@article{e3ad4d1c88a2406c8dc33bd1affbac20,
title = "Instinctive Assistive Indoor Navigation using Distributed Intelligence",
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.",
keywords = "Assistive technologies, Human-machine interface, IoT devices, Wearable computers",
author = "Md Muztoba and Rohit Voleti and Fatih Karabacak and Jaehyun Park and Umit Ogras",
note = "Funding Information: This work was supported partially by National Science Foundation (NSF) Grants No. CNS-1651624 and No. CNS-1526562, and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (Grant No. NRF-2018R1C1B50447150). Funding Information: This work was supported partially by National Science Foundation (NSF) Grants No. CNS-1651624 and No. CNS-1526562, and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (Grant No. NRF-2018R1C1B50447150). Authors{\textquoteright} addresses: M. Muztoba, R. Voleti, F. Karabacak, and U. Y. Ogras, School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ 85281; emails: {mmuztoba, rnvoleti, fatihkarabacak, umit}@asu.edu; J. Park, School of Electrical Engineering, University of Ulsan, Ulsan, South Korea; email: jaehyun@ulsan.ac.kr. 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 permissions@acm.org. {\textcopyright} 2018 Association for Computing Machinery. 1084-4309/2018/11-ART80 $15.00 https://doi.org/10.1145/3212720 Publisher Copyright: {\textcopyright} 2018 Association for Computing Machinery.",
year = "2018",
month = dec,
doi = "10.1145/3212720",
language = "English (US)",
volume = "23",
journal = "ACM Transactions on Design Automation of Electronic Systems",
issn = "1084-4309",
publisher = "Association for Computing Machinery (ACM)",
number = "6",
}