An Overview of Location Semantics Technologies and Applications

Author:

Ma Shang1,Liu Qiong2,Tang Henry2

Affiliation:

1. Department of EECS, University of California Irvine, Irvine, California 92612, USA

2. FX Palo Alto Laboratory, Palo Alto, California 94303, USA

Abstract

A localization system is a coordinate system for describing the world, organizing the world, and controlling the world. Without a coordinate system, we cannot specify the world in mathematical forms; we cannot regulate processes that may involve spatial collisions; we cannot even automate a robot for physical actions. This paper provides an overview of indoor localization technologies, popular models for extracting semantics from location data, approaches for associating semantic information and location data, and applications that may be enabled with location semantics. To make the presentation easy to understand, we will use a museum scenario to explain the pros and cons of different technologies and models. More specifically, we will first explore users' needs in a museum scenario. Based on these needs, we will then discuss advantages and disadvantages of using different localization technologies to meet these needs. From these discussions, we can highlight gaps between real application requirements and existing technologies, and point out promising localization research directions. Similarly, we will also discuss context information required by different applications and explore models and ontologies for connecting users, objects, and environment factors with semantics. By identifying gaps between various models and real application requirements, we can draw a roadmap for future location semantics research.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Linguistics and Language,Information Systems,Software

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Sparse sensing data–based participant selection for people finding;International Journal of Distributed Sensor Networks;2019-04

2. WiLabel: Behavior-Based Room Type Automatic Annotation for Indoor Floorplan;IEEE Access;2019

3. Foglight: Visible Light-Enabled Indoor Localization System for Low-Power IoT Devices;IEEE Internet of Things Journal;2018-02

4. Semantic localization;Encyclopedia with Semantic Computing and Robotic Intelligence;2017-03

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