Spatial Queries for Indoor Location-based Services

被引：0
|
作者：
Liu, Tiantian [1 ]
机构：
[1] Aalborg Univ, Dept Comp Sci, Aalborg, Denmark
来源：
2022 23RD IEEE INTERNATIONAL CONFERENCE ON MOBILE DATA MANAGEMENT (MDM 2022) | 2022年
关键词：
D O I：
10.1109/MDM55031.2022.00071
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Indoor Location-based Services (LBS) facilitate people in indoor scenarios such as airports, train stations, shopping malls, and office buildings. Indoor spatial queries are the foundation to support indoor LBSs. However, the existing techniques for indoor spatial queries are limited to support more advanced queries that consider semantic information, temporal variations, and crowd influence. This work studies indoor spatial queries for indoor LBSs. Some typical proposals for indoor spatial queries are compared theoretically and experimentally. Then, it studies three advanced indoor spatial queries, a) Indoor Keyword-aware Routing Query. b) Indoor Temporal-variation aware Routing Query. c) Indoor Crowd-aware Routing Query. A series of techniques are proposed to solve these problems.
引用
收藏
页码：322 / 324
页数：3
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