Design of Versatile Hydroponic Prototype for Efficient Genesis of Nutrient Environment - A Machine Learning Approach

Agriculture has always played a key role in the growth of the nation. The usual method of soil-based agriculture involves lots of dependencies like smaller farms, costly manures, and pesticides, etc. Also, study shows there is an immense need for organic and healthy food in recent years. In this paper we present a farming technique called hydroponics and with the power of machine learning algorithms we modify the existing passive hydroponics system to possess the novel ability to enhance the overall plant growth based on the crop type and crop’s ability to consume the nutrients. Here we grow plants in a small, enclosed area. This is a type of agriculture which can be more effective if controlled and monitored properly. In this system, we monitor and control all the necessary things which are required by plants using reinforcement learning. The data captured can generate multiple growth traits automatically using large data sets. This system can be used by home growers as well as commercial growers.