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Tarımsal Akıllı Sulama Sistemlerinde Yapay Zekâ, Derin Öğrenme ve Nesnelerin İnterneti Uygulamaları

Artificial Intelligence, Deep Learning, and Internet of Things Applications in Agricultural Smart Irrigation Systems

Hasan Şahin(HARRAN ÜNİVERSİTESİ)0000-0002-3977-4252
Sayfa
41–60
Yayın Tarihi
2024-04-30
DOI
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Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Büyük ölçekli tarımsal alanların etkili, doğru ve optimum bir şekilde sulanabilmesi için farklı sensörler, uydu görüntüleri, hava tahmin değerleri ve otomatik kontrol elemanlarından oluşan sistemlerin kullanımı önerilmektedir.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Tarımsal sulamada su yönetimi, şüphesiz en önemli başlıklardan birisidir.
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Temel Bulgular & Veri:Akıllı sulama sistemleri orta ölçekli çiftçiler için de önerilebilmektedir ancak sistemin verimliliği; sulanan tarım alanının büyüklüğü, arazi topoğrafyası, ürün çeşidi, su kaynağı, çevresel faktörler gibi farklı parametrelere bağlıdır.
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Sonuç & Katkı:Büyük ölçekli tarımsal alanların etkili, doğru ve optimum bir şekilde sulanabilmesi için farklı sensörler, uydu görüntüleri, hava tahmin değerleri ve otomatik kontrol elemanlarından oluşan sistemlerin kullanımı önerilmektedir.
🔬Tür:Uygulamalı Anket & Alan Araştırması
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Akıllı Sulama · Su Temini · Yapay Zeka

Özet

Tarımsal sulamada su yönetimi, şüphesiz en önemli başlıklardan birisidir. Tarımsal sulama amaçlı su tedarikinin, gündemde olan iklim değişikliği, küresel ısınma ve su krizi gibi hususlar da göz önüne alındığında, ileriki zamanlarda çok daha önemli bir sorun olarak karşımıza çıkacağı tahmin edilmektedir. Bu yüzden, tarımsal sulamada su kullanımının optimizasyonu ile su kaybının en aza indirilmesi gerekmektedir. Son zamanlarda, bu endişelerle, tarımsal sulamada yapay zekâ (AI) yönetimi, derin öğrenme (DL) teknikleri ve nesnelerin interneti (IoT) uygulamalarından faydalanılmaktadır. Akıllı sulama sistemleri orta ölçekli çiftçiler için de önerilebilmektedir ancak sistemin verimliliği; sulanan tarım alanının büyüklüğü, arazi topoğrafyası, ürün çeşidi, su kaynağı, çevresel faktörler gibi farklı parametrelere bağlıdır. Büyük ölçekli tarım alanları için akıllı sulama sistemlerinin kullanımı, su kaynaklarının azalmasından dolayı daha da zorunlu hale gelmektedir. Büyük ölçekli tarımsal alanların etkili, doğru ve optimum bir şekilde sulanabilmesi için farklı sensörler, uydu görüntüleri, hava tahmin değerleri ve otomatik kontrol elemanlarından oluşan sistemlerin kullanımı önerilmektedir. Ancak, akıllı sulama sistemleri ve diğer yeni tarım teknolojilerinin kullanımı özendirilirken, çiftçilerin de ilgili kurumlar tarafından bilgilendirilerek yanlış teknolojilere yatırım yapmalarının önlenmesi konusu unutulmaması gereken önemli bir husustur. Yeni tarım teknolojilerinde ithalat yerine, yerli üretimin teşvik edilmesi ve kamu kurumlarının koordinasyonu sağlanmalıdır.

Abstract

Water management in agricultural irrigation is undoubtedly one of the most important topics. Considering the current issues such as climate change, global warming, and the water crisis, water supply for agricultural irrigation purposes is expected to emerge as a much more important problem in the future. Therefore, water loss should be minimized by optimizing water use in agricultural irrigation. Recently, with these concerns, Artificial Intelligence (AI) management, Deep Learning (DL) techniques, and Internet of Things (IoT) applications have been utilized in agricultural irrigation. Smart irrigation systems can also be recommended for medium-scale farmers however the efficiency of the system depends on different parameters, such as the size of the irrigated agricultural area, land topography, product type, water source, and environmental factors. The use of smart irrigation systems for large-scale agricultural areas is becoming more necessary due to the decrease in water resources. To irrigate large agricultural areas effectively, accurately, and optimally, it is recommended to use a system consisting of different sensors, satellite images, weather forecast data, and automatic control systems. However, while promoting the use of smart irrigation systems and other new agricultural technologies, it is important issue that not to overlook the need to inform farmers by relevant institutions to prevent them from investing in the wrong technologies. Instead of importing new agricultural technologies, promoting domestic production and ensuring coordination among public institutions should be facilitated.

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Bu Makaleye Atıf Yap

Şahin, H. (2024). Tarımsal Akıllı Sulama Sistemlerinde Yapay Zekâ, Derin Öğrenme ve Nesnelerin İnterneti Uygulamaları. Tarım Makinaları Bilimi Dergisi, Cilt: 20 Sayı: 1, 41–60. https://ajindex.com/articles/1276929

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