Information Abstraction and Knowledge Acquisition from Real-World Data

Abstract: This research focuses on enabling heterogeneous sensor devices to con-nect and communicate their data on the Internet and develops software systems than can interpret this data and create human understandable or machine-interpretable perceptions from the data. The software mechanisms collect and process the sensor data, identify different patterns and create higher-level abstractions from the data according to the context of the sensor device. This research develops some of the key components that are used as enabling solutions for the Internet of Things. 1 Main Objective and Motivation There is a growing demand for new information processing techniques and meth-ods that are able to process the myriad of data that is collected by sensory devices and mobile users. It is predicted that in the next 5-10 years there will be around 50 billion Internet connected devices that will produce 20 % of non-video Internet traffic. The devices include sensor nodes, smart phones, GPS and many other sources that capture and communicate the real world data. This deluge of data requires efficient mecha-nisms to address the data communication and data management challenges for th