Integrated Smart System for Hydroponic Cultivation in Egypt

Abstract

Water scarcity has become the main problem all over the world. Due to climate change, lack of freshwater, and clean water resources, there are not enough resources to meet the demand that leads to an unstable Ecosystem. The recycling of water will help to reduce the problem severity. Hydroponic farming has many benefits over traditional, soil-based farming. Increased water conservation and reduced fertilizer usage. Many farmers do not work on hydroponic farms due to lack of disease control and that will result in low crops production and lack of crop quality. In this thesis, the hydroponic cultivation process is presented through a smart integrated system covering the monitoring of plant watering and recirculating of water, keeping the required percentage of nutrients for healthy planting and producing organic crops. This will make the hydroponic systems attractive, recirculating integrated systems requires very specific algorithms using Machine Learning (ML). The ML algorithm is applied to control plant growth, optimize the Electrical Conductivity (EC) values of the nutrient solution, predict plant maturity and crop quality, make smarter decisions, and take appropriate action in real-world scenarios without (or with limited) human participation. It provides a comprehensive and adaptable framework for data-driven decision-making that may be utilized in a variety of agricultural settings. On the other hand, our project plays an important role in reducing the pollution caused by the drainage water discharge as it re-uses the drained water after nutrients injection process in planting. In addition, there is no need to use herbicides, or any chemical fertilizers as weed growth will be eliminated with hydroponic systems. Herbicides or chemical fertilizers in traditional farming cause air pollution and soil contamination. All of that is covered and resolved throughout this project