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AI and Semantic Communication for Infrastructure Monitoring in 6G-Driven Drone Swarms

2025/02/26 by Tasnim Ahmed, Ahmed, Tasnim, Salimur Choudhury +1
Computer Science · Engineering · #Advanced Data and IoT Technologies #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Organizational and Employee Performance #Robotics (cs.RO) #UAV Applications and Optimization

paper · pdf · doi:10.48550/arxiv.2503.00053

openalex publication_date 2025/02/26 · openalex created_date 2025/10/12 · openalex updated_date 2026/07/28

Abstract

The adoption of unmanned aerial vehicles to monitor critical infrastructure is gaining momentum in various industrial domains. Organizational imperatives drive this progression to minimize expenses, accelerate processes, and mitigate hazards faced by inspection personnel. However, traditional infrastructure monitoring systems face critical bottlenecks-5G networks lack the latency and reliability for large-scale drone coordination, while manual inspections remain costly and slow. We propose a 6G-enabled drone swarm system that integrates ultra-reliable, low-latency communications, edge AI, and semantic communication to automate inspections. By adopting LLMs for structured output and report generation, our framework is hypothesized to reduce inspection costs and improve fault detection speed compared to existing methods.

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