Artificial Intelligence Approach of Context-Awareness Architecture for Mobile Computing

Wireless network carriers are expanding their data services to combat the shrinking average revenue per user in the face of challenges from competitive markets and emerging technologies such as VOIP. Context-aware applications, built on the notions of human computer interfaces and interaction, extract user data, analyze user patterns, and infer user intentions in a given environment. The objective of this study is to design an intelligent architecture that is based on an integrated platform that provides a context-aware solution for mobile users. The major components of the architecture are smart proxy on the user devices and context-aware search engine in the carrier's network. Context weights and profiles are automatically generated to reflect the mobile user's contextual change. The smart proxy computes context weights by utilizing a dynamic neural network based algorithm and adapts to user situation. At the server side, the context-aware search engine returns query results based on the context profiles sent by client proxy. As such, a systematic approach can be used to handle context awareness for mobile users