Smart wireless sensor networks and biometric authentication for real time traffic light junctions management

  • Authors:

  • Mario Collotta;Vincenzo Conti;Gianfranco Scatí;Giovanni Pau;Salvatore Vitabile

  • Affiliations:

  • Faculty of Engineering and Architecture, University of Enna - Kore, Cittadella Universitaria, 94100, Enna, Italy;Faculty of Engineering and Architecture, University of Enna - Kore, Cittadella Universitaria, 94100, Enna, Italy;Faculty of Engineering and Architecture, University of Enna - Kore, Cittadella Universitaria, 94100, Enna, Italy;Faculty of Engineering and Architecture, University of Enna - Kore, Cittadella Universitaria, 94100, Enna, Italy;Department of Biopathology, Medical and Forensic Biotechnologies, University of Palermo, Via del Vespro, 129, 90127, Palermo, Italy

  • Venue:
  • International Journal of Intelligent Information and Database Systems
  • Year:
  • 2013

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Abstract

The main challenge of intelligent transportation systems ITS is to deal with 'real-time' information to improve vehicular traffic management. Road data can be processed and used for dynamic traffic light management in order to reduce waiting times in queues. This paper proposes an innovative distributed architecture based on a wireless sensor network WSN with a network coordinator providing remote and ubiquitous authentication module for managing unexpected events. The architecture is completed by a dynamic module for street priority management depending on traffic rate. Many experimental trials have been carried out considering three different levels of traffic intensity to prove the effectiveness of the proposed approach. In a street with high traffic intensity 120 vehicles in queue, the average vehicles/second rate decrease from 6.135, using a fixed cycle traffic light, to 0.365 using the proposed traffic light measurement system. Moreover, to improve the system security, a fingerprints-based embedded authentication system has been implemented as a self-contained sensor to increase the security of distributed personal data storage. The best achieved FAR and FRR indexes are respectively 0.73% and 9.21%, with a mean elaboration time of 192.46 ms and a working frequency of 22.5 MHz.