Sustainable and Energy Efficient Agriculture with Artificial Intelligence Adoption

Agriculture is crucial for global food security. Traditional farming methods are insufficient to meet the growing demands from population growth, climate change, and limited resources. With the world’s population expected to reach almost 9 billion in the next decade, food systems, water resources, and agricultural productivity will face more pressure. This paper examines how AI can help develop efficient and sustainable farming systems based on data. AI can improve crop monitoring, yield predictions, soil analysis, and pest management by using various weather data, including rainfall, temperature, humidity, wind, and storm forecasts, allowing for timely actions. A major focus of this study is how AI can optimize resource use, especially in irrigation and weed control. Research shows that soil-water sensing technologies in AI-based smart irrigation systems can reduce water consumption by up to 25 percent. This reduction is vital for areas dealing with water shortages. Robotic and AI-driven precision weeding methods decrease reliance on herbicides and manual labor, lowering energy use and improving environmental sustainability. Using drones for spraying and crop monitoring boosts efficiency by accurately targeting problem areas, reducing chemical waste, and minimizing production losses. This study reviews the existing literature and analyzes the benefits, challenges, and practical issues of adopting AI in agriculture. It considers international examples, such as India’s AI4AI initiative, AI-supported weeding systems in Africa, and a proposed AI framework for agriculture in the Konya Province in Türkiye. It is important to emphasize that this framework is purely conceptual and illustrative, and does not represent an implemented pilot or empirical application. The findings show that while AI could greatly improve food security, resource use, and climate resilience, barriers like low digital literacy, high implementation costs, and infrastructure issues limit its wider use. Overall, the study concludes that AI is not merely a technological upgrade; it is essential for creating sustainable and energy-efficient agricultural systems in the future.

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