Year: 2025
Type: conference-paper
Abstract: Cultivating of houseplants in biophilic designed spaces requires appropriate timing and amount of watering.However, determining them is challenging, as fluctuations in ambient temperature can influence these factors.We develop a system capable of predicting ambient temperature changes and determining the appropriate timing and amount of watering.The system acquires ambient data using sensors connected to a Jetson Nano and processes the data using a neural network for the prediction and determination.We adopt an echo state network, a lightweight neural network, enabling a power-efficient system capable of running on edge devices.Additionally, we implement a function to notify the user of the timing and amount of watering via a chat service whenever the soil moisture content drops below a predefined threshold.
Institution: Kyushu Institute of Technology
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W4409914130