An Assessment of Autonomous Navigation Systems for Drones in Northern Nigeria: A Case Study of Sokoto State University
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1.1 Background of the Study
Drones have become an essential tool for various applications, including surveillance, agriculture, and disaster management. The integration of Artificial Intelligence (AI) into autonomous navigation systems has significantly enhanced drone operations, enabling real-time decision-making, obstacle avoidance, and precise navigation. In Northern Nigeria, autonomous drones have the potential to address challenges in agriculture, security, and logistics.
Sokoto State University has been at the forefront of research and development in drone technology, focusing on AI-driven navigation systems to improve operational efficiency and reliability. This study examines the role of AI in enhancing autonomous drone navigation and its implications for socio-economic development in Northern Nigeria (Bello & Yusuf, 2025).
1.2 Statement of the Problem
Despite the potential of autonomous drones, their deployment in Northern Nigeria faces challenges such as limited infrastructure, technical expertise, and regulatory barriers. The lack of efficient navigation systems further restricts the widespread use of drones in critical sectors.
1.3 Objectives of the Study
- To evaluate the use of AI in autonomous drone navigation systems in Northern Nigeria.
- To assess the impact of AI-driven navigation systems on drone operations.
- To identify challenges limiting the adoption of autonomous drones in Northern Nigeria.
1.4 Research Questions
- How is AI being used in autonomous drone navigation systems in Sokoto State?
- What is the impact of AI on the efficiency and reliability of drone operations?
- What challenges hinder the adoption of autonomous drones in Northern Nigeria?
1.5 Research Hypothesis
- AI significantly enhances the efficiency of autonomous drone navigation systems.
- AI-driven drones improve operational outcomes in critical sectors such as agriculture and security.
- Infrastructure and regulatory challenges limit the adoption of autonomous drones.
1.6 Significance of the Study
This study highlights the potential of AI-driven navigation systems in improving drone applications, offering practical recommendations for researchers, policymakers, and industries.
1.7 Scope and Limitations of the Study
The study focuses on Sokoto State University’s research on AI-driven drone navigation systems and their applications in Northern Nigeria. Limitations include restricted access to proprietary navigation technologies and variability in drone deployment conditions.
1.8 Operational Definition of Terms
- Autonomous Navigation Systems: AI-driven systems enabling drones to operate without human intervention.
- Drones: Unmanned aerial vehicles used for surveillance, agriculture, and logistics.
- Obstacle Avoidance: The ability of drones to detect and avoid obstacles during flight.
- Logistics: The transportation and delivery of goods using drones.
Operational Efficiency: The effectiveness of drones in performing tasks with minimal errors and delays.
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