DOI: https://doi.org/10.36719/2789-6919/46/163-166
Nurlan Eyvazov
Azerbaijan State Technical University
Master student
https://orcid.org/0009-0002-2532-2789
nurlan.elvazov@gmail.com
Mikayil Huseynzadeh
Azerbaijan State Technical University
Master student
https://orcid.org/0009-0006-7637-3892
huzeynzade.mikail2807@gmail.com
Agrotechnical Efficiency of Irrigation Systems Controlled by Artificial Intelligence
Abstract
Efficient and economical management of irrigation systems in agriculture is considered one of the main priorities of global food security and sustainable production in the modern era. Traditional irrigation systems, often based on fixed schedules, do not take into account soil and plant needs in real time, which leads to water waste and reduced productivity. The application of artificial intelligence (AI) technologies plays an important role in overcoming these problems. Artificial intelligence-controlled irrigation systems automatically make irrigation decisions in real time based on soil moisture levels, weather forecasts, solar radiation, plant development stage and other agrotechnical indicators. These technologies collect, analyze data and apply optimal irrigation strategies through machine learning and sensor networks. As a result, water consumption can be reduced by 30–50%, and productivity can increase by 20–40%. In addition, these systems facilitate the timely and correct implementation of agrotechnical measures, prevent soil salinization and create conditions for sustainable use of water resources. The application of artificial intelligence also contributes to reducing operating costs for farmers, improving agro-ecological conditions and increasing the technological level of agricultural production in general.
Keywords: agrotechnical, sensor, irrigation, agrarian, digital