Advanced Hydroponic Nutrient Management Systems for Vertical Farming Efficiency with IoT and Model Predictive Control to Enhance Sustainable Crop Growth

¹ Department of computers Techniques engineering, College of technical engineering, The Islamic University, Najaf, Iraq Department of computers Techniques engineering, College of technical engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq Department of computers Techniques engineering, College of technical engineering, The Islamic University of Babylon, Babylon, Iraq
² College of Pharmacy, Ahl Al Bayt University, Karbala, Iraq
³ Department of Civil, GRIET, Hyderabad, Telangana, India

^* Corresponding author: muntatheralmusawi@gmail.com

Abstract

In the quest to advance vertical farming efficiency, optimizing hydroponic nutrient management systems is essential for achieving high productivity and sustainability. This study investigates how to add advanced technologies and protocols to improve nutrient delivery as well as control environmental parameters in hydroponic systems. A Model Predictive Control (MPC) focused on the use of mathematical models to predict future states and change the nutrient solution dynamically is a core focus. The use of this approach guarantees precision in the management, and it is adjusted according to the changing demands of plants while reducing nutrient waste. Communication efficiency is addressed by using MQTT (Message Queuing Telemetry Transport) and CoAP (Constrained Application Protocol). MQTT facilitates real-time data transmission with its lightweight, publish-subscribe model, enabling effective interaction between sensors, controllers, and user interfaces. CoAP is a reliable and efficient communication by which, in resource-constrained environments, the data exchange can take place in the context of Internet of Things (IoT) applications. The study includes the use of the Bosch BME280 sensor to monitor the temperature, humidity, and pressure to maintain optimal growing conditions. Simultaneously, the TDC-GP30 sensor is used to measure carbon dioxide (C02) levels, allowing plant respiration and the total system performance to be determined. This helps to form a critical part of a comprehensive environmental monitoring system to be able to respond quickly and more easily support plant health. These technologies are integrated, whereby the aim is to achieve multiple key objectives, such as optimizing nutrient delivery for improved yield, enhancing environmental control for optimal growing conditions, and encouraging sustainable growing practices. The study shows that it is possible to hugely enhance the efficiency and productivity of vertical farming systems by utilizing advanced control algorithms and exact monitoring of vertical channels. The implementation of MPC reduced the nutrient waste by 15% and crop yields by 20%. This increased data transmission efficiency by 25 percent using the MQTT and CoAP protocols, and kept a Bosch BME280 sensor at optimal growing conditions, at a temperature accuracy of ±0.5°C and humidity accuracy of ±3%. In terms of accuracy, the TDC-GP30 sensor determined C02 levels with ±5ppm. These advancements overall were equivalent to a 30 percent improvement in vertical farm efficiency, providing not just increases in productivity but also increases in sustainability.