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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635930 | PMC |
| http://dx.doi.org/10.1073/pnas.1713830114 | DOI Listing |
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Development and laboratory evaluation of a novel IoT-based electric-driven metering system for high precision garlic planter.
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College of Engineering, South China Agricultural University, Guangzhou, China.
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).
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School of Electronics Engineering (SENSE), Vellore Institute of Technology, Vellore, Tamil Nadu, India.
In recent years, the utilization of motor imagery (MI) signals derived from electroencephalography (EEG) has shown promising applications in controlling various devices such as wheelchairs, assistive technologies, and driverless vehicles. However, decoding EEG signals poses significant challenges due to their complexity, dynamic nature, and low signal-to-noise ratio (SNR). Traditional EEG pattern recognition algorithms typically involve two key steps: feature extraction and feature classification, both crucial for accurate operation.
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Department of Electrical and Computer Engineering, National University of Singapore, 117538, Singapore. Electronic address:
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