A Domain-Specific Language for LLM-Driven Trigger Generation in Multimodal Data Collection
Data-driven systems depend on task-relevant data, yet data collection pipelines remain passive and indiscriminate. Continuous logging of multimodal sensor streams incurs high storage costs and captures irrelevant data. This paper proposes a declarative framework for intent-driven, on-device data collection that enables selective collection of multimodal sensor data based on high-level user requests. The framework combines natural language interaction with a formally specified domain-specific language (DSL). Large language models translate user-defined requirements into verifiable and composable DSL programs that define conditional triggers across heterogeneous sensors, including cameras, ...
| Authors | Philipp Reis, Philipp Rigoll, Martin Zehetner et al. |
|---|---|
| Primary category | cs.DB |
| Published | 13 March 2026 |
| Last updated at source | 13 March 2026 |
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