Big data has arrived. Myriad applications, systems generate data of humongous volumes, variety and velocity which traditional computing systems and databases are unable to manage. The proliferation of sensors in every possible device is also becoming one of the major generators of Big data. Of particular interest in this article is how context aware computing systems which derive context from data and act accordingly, deal with such huge amounts of data. Big industry players namely Google, Yahoo, and Amazon are already developing context aware applications using user data from emails, chat messages, browsing and shopping histories etc. For instance, Gmail reminds us of our flight schedule by understanding flight booking related content in our emails. Similarly, Amazon understands user preference and recommends items of interest to shop and so on. In this paper, we survey context aware computing systems from a Big data perspective. We first propose a taxonomy of existing work on the basis of sensing platforms and then discuss the latest developments in this field of Big data context aware systems focusing on how such systems deal with various Big data challenges. We conclude the paper with an insight on open research issues involving designing and developing context aware Big data generating systems.

大数据已经到来。无数的应用程序和系统生成大量数据，种类和速度，而传统计算系统和数据库无法管理这些数据。传感器在各种可能的设备中的泛滥也正成为大数据的主要产生者之一。本文特别感兴趣的是上下文感知计算系统如何从数据中获取上下文并据此采取行动，以处理如此大量的数据。Google，Yahoo和Amazon等大型行业参与者已经在使用来自电子邮件，聊天消息，浏览和购物历史记录等的用户数据来开发上下文感知应用程序。例如，Gmail通过了解电子邮件中与航班预订相关的内容来提醒我们航班时刻表。同样，亚马逊了解用户的喜好并推荐要购物的物品等等。在本文中，我们从大数据角度调查了情境感知计算系统。我们首先基于传感平台提出现有工作的分类法，然后讨论大数据上下文感知系统在该领域的最新发展，重点是此类系统如何应对各种大数据挑战。在本文的结尾，我们对涉及设计和开发上下文感知大数据生成系统的开放研究问题有深刻见解。