期刊名称：Bulletin of the Technical Committee on Data Engineering
出版年度：2010
卷号：33
期号：02
出版社：IEEE Computer Society
摘要：Much research has been conducted on the management of outdoor moving objects. In contrast, rel-
atively little research has been conducted on indoor moving objects. The indoor setting differs from
outdoor settings in important ways, including the following two. First, indoor spaces exhibit complex
topologies. They are composed of entities that are unique to indoor settings, e.g., rooms and hallways
that are connected by doors. As a result, conventional Euclidean distance and spatial network distance
are inapplicable in indoor spaces. Second, accurate, GPS-like positioning is typically unavailable in in-
door spaces. Rather, positioning is achieved through the use of technologies such as Bluetooth, Infrared,
RFID, or Wi-Fi. This typically results in much less reliable and accurate positioning.
This paper covers some preliminary research that explicitly targets an indoor setting. Specifically,
we describe a graph-based model that enables the effective and efficient tracking of indoor objects
using proximity-based positioning technologies like RFID and Bluetooth. Furthermore, we categorize
objects according to their position-related states, present an on-line hash-based object indexing scheme,
and conduct an uncertainty analysis for indoor objects. We end by identifying several interesting and
important directions for future research.
