Early Detection System for Gas Leakage and Fire in Smart Home Using Machine Learning

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Making houses more inclusive, safer, resilient and sustainable is an important requirement that must be achieved in every society. Gas leakage and fires in smart houses are serious issues that are causing people's death and properties losses. Currently, preventing and alerting systems are widely available. However, they are generally individual units having elementary functions without adequate capabilities of multi-sensing and interaction with the existing Machine-to-Machine (M2M) home network along with the outside networks such as Internet. Indeed, this communication paradigm will be clearly the most dominant in the near future for M2M home networks. In this paper, we are proposing an efficient system model to integrate the gas leakage and fire detection system into a centralized M2M home network using low cost devices. Then, through machine learning approach, we are involving a data mining method with the sensed information and detect the abnormal air state changes in hidden patterns for early prediction of the risk incidences. This work will help to enhance safety and protect property in smart houses.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Consumer Electronics, ICCE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538679104
DOIs
Publication statusPublished - 2019 Mar 6
Event2019 IEEE International Conference on Consumer Electronics, ICCE 2019 - Las Vegas, United States
Duration: 2019 Jan 112019 Jan 13

Publication series

Name2019 IEEE International Conference on Consumer Electronics, ICCE 2019

Conference

Conference2019 IEEE International Conference on Consumer Electronics, ICCE 2019
CountryUnited States
CityLas Vegas
Period19/1/1119/1/13

Fingerprint

Home networks
Leakage (fluid)
Intelligent buildings
Learning systems
Fires
Gases
Data mining
Internet
Communication
Air
Costs

Keywords

  • fire detection
  • gas leakage detection
  • machine learning
  • machine-to-machine
  • smart home
  • wireless sensor network

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Media Technology
  • Electrical and Electronic Engineering

Cite this

Salhi, L., Silverston, T., Yamazaki, T., & Miyoshi, T. (2019). Early Detection System for Gas Leakage and Fire in Smart Home Using Machine Learning. In 2019 IEEE International Conference on Consumer Electronics, ICCE 2019 [8661990] (2019 IEEE International Conference on Consumer Electronics, ICCE 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE.2019.8661990

Early Detection System for Gas Leakage and Fire in Smart Home Using Machine Learning. / Salhi, Lamine; Silverston, Thomas; Yamazaki, Taku; Miyoshi, Takumi.

2019 IEEE International Conference on Consumer Electronics, ICCE 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8661990 (2019 IEEE International Conference on Consumer Electronics, ICCE 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Salhi, L, Silverston, T, Yamazaki, T & Miyoshi, T 2019, Early Detection System for Gas Leakage and Fire in Smart Home Using Machine Learning. in 2019 IEEE International Conference on Consumer Electronics, ICCE 2019., 8661990, 2019 IEEE International Conference on Consumer Electronics, ICCE 2019, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE International Conference on Consumer Electronics, ICCE 2019, Las Vegas, United States, 19/1/11. https://doi.org/10.1109/ICCE.2019.8661990
Salhi L, Silverston T, Yamazaki T, Miyoshi T. Early Detection System for Gas Leakage and Fire in Smart Home Using Machine Learning. In 2019 IEEE International Conference on Consumer Electronics, ICCE 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8661990. (2019 IEEE International Conference on Consumer Electronics, ICCE 2019). https://doi.org/10.1109/ICCE.2019.8661990
Salhi, Lamine ; Silverston, Thomas ; Yamazaki, Taku ; Miyoshi, Takumi. / Early Detection System for Gas Leakage and Fire in Smart Home Using Machine Learning. 2019 IEEE International Conference on Consumer Electronics, ICCE 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 IEEE International Conference on Consumer Electronics, ICCE 2019).
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