Artificial Intelligence Based Soilless Agriculture System Using Automatic Hydroponics Architecture

The conventional practices of farming vegetables are inherently associated with the shortage of vegetables due to its seasonal nature, limited farming land and continuous demand. The introduction of artificial means of vegetable production is labor-intensive because of the processes involved in this paper an Artificial Intelligence (AI) based Nutrient Film Technique (NFT) hydroponics system will be designed to mitigate the shortage of vegetable production and minimizes labor. AI will be coded into the ATMEGA328P microcontroller using C++ to provide the required automatic control necessary for the NFT pumps and valves, while Attention Commands (AT) will be used for the interfaced Sim900 Global System for Mobile Communication (GSM) modem for sending Short Message Service (SMS) to the farm operator in case of any malfunction. The improved NFT is found to maximize farmland sine layers of plants can be arranged on one another at a given distance apart, which varies from plant to plant. The AI minimizes human intervention and provides exact mixing and supply of balanced nutrients to plants for fast growth and healthy plants. Continuous production throughout the year using precise AI techniques was designed. Therefore, an improved user-friendly NFT was achieved by utilizing AI embedded in a microcontroller.