Enhancing Agricultural Efficiency with Uav-Aided Smart Irrigation Systems

  • Samaila Umaru
  • Muyideen Omuya Momoh
  • Muhammad Habib Mohammed
  • Reuben Ambi Shekarau
  • Ameer Mohammed
  • Aminu Sahabi Abubakar
Keywords: Unmanned Aerial Vehicle, Precision Agriculture, Sensor, Smart irrigation, Real-time

Abstract

Agriculture faces a critical obstacle: the limited availability of timely, precise data needed for effective decision-making and farm
operations. To maximize production, minimize expenses, and increase yields, farmers need immediate access to actionable
information. Technology-driven crop management approaches, known as precision agriculture, present transformative opportunities
for agricultural stakeholders. Among these technological advances, unmanned aerial vehicles (UAVs) have emerged as innovative
instruments that deliver multiple advantages. When outfitted with sophisticated sensors, these aerial platforms can acquire high
resolution imagery, track biological and environmental stress factors, identify pest infestations and plant diseases, and support
targeted spraying and pollination activities. UAV applications extend to monitoring livestock, tracking natural resources, and various
other functions. Through UAV deployment, farmers obtain vital field and environmental data at significantly lower costs compared
to conventional approaches. The substantial data volumes produced by UAVs enable analytical processes that yield practical
recommendations, resulting in heightened agricultural output, minimized resource waste, and improved environmental stewardship.
This study examines the contemporary application of UAVs in farming contexts, intelligent irrigation technologies, and opportunities
for their combined implementation to advance agricultural efficiency and ecological sustainability.

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Published
2025-12-04
How to Cite
Umaru, S., Momoh, M., Mohammed, M., Shekarau, R., Mohammed, A., & Abubakar, A. (2025). Enhancing Agricultural Efficiency with Uav-Aided Smart Irrigation Systems. International Journal of Artificial Intelligence & Mathematical Sciences, 4(1), 19-35. https://doi.org/10.58921/ijaims.v4i1.139