Intelligent Drone Swarm Coordination for Precision Farming and Disaster Response

Abstract

This study explores how reliable intelligent drone swarms are utilized as a single efficient bi-functional agent for precision agriculture and disaster relief support. Even though autonomous Unmanned Aerial Vehicles (UAVs) change individual sectors, traditional systems with one agent face limits in operational scale, battery duration as well as fault tolerance. This paper proposes a resilient co-design architecture based on decentralized swarm intelligence, bio-inspired optimization algorithms alongside dynamic ad-hoc networking capable of seamlessly transitioning from agricultural monitoring to search-and-rescue missions in minutes. We propose a hybrid coordination scheme, integrating Modified Particle Swarm Optimization (MPSO) and decentralized consensus protocols, allowing for near real-time avoidance of obstacles, task allocation and on-the-fly area coverage based on limited communication mapping in unstructured environments. HIL simulations and field validations over diff operational topologies show that the suggested system can decrease overall mission time by 32% and increase coverage efficiency by 24% compared to conventional centralized routing algorithms. Also, the swarm showed substantial self-healing properties even after massive nodes loss 30% active nodes) still providing 88% of operational throughput. In the end, this renewable energy and nutrient-cycling infrastructure provides an economically competitive, high-performance solution for rural resilience and resource management that reconciles the dual rescue technologies of contemporary commercial food production with advanced emergency crisis technologies.