The Use of Intelligent Systems for Determining Planting Distance on Corn and Soybean Planters and Remote Monitoring

Roza Susanti; Yul  Antonisfia; Efendi; Jama’an; A. Larenza Sri Gusti Astuti

doi:10.59890/ijatss.v2i12.95

Authors

Roza Susanti Padang State Polytechnic
Yul Antonisfia Padang State Polytechnic
Efendi Padang State Polytechnic
Jama’an Padang State Polytechnic
A. Larenza Sri Gusti Astuti Padang State Polytechnic

DOI:

https://doi.org/10.59890/ijatss.v2i12.95

Keywords:

M JST, HC-SR04 Ultrasonic Sensor, TCS3200 Sensor, Mit App Inventor

Abstract

Indonesia is a country that heavily relies on corn and soybeans, making increased cultivation vital for achieving high productivity. Proper planting distance and hole depth are crucial factors to ensure uniform growth and optimize land use. Planting distances that are too tight lead to non-uniform growth due to root competition for nutrients, while excessively wide spacing reduces productivity by leaving land underutilized.This study aims to address these challenges by developing a planting tool using a backpropagation artificial neural network. The HC-SR04 ultrasonic sensor detects seed capacity in the container, while the TCS3200 sensor identifies seed color. Data is processed by an Arduino Mega microcontroller, with an LCD displaying information and the Mit App Inventor application enabling remote monitoring. A DC motor serves as the wheel and planter driver, and a servo motor handles seed rationing. Testing showed promising results. For corn seedlings, the average planting distance was 23.6 cm, with a hole depth of 2.18 cm. For soybean seedlings, the average planting distance was 35.47 cm, with a hole depth of 2.04 cm. This tool demonstrates potential to enhance planting efficiency and uniformity, contributing to improved agricultural productivity

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