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N-iX > 实例探究 > 利用计算机视觉和深度学习提高道路安全和运输系统效率
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Increasing Market Reach with Intelligent Traffic Management Solution: A Case Study on Redflex

技术
  • 网络安全和隐私 - 入侵检测
  • 传感器 - 自动驾驶传感器
适用行业
  • 教育
  • 运输
适用功能
  • 物流运输
用例
  • 计算机视觉
  • 视觉质量检测
服务
  • 系统集成
  • 培训
挑战
Redflex 希望通过新的流量管理解决方案来提高其市场占有率。客户需要验证他们的产品理念并开发具有高检测精度的智能交通解决方案。
关于客户
Redflex 是一家总部位于澳大利亚的公司,为政府、警察和交通部门开发智能交通解决方案 (ITS)。他们希望扩大市场占有率并开发下一代交通管理解决方案。
解决方案
N-iX 组建了一支强大的计算机视觉专家团队,并以 PoC 启动了该项目。我们的专家与客户及其澳大利亚团队一起致力于安全带紧固检测并捕捉分心驾驶行为。利用计算机视觉和深度学习模型,我们开发了一个系统,可以自动检测驾驶员是否系好安全带并捕获分心的驾驶行为。
运营影响
  • The solution developed by N-iX has helped Redflex validate their product idea to expand to new markets. It has also improved road safety and transport system efficiency by automatically detecting whether a driver has fastened the seat belt or not. The solution has reached a high level of accuracy for both PoCs. The model developed supports real-time streams, helping create fines in real-time based on captured data. This has significantly improved the efficiency of traffic management and has the potential to deter dangerous driving behaviors.

数量效益
  • Developed a solution with approximately 88% detection accuracy.

  • The next PoC provides a 91% person detection accuracy both at night and during the day.

  • The model developed supports a real-time stream (30 FPS) that helps generate fines in real-time based on captured data and specific violations.

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