. Additionally, the EDMS minimized the MR up to 3.77% at the same operating velocity, with standard division and standard error of 1.65325 and 0.73936, respectively. Furthermore, the results indicated a progressive increase in the QR and MQ standard errors as the EDMS's operating velocity increased. Additionally, the sensor's monitoring accuracy gradually declined with an increase in the operating speed of the EDMS. Finally, this study introduced a novel EDMS to garlic seed planters that was not used before. The developed EDMS and GSMCS are technical manuals for developing and designing monitoring systems capable of precisely measuring and identifying the rates of qualifying and missing garlic seed measurements.