Fog-Based Crime-Assistance in Smart IoT Transportation System

• Published in: IEEE access Vol. 6; pp. 11101 - 11111
• Main Authors: Neto, Augusto J. V., Zhao, Zhongliang, Rodrigues, Joel J. P. C., Camboim, Hugo Barros, Braun, Torsten
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cloud computing; Crime; Edge computing; fog computing; Internet of Things (IoT); Law enforcement; Police; Public safety; Real-time systems; Security; Smart transportation safety; smart video surveillance; Streaming media; Surveillance; Survivability; Transportation safety; Transportation systems; ubiquitous computing; Video surveillance
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2018.2803439

Smart transportation safety (STS) envisions improving public safety through a significant paradigm shift for police authority responses on crimes toward a pro-active one. The application of smart surveillance in STS is critical for automatic and accurate identification of events in case of security threats in target environments. Cloud computing reduces costs and high resource consumption of smart surveillance capable STS systems, at the cost of introducing additional latency through far away centralized systems. In this paper, the fog-framework for intelligent public safety in vehicular environment (FISVER) framework applies fog computing in smart video surveillance-based STS to enhance crime assistance in a cost-efficient way. Through fog-FISVER, in-vehicle and fog infrastructures support autonomous and real-time crime detection on public bus services. A fog-FISVER laboratory testbed prototype was created and extensive evaluations in a real testbed were performed. Results show that fog-FISVER delivers outstanding system performance and device survivability behavior over typical STS use cases.