IoT Driven Ambient Intelligence Architecture for Indoor Intelligent Mobility.pdf (536.38 kB)

IoT driven ambient intelligence architecture for indoor intelligent mobility

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conference contribution
posted on 17.10.2018, 10:49 by Varuna De Silva, Jamie Roche, Xiyu Shi, Ahmet Kondoz
Personal robots are set to assist humans in their daily tasks. Assisted living is one of the major applications of personal assistive robots, where the robots will support health and wellbeing of the humans in need, especially elderly and disabled. Indoor environments are extremely challenging from a robot perception and navigation point of view, because of the ever-changing decorations, internal organizations and clutter. Furthermore, human-robot-interaction in personal assistive robots demands intuitive and human-like intelligence and interactions. Above challenges are aggravated by stringent and often tacit requirements surrounding personal privacy that may be invaded by continuous monitoring through sensors. Towards addressing the above problems, in this paper we present an architecture for "Ambient Intelligence" for indoor intelligent mobility by leveraging IoTs within a framework of Scalable Multi-layered Context Mapping Framework. Our objective is to utilize sensors in home settings in the least invasive manner for the robot to learn about its dynamic surroundings and interact in a human-like manner. The paper takes a semi-survey approach to presenting and illustrating preliminary results from our in-house built fully autonomous electric quadbike.

History

School

  • Loughborough University London

Published in

The 3rd IEEE Cyber Science and Technology Congress

Citation

DE SILVA, V. ... et al, 2018. IoT driven ambient intelligence architecture for indoor intelligent mobility. IN: 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech), Athens, Greece, 12-15 August 2018, pp.451-456.

Publisher

© IEEE

Version

AM (Accepted Manuscript)

Publication date

2018

Notes

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

ISBN

9781538675182

Language

en

Location

Athens, Greece

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