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Precision Agriculture with AI-Powered Drones: Enhancing Crop Health Monitoring and Yield Prediction

Author

Listed:
  • Ezeanyim Okechukwu Chiedu

    (Industrial/Production Engineering Department, Nnamdi Azikiwe University, P.M.B. 5025 Awka, Anambra State – Nigeria)

  • Okpala Charles Chikwendu

    (Industrial/Production Engineering Department, Nnamdi Azikiwe University, P.M.B. 5025 Awka, Anambra State – Nigeria)

  • Igbokwe Benjamin Nnaemeka

    (Industrial/Production Engineering Department, Nnamdi Azikiwe University, P.M.B. 5025 Awka, Anambra State – Nigeria)

Abstract

Precision Agriculture is revolutionizing modern agriculture through the utilization of advanced technologies for the optimization of crop production, minimization of environmental impact, as well as the enhancement of decision-making processes. Artificial Intelligence (AI)-powered drones are at the forefront of this transformation, providing innovative solutions for real-time monitoring of crop health, targeted interventions, and accurate yield prediction. This article examines the integration of AI in drone technology for the bolstering of the effectiveness of precision agriculture, focusing on its role in improving crop health assessments, early disease and pest detection, nutrient management, and yield forecasting. Additionally, the paper addressed key challenges, including data processing, scalability, and the integration of AI-powered drones with other agricultural technologies. As technology advances and becomes more affordable, the future of AI-driven drones promises to play a crucial role in shaping sustainable and efficient farming practices globally.

Suggested Citation

  • Ezeanyim Okechukwu Chiedu & Okpala Charles Chikwendu & Igbokwe Benjamin Nnaemeka, 2025. "Precision Agriculture with AI-Powered Drones: Enhancing Crop Health Monitoring and Yield Prediction," International Journal of Latest Technology in Engineering, Management & Applied Science, International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS), vol. 14(3), pages 156-163, March.
    • Handle: RePEc:bjb:journl:v:14:y:2025:i:3:p:156-163
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