IoT greenhouse for the study of seedlings, in the southwestern region of Valle del Cauca
DOI:
https://doi.org/10.26507/paper.4542Keywords:
IOT, ESP32, greenhouse, seedlingsAbstract
A low‑cost IoT greenhouse was developed aimed to optimizing letucce and coriander cultivation at University of Valle, using an ESP32 microcontroller to regulate air temperature, relative humidity, substrate moisture and photoperiod through DHT22 sensors, capacitive tensiometers, a UV‑LED module and actuators (fans, drip pump and relays). Control set‑points (20–24 °C and 60–80 % RH for lettuce; ≥ 24 °C and 60–75 % RH for coriander) were derived from nine recent agronomic studies. Over a 22‑day trial, real‑time environmental data and seedling growth of Lactuca sativa and Coriandrum sativum were recorded. The system stayed within the optimal lettuce range 86 % of the time and reached the coriander temperature target during the final ten days. Mean elongation rates were 0.36 cm day⁻¹ for lettuce and 0.55 cm day⁻¹ for coriander, while water consumption decreased by 23 % compared with timer‑based manual irrigation. Main constraints included the ±0.5 °C/±2 % RH sensor resolution and occasional RH peaks above 80 % under limited ventilation. Upgrading to higher‑precision sensors, predictive algorithms and active dehumidification is recommended for mixed‑crop optimization. Overall, the study shows that an IoT greenhouse tuned with literature‑backed environmental ranges enhances biomass production and water‑use efficiency, providing a scalable platform for precision agriculture.
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