Dependency-aware action planning for smart home
Jongjin Kim, Jaeri Lee, Jeongin Yun, U. Kang, Praveen Kumar Donta, Praveen Kumar Donta, Praveen Kumar Donta
TL;DR
This paper introduces SmartAid, a method for smart homes to plan actions based on user requests while considering dependencies between devices and their capabilities.
Contribution
SmartAid introduces a novel action planning method that considers dependencies in smart home systems using learned state transition models.
Findings
SmartAid successfully represents real-world devices using state transition logs.
The method generates accurate action sequences for user queries by considering dependencies.
Experiments show SmartAid outperforms existing approaches in action planning accuracy.
Abstract
How can a smart home system control a connected device to be in a desired state? Recent developments in the Internet of Things (IoT) technology enable people to control various devices with the smart home system rather than physical contact. Furthermore, smart home systems cooperate with voice assistants such as Bixby or Alexa allowing users to control their devices through voice. In this process, a user’s query clarifies the target state of the device rather than the actions to perform. Thus, the smart home system needs to plan a sequence of actions to fulfill the user’s needs. However, it is challenging to perform action planning because it needs to handle a large-scale state transition graph of a real-world device, and the complex dependence relationships between capabilities. In this work, we propose SmartAid (Smart Home Action Planning in awareness of Dependency), an action…
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Taxonomy
TopicsContext-Aware Activity Recognition Systems · IoT and Edge/Fog Computing · Robotics and Automated Systems