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VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/996
Title: Early fire detection system with machine learning and embedded system
Authors: Vu Tuan Hung 
Keywords: Early fire detection;Machine learning;Thermal sensors;Smoke sensors
Issue Date: 2020
Publisher: Vietnamese-German University
Abstract: 
This paper introduces an automated, user- and budget-friendly, effortlessly installable and intuitively self-correcting fire detection algorithm; employed aptly are the fortitude of embedded builtin thermal and air quality (smoke) sensors and a logistic regression model that is fed on incrementally accumulated data from a particular environment, and continually analyzes the metrics from that environment in real-time to assess the chance of fire. Users are forthwith notified via a mobile application should the pattern of fire be identified. The resemblance of this fire probability estimator to human cognition derives from the ability to replicate a
personals course of perception. In addition, the self-correction feature weighs up the potentialities, making it a circulating maintenance-less and future-proof plan. The modularity of the
logical flow of the design and its simplistic installation are expected to cultivate community's support at the beginning of deployment, making it ideal for cross-environment application
URI(1): http://epub.vgu.edu.vn/handle/dlibvgu/996
Rights: Attribution-NonCommercial 4.0 International
Appears in Collections:Computer Science (CS)

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