Improving Hydroponic Systems by Using ARUCO Markers for Leaf Detection: Focus on Tomato Plants

Over the past few years, overpopulation has become a major issue, raising the demand for basic agricultural necessities. Even with the introduction of closed-environment systems aiming to provide an alternative for space requirements, the initial setup costs for such systems are high, which serves as a barrier for farmers and industries to set up a profitable system. Hydroponics is a soil-less cultivation method that aims to replace the soil in agriculture. In traditional soil-based agriculture, plants obtain their nutrients from the soil, which acts as a reservoir for essential minerals, physical support, and water retention. However, soil contains undesirable components that reduce plant growth efficiency by absorbing plant nutrients. This makes it unpredictable, even in a controlled environment. Compared to its water counterpart, the water medium provides numerous advantages, such as water conservation, efficient nutrient delivery, reduced pest and disease risk, faster growth, reduced environmental impact, and much more. Hence, by eliminating soil, this work eliminates unpredictability and creates a better-controlled environment that performs better than its soil counterpart. However, the initial setup costs of hydroponic systems can often be prohibitive for small-scale farmers or resource-constrained communities. This research work aims to grow tomato plants hydroponically so that tomatoes are available regardless of the season. We use a combination of Nutrient Film Technique (NFT), Deep Water Culture (DWT) to analyze the growth of tomatoes in outdoor weather and other environmental conditions in southern India. Further, ARUCO markers are used for leaf identification and also to estimate the distance, pose and coordinates of the leaves by image processing technique. This serves as a method to achieve optimal leaf picture from the environment.

Authors

Institutions

Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3554598
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improving Hydroponic Systems by Using ARUCO Markers for Leaf Detection: Focus on Tomato Plants

S. Muthulakshmi, R. Kesavan, N. Subhashini, Pradeep Vishnuram et al.
IEEE Access
Smart Agriculture and AI
article

Improving Hydroponic Systems by Using ARUCO Markers for Leaf Detection: Focus on Tomato Plants

S. Muthulakshmi, R. Kesavan, N. Subhashini, Pradeep Vishnuram, P. Tharun
article en

Abstract

Over the past few years, overpopulation has become a major issue, raising the demand for basic agricultural necessities. Even with the introduction of closed-environment systems aiming to provide an alternative for space requirements, the initial setup costs for such systems are high, which serves as a barrier for farmers and industries to set up a profitable system. Hydroponics is a soil-less cultivation method that aims to replace the soil in agriculture. In traditional soil-based agriculture, plants obtain their nutrients from the soil, which acts as a reservoir for essential minerals, physical support, and water retention. However, soil contains undesirable components that reduce plant growth efficiency by absorbing plant nutrients. This makes it unpredictable, even in a controlled environment. Compared to its water counterpart, the water medium provides numerous advantages, such as water conservation, efficient nutrient delivery, reduced pest and disease risk, faster growth, reduced environmental impact, and much more. Hence, by eliminating soil, this work eliminates unpredictability and creates a better-controlled environment that performs better than its soil counterpart. However, the initial setup costs of hydroponic systems can often be prohibitive for small-scale farmers or resource-constrained communities. This research work aims to grow tomato plants hydroponically so that tomatoes are available regardless of the season. We use a combination of Nutrient Film Technique (NFT), Deep Water Culture (DWT) to analyze the growth of tomatoes in outdoor weather and other environmental conditions in southern India. Further, ARUCO markers are used for leaf identification and also to estimate the distance, pose and coordinates of the leaves by image processing technique. This serves as a method to achieve optimal leaf picture from the environment.

IEEE AccessVol. 13
Vellore Institute of Technology University (IN)
Openalex Percentile: Top 96%
Smart Agriculture and AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.