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Research Article Open access CC BY 4.0

Smart Hydroponic Greenhouse (Sensing, Monitoring and Control) Prototype Based on Arduino and IOT

M. A. Abul-Soud, M. S. A. Emam, Sh. M. Mohammed

International Journal of Plant & Soil Science · pp. 63–77 · Published 12 Apr 2021

10.9734/ijpss/2021/v33i430430

Abstract

Aims: Sensing, monitoring and control the micro-climate measurements and environmental conditions of greenhouse prototype to create a smart hydroponic greenhouse for maximizing the food production as well as minimizing the ecological footprint under the climate change impacts, Coved 19 crisis, and natural resources shortages. Study Design: Factorial with 3 replicates. Place and Duration of Study: Central Laboratory for Agriculture Climate (CLAC), Agriculture Research Center, Egypt during 2020. Methodology: Two systems of hydroponic culture, nutrient film technique (NFT) and deep flow technique (DFT) that cultivated by lettuce plants were established under greenhouse (polycarbonate) prototype (0.8 * 1.2 * 0.6 m) designed with artificial grown light and cooling system. Based on Arduino Mega 2560 that programmed via the Arduino IDE program, different sensors and actuators were used to establishing the smart greenhouse. Internet of things (IoT) via Node MCU ESP 8266 that programmed to transmitted the data every 30 min. to the internet web google platform (Firebase) for presenting the real-time records and hosting the data. Vegetative characteristics; yield parameters and N, P, and K contents of lettuce plants were measured. Results: the smart greenhouse worked according to the programming of Arduino Mega and Node MCU with high efficiency. Google firebase platform displays the real-time records and hosts about 100 thousand different sensor records during the lettuce season. Decreasing the distance between the lettuce and artificial lightning source led to increasing the intensity of light that had a positive impact on lettuce growth but it wasn't sufficient to give a high quality of lettuce yield under the experiment. NFT system gave higher values of average No. of leaves and fresh weight of lettuce plants than DFT system that presented higher plant length. Conclusion: Integrated monitoring and control system and IOT provide a wireless sensors network that offered a high capability of accessing huge data anywhere and anytime. Smart management of nutrient solution (TDS, pH, temperature, and level), without smart control, were not useful enough regarding the rapid solution changes and the need for a high response.

Smart agriculture monitoring control NFT DFT arduino mega IOT WiFi sensors and goggle firebase

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