A novel vehicular sensing framework for smart cities

Abstract

Smart cities leverage technology to analyze data to make decisions, anticipate problems and coordinate resources to operate efficiently. Data produced by sensors embedded in vehicles moving on streets enable sensing applications for smart cities that were infeasible in the past due to high deployment costs. In this paper, we propose a novel framework for collection, aggregation and retrieval of data. The framework considers vehicles and road-side units as the main entities. To collect data, the city road network is divided into a number of sensing regions. We discuss the aggregation operations for each type of event. A retrieval mechanism is also proposed to deliver content in real-time. The simulations results demonstrate that the proposed framework outperforms existing vehicular sensing approaches in terms of delay and accuracy.