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A soil monitoring and recommendation system for consumers' ornamental plants

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, the research team designs and implements 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. They also classify treatment categories for plants by using a data mining classification algorithm, that is C4.5.

This web-based application can then notify users based on the treatment required by the plants. In the data training performance evaluation, the team shows that the system can achieve as high as 89.6% accuracy when they use the 80:20 data partition.

Read the complete research at www.researchgate.net.

Angdresey, Apriandy & Sitanayah, Lanny & Kairupan, Tjia. (2021). A Soil Monitoring and Recommendation System for Ornamental Plants. 

 


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