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A Dataset for Visual Classification of Battery Fire and Smoke
- Format:
- Book
- Conference/Event
- Author/Creator:
- Govilesh, Vidarshana, author.
- Gunasekaran, Aswin, author.
- Challa, Karthikeya, author.
- Maxim, Bruce, author.
- Shen, Jie, author.
- Conference Name:
- WCX SAE World Congress Experience (2026-04-14 : Detroit, Michigan, United States)
- Language:
- English
- Subjects (All):
- Energy storage systems.
- Battery packs.
- Electric vehicles.
- Consumer electronics.
- Batteries.
- Local Subjects:
- Energy storage systems.
- Battery packs.
- Electric vehicles.
- Consumer electronics.
- Batteries.
- Physical Description:
- 1 online resource
- Place of Publication:
- Warrendale, PA SAE International 2026
- Summary:
- Battery fires pose a significant risk across a wide range of applications, including electric vehicles, consumer electronics, and grid-scale energy storage systems. Early detection of fire and smoke is critical to preventing catastrophic failures and ensuring human safety. In this study, we developed a synthetic dataset of battery fire and smoke images in the context of a simple battery pack. The primary application of this dataset is to support the development of a machine learningbased visual classification system capable of accurately detecting battery fires and smoke in real time at an early stage. The intended outcome is a deployable classification system that enhances battery safety through rapid visual identification of hazardous conditions
- Notes:
- Vendor supplied data
- Access Restriction:
- Restricted for use by site license
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