基于活动识别的上下文感知系统研究

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2019-02-01 DOI:10.1109/ICAIIC.2019.8669035

Yuki Watanabe, Reiji Suzumura, Shogo Matsuno, M. Ohyama

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引用次数: 2

摘要

身体活动是重要的上下文信息，可以实时、详细地定义和理解用户的情况。因此，我们开发了一个使用活动识别的上下文感知功能，并表明它可以根据用户的情况提供更合适的支持。在这项研究中，我们首先通过将机器学习应用于智能手机感知的数据来构建一个模型，以预测用户的身体活动。在实验中，使用该模型获得了97.6%的准确率。接下来，我们利用活动识别开发了三个功能。这些功能可以实时预测用户的身体活动。此外，根据预测的身体活动执行用户支持。在使用开发函数的实验中，证实了这些函数在实际条件下正确工作。

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Investigation of Context-aware System Using Activity Recognition

The physical activity is important context information to define and understand the user’s situation in real time and in detail. Therefore, we developed a context-aware function using the activity recognition and showed that it is possible to provide more appropriate support according to the user’s situation. In this study, we first constructed a model by applying machine learning to data sensed by a smartphone in order to predict the physical activity of the user. In the experiment, high accuracy of 97.6% was obtained by using the model. Next, we developed three functions using the activity recognition. These functions predict the physical activity of user in real time. In addition, user support is performed according to the predicted physical activity. In the experiment using developed functions, it is confirmed that these functions worked correctly in real-world conditions.

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来源期刊

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

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