Instinctive Assistive Indoor Navigation using Distributed Intelligence

Md Muztoba, Rohit Voleti, Fatih Karabacak, Jaehyun Park, Umit Ogras

Research output: Contribution to journalArticle

Abstract

Cyber-physical systems (CPS) and the Internet of Things (IoT) offer a significant potential to improve the effectiveness of assistive technologies for those with physical disabilities. Practical assistive technologies should minimize the number of inputs from users to reduce their cognitive and physical effort. This article presents an energy-efficient framework and algorithm for assistive indoor navigation with multi-modal user input. The goal of the proposed framework is to simplify the navigation tasks and make them more instinctive for the user. Our framework automates indoor navigation using only a few user commands captured through a wearable device. The proposed methodology is evaluated using both a virtual smart building and a prototype. The evaluations for three different floorplans show one order of magnitude reduction in user effort and communication energy required for navigation, when compared to conventional navigation methodologies that require continuous user inputs.

Original languageEnglish (US)
Article number80
JournalACM Transactions on Design Automation of Electronic Systems
Volume23
Issue number6
DOIs
StatePublished - Dec 2018

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Keywords

  • Assistive technologies
  • Human-machine interface
  • IoT devices
  • Wearable computers

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering

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