计算机科学
软件部署
手势
无线传感器网络
数据建模
人机交互
人工智能
机器学习
实时计算
软件工程
计算机网络
作者
Pramuka Medaranga Sooriya Patabandige,Steven Waskito,K. Li,Kai Jie Leow,Shantanu Chakrabarty,Ambuj Varshney
标识
DOI:10.1145/3581791.3597366
摘要
An important step in the deployment of wireless embedded systems is the analysis of the sensor data. Traditionally, this requires machine learning models tailored to the application use case. However, this step requires significant expertise from the end user and can be less adaptable to the dynamics of real-world deployments. In recent years, large language models have seen significant developments. These models have been shown to be capable of performing general-purpose tasks. In this work, we explore the hypothesis that large language models can be used to aid in sensor data analysis. Our preliminary findings through real-world experiments show significant promise for two tasks: inferring hand gestures through tracking of light and vibration sensor data. We believe these findings highlight the potential of large language models in sensor data analysis, and thus, it warrants further study.
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