| Title | Strategies to Handle Big Data for Traffic Management in Smart Cities |
|---|---|
| ID_Doc | 79120 |
| Authors | Nandury, SV; Begum, BA |
| Title | Strategies to Handle Big Data for Traffic Management in Smart Cities |
| Year | 2016 |
| Published | |
| Abstract | The myriad sensors deployed across a smart city, serve as major source for Big data, which can potentially be used for various applications like smart governance, smart energy, smart traffic, smart environment, etc. However, issues related to the handling of such huge volumes of data originating from thousands of heterogeneous sensor and IoT devices placed across the length and breadth of the city, emerge as a major challenge. While it may be relatively easy to identify the IT devices necessary for processing Big data, in the absence of clear strategies and robust platform architecture for handling Big data, the deployment of these resources attain limited success. The SWIFT architecture introduced by us in an earlier work provides a ubiquitous platform for seamless interaction of various smart objects, devices and systems, and hence may prove to be an ideal architecture to capture, process and assimilate information from Big data. In this paper we discuss issues related to implementation of SWIFT architecture for handling Big data for traffic management in smart cities. Various strategies to provide Big data solutions for smart traffic in terms of profiling traffic density, traffic signaling, managing the parking lots, smart navigation and monitoring vehicular pollution are discussed in the paper. |
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