MapNexus : a framework to derive human intent from architectural space to enable context-aware information exchanges in a wireless intranet

Abstract

Architectural interior spaces provide a rich syntax for context-aware modeling. In a wireless wide area network (WAN), an urban environment can be geographically tessellated into a series of polygons reflecting the radio transmission range of each wireless access point (AP). By using these APs as spatial aggregation units in a relational database, logical assumptions about short-term behavioral patterns can be modelled; this paper describes a method to capture, encode, and interpret context-aware cues. These cues are then utilized by an intranet web server to produce context-aware output, information that fits the client's short-term activity landscape and intentions. The method does not require any special client-side software and preserves the user's anonymity as it derives the client's physical location implicitly. Such a framework permits a new type of context-aware web interaction based upon the logical "common sense" patterns that are specific to architectural interior spaces at a given time.