Summary of Layout Agnostic Human Activity Recognition in Smart Homes Through Textual Descriptions Of Sensor Triggers (tdost), by Megha Thukral et al.
Layout Agnostic Human Activity Recognition in Smart Homes through Textual Descriptions Of Sensor Triggers (TDOST)
by Megha Thukral, Sourish Gunesh Dhekane, Shruthi K. Hiremath, Harish Haresamudram, Thomas Ploetz
First submitted to arxiv on: 20 May 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Human-Computer Interaction (cs.HC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper addresses the challenge of building human activity recognition (HAR) models for smart home environments that can generalize well across different homes. Current approaches require significant annotated data and training, which is impractical for real-world deployment. The authors propose a novel method that leverages textual descriptions of raw sensor data to create HAR systems that can predict activities across new, unseen smart homes without retraining or adaptation. The approach utilizes textual embeddings rather than raw sensor data, allowing for more effective activity recognition. The paper evaluates the effectiveness of this method on benchmarked CASAS datasets and analyzes how individual components impact downstream performance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research makes it easier to recognize human activities in smart homes. Right now, building models that can work well in different homes requires a lot of data and training time. The authors have come up with a new way to do this using text descriptions of sensor data. This lets them create models that can predict activities in new homes without needing more data or retraining. They tested their approach on some benchmark datasets and found it works well. |
Keywords
» Artificial intelligence » Activity recognition
