4.7 Article

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

期刊

ACM COMPUTING SURVEYS
卷 47, 期 3, 页码 -

出版社

ASSOC COMPUTING MACHINERY
DOI: 10.1145/2693843

关键词

Design; Human Factors; Performance; Anticipatory computing; mobile sensing; context-aware systems

资金

  1. EPSRC [EP/I032673/1]
  2. EPSRC [EP/I032673/1] Funding Source: UKRI
  3. Engineering and Physical Sciences Research Council [EP/I032673/1] Funding Source: researchfish

向作者/读者索取更多资源

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.

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