ISW-Agent: Integrating LLM-Driven Dialogue with n8n Workflow for Internal Solitary Wave Remote Sensing Image Processing

Key points

• Internal solitary wave (ISW) remote sensing requires task parameters and spatial information to be transferred across image acquisition, detection, stripe extraction, and propagation prediction.1
• In tests of 120 Chinese instructions per backend, GPT-5.6 Sol and DeepSeek both achieved a strict task-match rate of 94.2%, with all intents and execution decisions matching the reference.1
• Sentinel-1 cases demonstrated continuous processing from dialogue requests to wavefront prediction for the specified scene.1
• Overall, ISW-Agent thus connects natural-language requests to traceable spatial processing chains for multimodel ISW analysis.1

Sources (1)

• [1]ISW-Agent: Integrating LLM-Driven Dialogue with n8n Workflow for Internal Solitary Wave Remote Sensing Image Processing
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 15, 08:38 AM

  Here, we present ISW-Agent, which integrates large language model (LLM) interpretation with n8n workflows and independent scientific models through structured task constraints, geospatial transformations, and stage-specific output validation.

  Internal solitary wave (ISW) remote sensing requires task parameters and spatial information to be transferred across image acquisition, detection, stripe extraction, and propagation prediction.

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