Design and Implementation of an Automated Weather-controlled Retractable Canopy System for Nursery Beds
Olayimika Daniel Promise, Mustapha Favour, Quadri Yusro, Ezekiel Nketawaji
Journal of Engineering Research and Reports · pp. 101–119 · Published 31 Jan 2026
10.9734/jerr/2026/v28i21792Abstract
The automated nursery bed canopy system represents a significant advancement in smart farming. This project addressed the need for precision and automation in nursery bed environments. Traditional nursery bed management faces challenges in providing protection for seedlings. This project seeks to revolutionise nursery bed cultivation by creating an automated canopy system capable of responding to environmental conditions intelligently. This study designed and implemented a hardware prototype of an automated weather-controlled retractable canopy system for nursery beds by integrating an ESP32 microcontroller, resistive soil moisture and rain sensors, a DHT22 humidity and temperature sensor, relay high-torque DC motor, solar panels, and the Blynk platform. A robust frame structure for retraction was constructed, using sensors including resistive soil moisture and rain sensors, a DHT22 humidity and temperature sensor, and motorized mechanisms including relays and high-torque DC motors for canopy movement. IoT was also integrated to ensure real-time feedback and data collection. The system met the coverage angle of 180° and was stable under different wind conditions. The time to open and cover the nursery bed under rainfall was 3 seconds, with a canopy position adjustment of ± 5°. The automated canopy systems gave a 50% higher growth rate (1.8 cm/day vs. 1.2 cm/day) compared to the manually controlled environment. The survival rate increased to 96% under the automated system, 8% better than traditional nurseries. Meanwhile, water use efficiency improved as the automated system achieved 11 kg of tomatoes per cubic meter of water compared to 6 kg/m³ under regular methods. The automated system was able to achieve better precision, reduce manual intervention, and offer potential applications in smart agriculture.
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