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Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

机译:预期的移动计算:技术发展现状和研究挑战

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摘要

Today's mobile phones are far from the mere communication devices they were 10 years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting, and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.
机译:今天的移动电话已经远非十年前的单纯通信设备。配备先进的传感器和先进的计算硬件,电话可用于推断用户的位置,活动,社交环境等。随着设备变得越来越智能,它们的功能已经从推断上下文发展到对其进行预测,然后对预测的上下文进行推理并采取行动。本文概述了移动传感和上下文预测的最新技术,为全面的预期移动计算铺平了道路。我们对移动电话可以推断和预测的现象进行了概述,并提供了用于此类预测的机器学习技术的描述。然后,我们讨论通过用户设备反馈回路进行的主动决策和决策交付。最后,我们讨论了预期的移动计算的挑战和机遇。

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