A Soil Monitoring and Recommendation System for Ornamental Plants

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Apriandy Angdresey, Lanny Sitanayah, Tjia Valentyno Nathaniel Kairupan

2021 Proceedings of 2021 6th International Conference on New Media Studies, CONMEDIA 2021 Conference paper Cited by 4 Quartile

Abstract

Taking care of ornamental plants includes paying attention to soil moisture in pots, making sure the plants are exposed to sufficient sunlight, and applying fertilizer when needed. However, people nowadays do not have enough time to monitor the conditions of their plants. In this paper, we design and implement an Internet of Things-based soil monitoring system by utilizing three sensors, i.e. a soil moisture sensor, a temperature sensor, and a pH sensor. We classify treatment categories for plants by using a data mining classification algorithm, that is C4.5. Our web-based application can then notify users based on the treatment required by the plants. In our data training performance evaluation, we show that the system can achieve as high as 89.6% accuracy when we use the 80:20 data partition. © 2021 IEEE.

Affiliations

Universitas Katolik de la Salle, Department of Informatics Engineering, Manado, Indonesia

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