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Smart driver assistance system using raspberry pi and sensor networks

机译:使用覆盆子PI和传感器网络的智能驾驶员辅助系统

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摘要

With the evolution of science and technology, monitoring human reactions and activities have become really easy and smooth. These new technologies have the potential to revolutionize the domain of safety and security in different realms of the society. Surveillance being the key factor of security measures has been elevated to a whole new level with the advancement in signal processing techniques. This paper basically focuses on the implementation of a smart surveillance system using signal processing and embedded tools which is applied in automobiles to ultimately develop the holistic driver assistance system. Earlier methods were based on physiological and analog data, but the present day scenario demands a smarter and digitalized working system so as to employ integrity and compatibility with other smart sub-systems like mobile phones and tablets. Transportation as we all know is one of the key sectors in the society. But the safety and security measures which people implement for their homes is not being employed for their vehicles. Apart from the vehicular anti-theft burglar systems, driver monitoring systems are also crucial to the lives of the driver and the passengers. Hence, this paper consists of three inter-linked modules which are the driver fatigue detection, alcohol content detection and vehicular crash detection along with control to monitor the driver's physiological state that can affect the vehicular control. A variety of input extraction hardware tools and software algorithms have been utilized in a collaborative way to implement this process.
机译:随着科学技术的演变,监测人体反应和活动变得非常容易和光滑。这些新技术有可能彻底改变社会不同领域的安全和安全领域。随着信号处理技术的进步,监视是安全措施的关键因素已被提升到全新水平。本文基本上侧重于使用信号处理和嵌入式工具的智能监控系统的实施,该工具应用于汽车中的应用,最终开发整体驾驶员辅助系统。早期的方法是基于生理和模拟数据,但现在的情况需要更智能和数字化的工作系统,以便与移动电话和平板电脑等其他智能子系统一起使用完整性和兼容性。众所周知的运输是社会的主要部门之一。但是,人们为其家庭实施的安全和安全措施不会被雇用。除了车辆防盗防盗系统外,驾驶员监控系统对驾驶员和乘客的生活也至关重要。因此,本文由三个相互联系的模块组成,这是驾驶员疲劳检测,酒精内容检测和车辆碰撞检测以及控制,以监测可能影响车辆控制的驾驶员的生理状态。已经以协作方式利用了各种输入提取硬件工具和软件算法来实现此过程。

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