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Conference Paper
Implementation of Danger Degree Calculation System for Public Safety Services
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- Authors
- Hyunho Park, Eunjung Kwon, Sungwon Byon, Minjung Lee, Young Soo Park, Eui-Suk Jung
- Issue Date
- 2023-07
- Citation
- International Conference on Ubiquitous and Future Networks (ICUFN) 2023, pp.29-32
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Danger degree calculations are important to provide public safety services because crime response methods vary depending on danger degrees of crime scenes. This paper proposes a danger degree calculation system (DDCS) to calculate the danger degrees by using natural language processing (NLP) of emergency report data that summarize emergency calls. This paper also explains an implementation of DDCS by building a deep learning NLP model with KoBERT and visualizing a process of danger degree calculations. Danger degrees from the DDCS will help a constabulary to determine appropriate physical forces (e.g., devices and crime control actions) for police officers’ responding to the crime scenes.
- KSP Keywords
- Danger Degree, NLP model, Natural Language Processing, Physical forces, Police officers, Public safety, control actions, deep learning(DL), emergency calls