(untitled) (Journal of Advanced Artificial Intelligence Research, 2026)
The integration of unmanned aerial vehicle swarms into precision agriculture promises transformative improvements in crop monitoring, resource allocation, and yield management. However, the operational energy demands of sustained aerial coverage impose severe constraints on mission duration and geographical scope, particularly in remote farming regions lacking charging infrastructure. This paper presents a comprehensive systems-level investigation into energy-aware coverage optimization for solar-assisted UAV swarms deployed in precision farming. We propose an architectural framework that couples photovoltaic energy harvesting with adaptive swarm coordination algorithms to maximize spatial coverage while respecting real-time energy budgets. The analysis examines structural trade-offs between solar panel sizing, battery capacity, flight dynamics, and coverage redundancy. Infrastructure considerations such as decentralized energy management, ground-based replenishment stations, and cloud-based supervisory control are addressed. Governance and policy dimensions, including regulatory frameworks for autonomous swarm operations, data sovereignty in agricultural analytics, and equitable access to drone-based farming services, are critically assessed. The discussion extends to robustness concerns under variable weather conditions and the fairness implications of algorithmically assigned coverage schedules for heterogeneous farmlands. A comparative evaluation of existing swarm coordination strategies highlights the need for context-aware optimization that balances energy efficiency with agronomic precision. By synthesizing insights from robotics, renewable energy systems, and socio-technical infrastructure studies, this paper advances a holistic perspective on sustainable UAV swarm operations. The findings underscore that achieving long-term viability in precision agriculture requires not only technical innovation in energy-aware path planning but also aligned institutional, economic, and policy frameworks. The proposed system architecture and analytical lens offer a foundation for future empirical deployments and interdisciplinary research at the intersection of autonomous systems, agricultural sustainability, and energy informatics.