Distributed acoustic sensing system integrable with AI agents

Distributed acoustic sensing (DAS) technology, with its high sensitivity, long-range coverage, and strong immunity to electromagnetic interference, has been widely applied in fields such as perimeter security, traffic monitoring, energy pipelines, and seismic observation. However, conventional DAS systems are mostly limited to signal acquisition and basic processing, lacking the capability to respond intelligently to complex noise and multi-source disturbances. This paper proposes a collaborative framework that integrates a front-end DAS unit with a back-end AI agent to achieve deep fusion between optical fiber sensing and intelligent decision-making. The front end performs signal acquisition and demodulation, while the AI agent employs deep learning for pattern recognition and event prediction, significantly enhancing recognition accuracy, robustness, and real-time responsiveness. Finally, the paper discusses future trends in the integration of DAS and AI agents, highlighting their potential in building multi-scenario intelligent sensing and proactive decision-making systems.