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.

随着科学技术的发展，监视人类的反应和活动已经变得非常容易和顺畅。这些新技术有可能改变社会各个领域的安全和保障领域。随着信号处理技术的进步，监视作为安全措施的关键因素已提高到一个全新的水平。本文主要着重于使用信号处理和嵌入式工具实现智能监控系统，并将其应用于汽车中以最终开发整体驾驶员辅助系统。较早的方法是基于生理和模拟数据，但是目前的情况需要一个更智能的数字化工作系统，以便与其他智能子系统（如手机和平板电脑）保持完整性和兼容性。众所周知，交通运输是社会的重要部门之一。但是，人们没有为他们的房屋采用人们为自己的房屋所采取的安全措施。除车辆防盗防盗系统外，驾驶员监控系统对于驾驶员和乘客的生活也至关重要。因此，本文由三个相互关联的模块组成，分别是驾驶员疲劳检测，酒精含量检测和车辆碰撞检测，以及用于监视可能影响车辆控制的驾驶员生理状态的控制。