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SeeNav: Seamless and Energy-Efficient Indoor Navigation using Augmented Reality

Published: 23 October 2017 Publication History

Abstract

Augmented Reality (AR) based navigation has emerged as an impressive, yet seamless way of guiding users in unknown environments. Its quality of experience depends on many factors, including the accuracy of camera pose estimation, response delay, and energy consumption. In this paper, we present SeeNav - a seamless and energy-efficient AR navigation system for indoor environments. SeeNav combines image-based localization and inertial tracking to provide an accurate and robust camera pose estimation. As vision processing is much more compute intensive than the processing of inertial sensor data, SeeNav offloads the former one from resource-constrained mobile devices to a cloud to improve tracking performance and reduce power consumption. More than that, SeeNav implements a context-aware task scheduling algorithm that further minimizes energy consumption while maintaining the accuracy of camera pose estimation. Our experimental results, including a user study, show that SeeNav provides seamless navigation experience and reduces the overall energy consumption by 21.56% with context-aware task scheduling.

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cover image ACM Conferences
Thematic Workshops '17: Proceedings of the on Thematic Workshops of ACM Multimedia 2017
October 2017
558 pages
ISBN:9781450354165
DOI:10.1145/3126686
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 23 October 2017

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Author Tags

  1. augmented reality
  2. energy efficiency
  3. indoor navigation

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  • Research-article

Funding Sources

  • Tekes: Finnish Funding Agency for Innovation
  • Academy of Finland

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MM '17
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MM '17: ACM Multimedia Conference
October 23 - 27, 2017
California, Mountain View, USA

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Cited By

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  • (2025)Review on Systems Combining Computer Vision and Radio Frequency IdentificationIEEE Internet of Things Journal10.1109/JIOT.2024.348475512:2(1291-1319)Online publication date: 15-Jan-2025
  • (2024)An Analog Neural Network for Estimating Sea State or Wave Height from Inertial Sensor Data2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS)10.1109/AICAS59952.2024.10595926(238-242)Online publication date: 22-Apr-2024
  • (2024)Reliability and Accuracy of Indoor Warehouse Navigation Using Augmented RealityIEEE Access10.1109/ACCESS.2024.342073212(94506-94519)Online publication date: 2024
  • (2024)A Cross Platform Mobile Application for Indoor NavigationIntelligent Systems and Applications10.1007/978-3-031-66329-1_6(78-89)Online publication date: 31-Jul-2024
  • (2024)ReferencesMobile Edge Computing and Communications10.1002/9781119611646.refs(209-243)Online publication date: 27-Dec-2024
  • (2023)Is This Right for You?: The Key Role of Shop Assistants in Promoting Energy-Efficient Household AppliancesSustainability10.3390/su15241663015:24(16630)Online publication date: 7-Dec-2023
  • (2023)UbiPose: Towards Ubiquitous Outdoor AR Pose Tracking using Aerial MeshesProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3613263(1-16)Online publication date: 2-Oct-2023
  • (2023)A systematic review of application development in augmented reality navigation researchCartography and Geographic Information Science10.1080/15230406.2023.219403250:3(249-271)Online publication date: 9-May-2023
  • (2021)Cloud Platforms for Context-Adaptive Positioning and Localisation in GNSS-Denied Scenarios—A Systematic ReviewSensors10.3390/s2201011022:1(110)Online publication date: 24-Dec-2021
  • (2021)An Indoor Navigation Methodology for Mobile Devices by Integrating Augmented Reality and Semantic WebSensors10.3390/s2116543521:16(5435)Online publication date: 12-Aug-2021
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