Comprehensive Review on Automation in Hydroponic Agriculture Using Machine Learning and IoT

Abstract

When food consumption is a very important condition, it is the sector that plays an important role. Must support current conditions where there is less land for agriculture and food security. The traditional methods used by farmers today are not sufficient to serve the increasing demand, so that limited land is an important factor in developing hydroponic agriculture. The hydroponic farming proposed in this study, there are two agriculture and fisheries. Only agriculture is discussed in this study. With the development of the hydroponic farming system, this system is very suitable for the conditions that need to be developed. The most pressing need is to clarify issues such as pest control and environmental impacts in fishing practices. The methodology used in this research is image preprocessing to collect structured and unstructured data to obtain information with the help of machine learning and IoT. The proposed machine learning method is Naive Bayes. Because the Naive Bayes method in some literature is more suitable for agriculture, but still overrides accuracy. The ultimate goal is to help farmers in producing food with alternative media.