Smart methodology for safe life on roads with active drivers based on real-time risk and behavioral monitoring

  • Abid Ali Minhas
  • Sohail JabbarEmail author
  • Muhammad Farhan
  • Muhammad Najam ul Islam
Original Research


Video services are becoming more pervasive due to the swift development of next-generation intelligent communications and network systems. With the growth of these types of services, the numbers of users are increasing at an exponential rate, and numbers of devices are being used for it, e.g., wearable equipment, smartphones, tablets, personal computers or laptops, and smart televisions. Real-time object tracking and identification of the state of drowsiness of driver is a challenging area of research. An increasing number of good results are reported concerning its robustness and accuracy. Frequently, no clear statements about the tracking situations are made, when it comes to the application of these methods to real-world problems. In order to address the problem of identification of the state of the drowsiness of driver, a research project has been initiated in the Kingdom of Saudi Arabia. This research aims to avoid road accidents due to the drowsiness of drivers by keeping them active through suitable means. Different methods are analyzed to detect the driver’s drowsiness, and a state of the art solution is proposed in this research. At the current state, we are considering the openness and closeness of eyes for detecting the driver’s drowsiness. Various techniques are analyzed to keep the fatigued driver active. In the case of the inevitable effect of drowsiness and the abnormal response of the driver towards alerts, the driver’s location and sufficient information of the driver’s state are communicated with the Police Base station. As a result of this research, we are optimistic about coming up with highly positive results in its social, economic and industrial benefits. Extending this research towards the product and its development on a large scale can make a significant contribution to the Kingdom’s economy as well.


Driver’s drowsiness detection Vehicle obstacle detection Collision warning Alerting actions Road accidents Fatigue detection 



This research, including all funds and support for equipment, was fully supported by Al Yamamah University, Riyadh, Kingdom of Saudi Arabia.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer Engineering, College of Engineering and ArchitectureAl Yamamah UniversityRiyadhKingdom of Saudi Arabia
  2. 2.CfACS IoT Lab, Department of Computing and MathematicsManchester Metropolitan UniversityManchesterUK
  3. 3.Department of Computer ScienceCOMSATS University Islamabad, Sahiwal CampusSahiwalPakistan
  4. 4.Department of Electrical EngineeringBahria UniversityIslamabadPakistan

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