PLANTery: an IoT-based automated plant watering system and pest detection using Convolutional Neural Network (CNN)

This study addresses busy individual’s challenges in maintaining plants, specifically watering and pest control. PLANTery automates plant care by using IoT sensors (for soil moisture, temperature, and humidity) to activate irrigation as needed and a Convolutional Neural Network (CNN) for real-time pest detection, alerting users, and recommending anti-pest measures. The system received an excellent rating from respondents, with an overall weighted mean of 4.74, indicating high functionality, efficiency, reliability, and usability. This result reflects intense user satisfaction and demonstrates that the system effectively achieves its objectives, providing robust solutions for plant care.

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Publication Details

Journal
IET conference proceedings.
Published
2025-03-01
DOI
https://doi.org/10.1049/icp.2025.0279
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

PLANTery: an IoT-based automated plant watering system and pest detection using Convolutional Neural Network (CNN)

Criselle J. Centeno, Ariel Antwaun Rolando C. Sison, Diony S. Abando, Sophia A. Maramara et al.
IET conference proceedings.
Smart Agriculture and AI
article

PLANTery: an IoT-based automated plant watering system and pest detection using Convolutional Neural Network (CNN)

Criselle J. Centeno, Ariel Antwaun Rolando C. Sison, Diony S. Abando, Sophia A. Maramara, Jayson G. Pisos, Francis Jericho F. Ras
article en

Abstract

This study addresses busy individual’s challenges in maintaining plants, specifically watering and pest control. PLANTery automates plant care by using IoT sensors (for soil moisture, temperature, and humidity) to activate irrigation as needed and a Convolutional Neural Network (CNN) for real-time pest detection, alerting users, and recommending anti-pest measures. The system received an excellent rating from respondents, with an overall weighted mean of 4.74, indicating high functionality, efficiency, reliability, and usability. This result reflects intense user satisfaction and demonstrates that the system effectively achieves its objectives, providing robust solutions for plant care.

IET conference proceedings.Vol. 2024(30)
Mapúa University (PH), University of the City of Manila (PH)
Zero hunger
Openalex Percentile: Top 97%
Smart Agriculture and AI
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PLANTery: an IoT-based automated plant watering system and pest detection using Convolutional Neural Network (CNN) — Criselle J. Centeno, Ariel Antwaun Rolando C. Sison, et al. · IET conference proceedings. (2025) | TGRS Research Map | TGRS