Intelligent location models for next generation location-based services

摘要

To become truly ubiquitous, next generation location-based services (LBS) will have to rely on mobile platforms upon which multiple sensors and measurement systems have been integrated to provide continuous, three-dimensional positioning and orientation. Such technologies are explored today for example in mobile mapping systems, vehicle navigation systems and mobile robot navigation. Next-generation LBS also need theoretically sound methods to translate position into location information. The article addresses this problem: the transformation of position into meaningful and reliable location, and the transformation of location knowledge into positioning constraints. It suggests by this way an intelligent location model that integrates sensor fusion with spatial knowledge fusion via a feedback cycle. It is shown that this feedback cycle consists of three layers: spatial constraints, temporal constraints and spatiotemporal constraints.