Automatic Data-Driven Agriculture System for Hydroponic Farming

Abstract

Until 2050, global urbanization will increase to 2.4 billion cities and towns. As the population grows, so does the consumption of fruits and vegetables. There will be a need for agricultural land and water resources. Nowadays, hydroponics is gaining popularity due to the plants exceedingly high quality and not required the large space and resources as like traditional planting. In this paper, a system which will be automatically control Electrical Conductivity (EC), Total dissolved solids (TDS), liquid levels, and power of hydrogen (pH) values is proposed to improve the Hydroponics Planting. This system is developed based on Neural Network for auto adjusting the value of hydrogen(pH) and nutrient in lettuce farm. It is designed to enable seamless data collection from various kinds of sensors in urban farm condition. The deployment of proposed system is tested in indoor urban farming environment. Through the experimental results, the proposed system can effectively regulate water and nutrients by assisting plant growth.