1,852 research outputs found
Spatial Queries for Indoor Location-based Services
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.</p
Towards Crowd-aware Indoor Path Planning (Extended Version)
Indoor venues accommodate many people who collectively form crowds. Such
crowds in turn influence people's routing choices, e.g., people may prefer to
avoid crowded rooms when walking from A to B. This paper studies two types of
crowd-aware indoor path planning queries. The Indoor Crowd-Aware Fastest Path
Query (FPQ) finds a path with the shortest travel time in the presence of
crowds, whereas the Indoor Least Crowded Path Query (LCPQ) finds a path
encountering the least objects en route. To process the queries, we design a
unified framework with three major components. First, an indoor crowd model
organizes indoor topology and captures object flows between rooms. Second, a
time-evolving population estimator derives room populations for a future
timestamp to support crowd-aware routing cost computations in query processing.
Third, two exact and two approximate query processing algorithms process each
type of query. All algorithms are based on graph traversal over the indoor
crowd model and use the same search framework with different strategies of
updating the populations during the search process. All proposals are evaluated
experimentally on synthetic and real data. The experimental results demonstrate
the efficiency and scalability of our framework and query processing
algorithms.Comment: The extension of a VLDB'21 paper "Towards Crowd-aware Indoor Path
Planning
Advanced Location-Based Technologies and Services
Since the publication of the first edition in 2004, advances in mobile devices, positioning sensors, WiFi fingerprinting, and wireless communications, among others, have paved the way for developing new and advanced location-based services (LBSs). This second edition provides up-to-date information on LBSs, including WiFi fingerprinting, mobile computing, geospatial clouds, geospatial data mining, location privacy, and location-based social networking. It also includes new chapters on application areas such as LBSs for public health, indoor navigation, and advertising. In addition, the chapter on remote sensing has been revised to address advancements
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