VGU RESEARCH REPOSITORY
Please use this identifier to cite or link to this item:
https://epub.vgu.edu.vn/handle/dlibvgu/996| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Vu Tuan Hung | en_US |
| dc.date.accessioned | 2021-03-09T03:07:06Z | - |
| dc.date.available | 2021-03-09T03:07:06Z | - |
| dc.date.issued | 2020 | - |
| dc.identifier.uri | http://epub.vgu.edu.vn/handle/dlibvgu/996 | - |
| dc.description.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 | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Vietnamese-German University | - |
| dc.rights | Attribution-NonCommercial 4.0 International | * |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | * |
| dc.subject | Early fire detection | en_US |
| dc.subject | Machine learning | en_US |
| dc.subject | Thermal sensors | en_US |
| dc.subject | Smoke sensors | en_US |
| dc.title | Early fire detection system with machine learning and embedded system | en_US |
| dc.type | Thesis | en_US |
| item.fulltext | With Fulltext | - |
| item.languageiso639-1 | other | - |
| item.grantfulltext | restricted | - |
| Appears in Collections: | Computer Science (CS) | |
Files in This Item:
| File | Description | Size | Format | Existing users please Login |
|---|---|---|---|---|
| Early fire detection system with machine learning.pdf | 2.24 MB | Adobe PDF |
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