Abstract

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.

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