Sensorium Arc: AI Agent System for Oceanic Data Exploration and Interactive Eco-Art
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911277287211008 |
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| author | Bissell, Noah Paley, Ethan Harrison, Joshua Calil, Juliano Lee, Myungin |
| author_facet | Bissell, Noah Paley, Ethan Harrison, Joshua Calil, Juliano Lee, Myungin |
| contents | Sensorium Arc (AI reflects on climate) is a real-time multimodal interactive AI agent system that personifies the ocean as a poetic speaker and guides users through immersive explorations of complex marine data. Built on a modular multi-agent system and retrieval-augmented large language model (LLM) framework, Sensorium enables natural spoken conversations with AI agents that embodies the ocean's perspective, generating responses that blend scientific insight with ecological poetics. Through keyword detection and semantic parsing, the system dynamically triggers data visualizations and audiovisual playback based on time, location, and thematic cues drawn from the dialogue. Developed in collaboration with the Center for the Study of the Force Majeure and inspired by the eco-aesthetic philosophy of Newton Harrison, Sensorium Arc reimagines ocean data not as an abstract dataset but as a living narrative. The project demonstrates the potential of conversational AI agents to mediate affective, intuitive access to high-dimensional environmental data and proposes a new paradigm for human-machine-ecosystem. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_15997 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Sensorium Arc: AI Agent System for Oceanic Data Exploration and Interactive Eco-Art Bissell, Noah Paley, Ethan Harrison, Joshua Calil, Juliano Lee, Myungin Artificial Intelligence Multimedia Sensorium Arc (AI reflects on climate) is a real-time multimodal interactive AI agent system that personifies the ocean as a poetic speaker and guides users through immersive explorations of complex marine data. Built on a modular multi-agent system and retrieval-augmented large language model (LLM) framework, Sensorium enables natural spoken conversations with AI agents that embodies the ocean's perspective, generating responses that blend scientific insight with ecological poetics. Through keyword detection and semantic parsing, the system dynamically triggers data visualizations and audiovisual playback based on time, location, and thematic cues drawn from the dialogue. Developed in collaboration with the Center for the Study of the Force Majeure and inspired by the eco-aesthetic philosophy of Newton Harrison, Sensorium Arc reimagines ocean data not as an abstract dataset but as a living narrative. The project demonstrates the potential of conversational AI agents to mediate affective, intuitive access to high-dimensional environmental data and proposes a new paradigm for human-machine-ecosystem. |
| title | Sensorium Arc: AI Agent System for Oceanic Data Exploration and Interactive Eco-Art |
| topic | Artificial Intelligence Multimedia |
| url | https://arxiv.org/abs/2511.15997 |