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With the rapid maturation in automotive industry, intelligent sensing has been emerged as a vital research field for fast paced future intelligent transportation system. After the progressive integration of advanced driver assistance system and the rapid growth in next generation Internet of Vehicles (IoV), diver’s identification constitutes an indispensable aspect for the authorization in next generation internet-connected smart vehicles. A real-time driver identification is crucial in next generation smart vehicles. The presented solution is based on channel state information (CSI) of WiFi signals. In this proposed framework, an innovative WiFibased low-cost driver identification system is proposed which can recognise driver with good accuracy and less computational burden. The core idea is based on analyzing the steering wheel maneuver, exploiting CSI of WiFi signal. In the era of advanced information and communication in intelligent transportation system, this driver identification systems may incorporate various intelligent means that are beneficial in many applications including safety, security, fleet management, ride hailing, insurance telematics, and customized vehicles. The proposed framework can recognise the activities with an average accuracy of 92.5% and identification with an average accuracy of 91.8%.
With the rapid maturation in automotive industry, intelligent sensing has been emerged as a vital research field for fast paced future intelligent transportation system. After the progressive integration of advanced driver assistance system and the rapid growth in next generation Internet of Vehicles (IoV), diver’s identification constitutes an indispensable aspect for the authorization in next generation internet-connected smart vehicles. A real-time driver identification is crucial in next generation smart vehicles. The presented solution is based on channel state information (CSI) of WiFi signals. In this proposed framework, an innovative WiFibased low-cost driver identification system is proposed which can recognise driver with good accuracy and less computational burden. The core idea is based on analyzing the steering wheel maneuver, exploiting CSI of WiFi signal. In the era of advanced information and communication in intelligent transportation system, this driver identification systems may incorporate various intelligent means that are beneficial in many applications including safety, security, fleet management, ride hailing, insurance telematics, and customized vehicles. The proposed framework can recognise the activities with an average accuracy of 92.5% and identification with an average accuracy of 91.8%.
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