Smartphone‐based Lifelog (automatically annotating the users' daily experience from multisensory streams on smartphones) is in great need. Accurate positioning under any situation is one of the most significant techniques for a desirable Lifelog. This paper proposes to detect location‐related activities and use the activity information to improve positioning accuracy. In the proposed system, a human activity recognition module is developed to extract location‐related activities from multisensory streams of smartphones. After that, the proposed system integrates activity information with PDR‐based positioning results in a context‐based map‐matching framework. The developed system can be used for both outdoor and indoor scenarios. Moreover, the developed indoor positioning method is used to determine the positions of calibration points automatically in an auto‐calibration Wi‐Fi positioning system. The proposed methods achieve 3.1‐m accuracy in outdoor and average 2.2‐m accuracy in indoor situations.

中文翻译：

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城市市区生活日志的定位和活动上下文信息的集成

非常需要基于智能手机的Lifelog（通过智能手机上的多传感器流自动注释用户的日常体验）。在任何情况下准确定位都是理想Lifelog的最重要技术之一。本文建议检测与位置有关的活动，并使用活动信息来提高定位精度。在提出的系统中，开发了人类活动识别模块，以从智能手机的多传感器流中提取与位置相关的活动。之后，拟议的系统将活动信息与基于PDR的定位结果集成在基于上下文的地图匹配框架中。开发的系统可用于室外和室内场景。此外，开发的室内定位方法用于在自动校准Wi-Fi定位系统中自动确定校准点的位置。所提出的方法在室外达到3.1-m的精度，在室内情况下达到2.2-m的平均精度。