AI and Semantic Communication for Infrastructure Monitoring in 6G-Driven Drone Swarms
This addresses the problem of costly and slow infrastructure monitoring for industries using drones, though it appears incremental as it builds on existing drone and AI technologies with 6G enhancements.
The paper tackles the problem of inefficient infrastructure monitoring by proposing a 6G-enabled drone swarm system that integrates ultra-reliable, low-latency communications, edge AI, and semantic communication to automate inspections, hypothesizing it will reduce costs and improve fault detection speed compared to existing methods.
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.