Context-awareness is getting increasingly important for a range of mobile and pervasive applications on nowadays smart phones. Whereas human-centric contexts (e.g., indoor/ outdoor, at home/in office, driving/walking) have been extensively researched, few attempts have studied from phones perspective (e.g., on table/sofa, in pocket/bag/hand). We refer to such immediate surroundings as micro environment, usually several to a dozen of centimetres, around a phone. In this study, we design and implement micro-environment sensing platform that automatically records sensor hints and characterizes the micro-environment of smart phones. The platform runs as a daemon process on a Smart phone and provides finer-grained environment information to upper layer applications via programming interfaces. It is a unified framework covering the major cases of phone usage, placement, attitude, and interaction in practical uses with complicated user habits. As a long-term running middleware, it considers both energy consumption and user friendship. The preliminary results show that it achieves low energy cost, rapid system deployment, and competitive sensing accuracy. We are going to make use of that data by reading and converting it into ASCII format. We will be developing various applications using that data for security as well as for saving the battery of mobile. The sensors which we are going to use in our project are Accelerometer, Light, Pressure, Proximity etc.
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