Integrated Rescue Plan for Intelligent Transportation, Medical and Fire Protection on Highways
Year: 2025
Type: article
Abstract: 随着交通领域的智能化发展，交通视频监测、线上消防(如微信江苏消防报警服务)和线上120 (如微信重庆“视频120”)等新兴服务模式正迅速崛起。然而，目前这些平台在处理高速公路交通事故时，无法感知事故信息以及选择救援方案，仍需人工干预，比较影响救援的时效性。针对此问题，本文提出了一种基于深度学习的高速公路事故智慧救援平台，首先，通过目标检测和目标分类算法精准识别人员和车辆以及类型，结合逻辑判断是否发生交通事故；借助人体姿态识别技术，判断人员是否受伤；同时，利用语义分割算法检测道路是否出现火焰和烟雾；根据这些信息自动决策事故等级，并启用对应的救援方案，将事故的关键信息上报至救援单位；智慧救援平台不仅解决了事故感知滞后的问题，而且提高了救援效率，保障了高速公路的安全。With the intelligent development of the transportation field, new service models such as traffic video monitoring, online fire protection (such as WeChat Jiangsu Fire Alarm Service), and online 120 (such as WeChat Chongqing “Video 120”) are rapidly emerging. However, at present, these platforms cannot sense accident information and select rescue plans when dealing with highway traffic accidents, and still require manual intervention, which affects the timeliness of rescue. In response to this problem, this article proposes an intelligent rescue platform for highway accidents based on deep learning. Firstly, through target detection and classification algorithms, it accurately identifies personnel and vehicles as well as their types, and combines logical judgment to determine whether a traffic accident has occurred. With the help of human pose detection technology, it judges whether personnel are injured. At the same time, it uses semantic segmentation algorithms to detect whether there is flame and smoke on the road. It automatically determines the accident level based on this information, activates corresponding rescue plans, and reports the key information of the accident to the rescue unit. The intelligent rescue platform not only solves the problem of delayed accident perception, but also improves the efficiency of rescue and ensures the safety of the highway.
Author: 阳 周
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409375354