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Integration of mobile devices in home automation with use of machine learning for object recognition

Published: 29 January 2021 Publication History

Abstract

The number of smart homes is increasingly expanding, with even more connected devices and available control options. Mobile devices have unfortunately been up to now generally regarded as mere remote controls in these environments.
This paper addresses this shortcoming, by presenting a novel integration architecture and prototype where the potential of mobile devices sensors can be better explored in home automation platforms, in particular by detecting objects in the information collected by their cameras that subsequently allow for users to interact with them in an intuitive way. The detection is performed at the mobile side, using a lightweight machine learning solution.
The obtained accuracy and processing time are comparable to that obtained at server side. But the advantage here is that the interactive experience of users can be dramatically improved, with the absence of round-trip time required if server processing would be used.

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Cited By

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  • (2023)Potential and Challenges of DIY Smart Homes with an ML-intensive Camera SensorProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581462(1-19)Online publication date: 19-Apr-2023

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Published In

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EATIS '20: Proceedings of the 10th Euro-American Conference on Telematics and Information Systems
November 2020
388 pages
ISBN:9781450377119
DOI:10.1145/3401895
This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 January 2021

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Author Tags

  1. internet of things
  2. smart homes

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  • Research-article

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  • Fundação para a Ciência e a Tecnologia

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EATIS 2020

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Overall Acceptance Rate 17 of 64 submissions, 27%

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View all
  • (2023)Potential and Challenges of DIY Smart Homes with an ML-intensive Camera SensorProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581462(1-19)Online publication date: 19-Apr-2023

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