Automatic Plant Health Monitoring Device based on NDVI Analysis using Raspberry Pi for Water Apple Plant

Rizky Pratama Hudhajanto, Nanta Fakih Prebianto, Muchammad Fajri Amirul Nasrullah, Jesy Neland

Abstract

Indonesia is a tropical country with abundant agricultural products. Therefore, the increase of efficiency and productivity of these crops is needed. Normalized Difference Vegetation Index is an index used to monitor plant health. To find out the NDVI value, a special camera is used to capture Near Infrared (NIR) light spectrum. This special camera is usually used by the professional plantation industry and is very expensive. In this study, we used a raspberry pi and a low cost Pi Noir camera to create a system that can predict the NDVI value of plants. The plant used as testing object is a Water Apple Plant (Syzygium aqueum). The result was that the system was able to identify the health of plant based on their NDVI value.

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Paper Citation


in Harvard Style

Hudhajanto R., Prebianto N., Nasrullah M. and Neland J. (2020). Automatic Plant Health Monitoring Device based on NDVI Analysis using Raspberry Pi for Water Apple Plant. In Proceedings of the 3rd International Conference on Applied Engineering - Volume 1: ICAE, ISBN 978-989-758-520-3, pages 115-118. DOI: 10.5220/0010352701150118


in Bibtex Style

@conference{icae20,
author={Rizky Pratama Hudhajanto and Nanta Fakih Prebianto and Muchammad Fajri Amirul Nasrullah and Jesy Neland},
title={Automatic Plant Health Monitoring Device based on NDVI Analysis using Raspberry Pi for Water Apple Plant},
booktitle={Proceedings of the 3rd International Conference on Applied Engineering - Volume 1: ICAE,},
year={2020},
pages={115-118},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010352701150118},
isbn={978-989-758-520-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Applied Engineering - Volume 1: ICAE,
TI - Automatic Plant Health Monitoring Device based on NDVI Analysis using Raspberry Pi for Water Apple Plant
SN - 978-989-758-520-3
AU - Hudhajanto R.
AU - Prebianto N.
AU - Nasrullah M.
AU - Neland J.
PY - 2020
SP - 115
EP - 118
DO - 10.5220/0010352701150118