2016 · 194 citations · 15 references
ComputingComputer SystemsBig Data AnalyticsInternet Of ThingsTransportationIntelligent Transportation SystemsReal-time AnalyticsSmart CitiesSmart City SystemsTraffic EngineeringTransportation System ManagementReal-time ProcessingReal-time Traffic MonitoringSmart City Internet Of ThingsTraffic DensityTraffic Density AnalysisTraffic ManagementTraffic Management SystemsTraffic Monitoring Systems
Smart traffic management is crucial for smart cities, yet existing systems are inadequate, costly, and difficult to configure. The paper proposes a low‑cost, real‑time smart traffic management system that instantly updates traffic information using deployed indicators. The system uses low‑cost vehicle‑detecting sensors placed every 500–1000 m, IoT to collect data, real‑time streaming to big‑data analytics, and predictive scripts to assess density, with a mobile app providing user interface. The mobile application enables users to view traffic density and offers alternative traffic management solutions.
Smart Traffic management system (STMS) is a one of the important feature for smart city. Currently traffic management and alert systems are not fulling needs of STMS. It is more expensive and highly configurable to provide better service for traffic management. This paper proposes a low cost Real-Time smart traffic Management System to provide better service by deploying traffic indicators to update the traffic details instantly. Low cost vehicle detecting sensors are embed in the middle of road for every 500 meters or 1000 meters. Internet of Things (IoT) are being used to acquire traffic data quickly and send it for processing. The Real time streaming data is sent for Big Data analytics. There are several analytical scriptures to analyze the traffic density and provide solution through predictive analytics. A mobile application is developed as user interface to explore the density of traffic at various places and provides an alternative way for managing the traffic.
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Reducing Traffic Jams via VANETs
Florian Knorr, Daniel Baselt, Michael Schreckenberg et al. · IEEE Transactions on Vehicular Technology · 2012 · 138 citations
Smart traffic control system with application of image processing techniques
Md Munir Hasan, Gobinda Saha, Aminul Hoque et al. · 2014 · 59 citations