Artificial Intelligence as a Catalyst for Next-Generation Emergency Call Systems
- Delivery
- Available on this site
- Format
- Price
- Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880
- Publication code
- 20265375
- Paper/Info type
- Proceedings (Spring)
No.86-26
- Pages
- 1-7(Total 7 p)
- Date of publication
- May 2026
- Publisher
- JSAE
- Language
- English
- Event
- 2026 JSAE Annual Congress (Spring)
Detailed Information
| Author(J) | 1) Hamma Tadjine Hadj, 2) Amine Kaddache, 3) Isao Hasegawa |
|---|---|
| Author(E) | 1) Hamma Tadjine Hadj, 2) Amine Kaddache, 3) Isao Hasegawa |
| Affiliation(J) | 1) IAV, 2) IAV, 3) IAV Japan |
| Affiliation(E) | 1) IAV, 2) IAV, 3) IAV Japan |
| Abstract(E) | Advanced emergency call systems currently transmit basic vehicle data during accidents. To enhance passenger safety, new features focus on improved data collection aligned with NENA2 and NG-AACN standards, considering in-vehicle architecture and communication protocols. The goal is to provide precise information about occupants and surroundings for better rescue operations. AI integration boosts efficiency and effectiveness, optimizing eCall systems through rapid data analysis and prioritizing calls by severity. AI enhances design and operational capabilities, enabling automated data processing and swift emergency assessment. Predictive analytics foresee potential emergencies, supporting proactive measures and strategic resource allocation for high-risk scenarios. |
