A Smart IoT-Based Irrigation System with Automated Plant Recognition using Deep Learning

Abstract

Machine Learning allows systems to learn and improve automatically from experiences without hand-coding. Thus, in recent years, many technology companies have been developing such application if Artificial Intelligence, from face recognition by Facebook, to the AlphaGo program by Google. The irrigation systems in the market nowadays mostly allow users to set them to a certain amount of water and at specific time intervals. However, there are usually more than one type of plants in a garden, and each species requires different amount of water. In order to resolve this issue, in this paper, we have developed an irrigation system, with the use of deep learning, that is able to adjust the amounts of water foe each type pf plant through plants recognition. There are two main parts of the solution, the software and the hardware. The prior is connected with cameras to undergo plant recognition, and utilizes database to find the suitable amount of water; the latter controls the amount of water that is able to flow out.