IoT Tabanlı ve Makine Öğrenmesine Dayalı Seçici Sulama Sistemi

Abstract

Due to population growth, urbanization and climate change, competition for water resources, especially over agriculture, is expected to increase. Since the annual amount of usable water per capita in our country is around 1,500 m3, we are in the position of a country with water shortage. That's why we have to save money on the use of limited, usable water resources and be careful about using them. This planned study presents a new structure integrated data collection system and machine learning system in agricultural facilities in order to create a special irrigation reform for each product in accordance with the variety of products planted in the soil, in the gardens where various crops are grown, and to increase production efficiency with the effective and correct use of water resources. In the study, it presents the design and development of an internet-based, remote-controlled and artificial intelligence-based multi-layer system for 8 different products. The multi-layer system manages information from wireless sensor networks for information discovery and decision making in rural environments. The proposed multi-layer system allows us to analyze the data collected by the sensors to make decisions in activities carried out in a rural environment, aiming to get the best efficiency with the least water use in irrigating the crops. Since water is a scarce natural resource that should not be wasted, the proposed system aims to irrigate according to the type of product, to monitor live data, and to monitor and control all these data from anywhere via mobile devices or computers. The devices in the system are intended to be operated in all kinds of terrain. In this context, all energy needs to be used in the project will be realized through renewable energy sources (Solar Photovoltaic).