We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
AI-based Electric Fire Detection State Judgment Data Set Construction.
- Authors
Hee-Chul Kim
- Abstract
In this paper, we create a virtuous cycle ecosystem of AI data for judging electric fire status. Data collection reflects feedback on inspection results such as collection of electric fire status judgment data through cloud sourcing and purification, processing, inspection and data disclosure of the collected data. It is necessary to determine the cause of the damage through fire forensics in order to confirm the property damage caused by the fire. The damage investigation so far is based on the experience of the investigator, and it is difficult to conduct a sufficient investigation and analysis of multiple fires. Accordingly, by building a data set for AI learning for the cause analysis of electric fires, The AI composition that can overcome the subjective and unprofessionalism of the forensic of electric fires is made. Therefore, we study the reliability and system development feasibility of digital conversion of fire detection report and data for AI learning.
- Subjects
ARTIFICIAL intelligence; PROPERTY damage; RELIABILITY in engineering; ACQUISITION of data; FIRE investigation
- Publication
Technical Journal / Tehnički Glasnik, 2024, Vol 18, Issue 1, p43
- ISSN
1846-6168
- Publication type
Article
- DOI
10.31803/tg-20230221152352