Latest revision as of 00:35, 29 January 2021

Abstract

Internet of Things (IoT) technology connects physical things through the internet by creating a virtual identity for everything. It is based on the Internet, wireless sensor networks and detection technologies to realize intelligent recognition of the tagged traffic object and automatic tracking. Traffic congestion in Riyadh city is chosen due to the proliferation in the number of vehicles that is resulting in grumbling by residents because of the massive delays, monetary losses and increased fuel wastage. There are currently few reliable services offered to residents from the traffic department enabling them to access traffic information. This research is to propose a traffic congestion framework for Riyadh road infrastructure and to apply IoT technology for monitoring traffic congestion. Sensing devices are used to identify the congestion of the traffic flow by providing multiple proposed services such as a vehicle counting, live streaming video and rerouting services. Users are able to access the services by using proposed mobile application connected to the internet, as those services are integrated with public map. Users are also able to identify the exact location where congestion occurs and an alternate solution can be provided easily. Business Process Execution Language (BPEL) is embedded as a supporting framework layer. Executable workflows are designed to combine the proposed services with the legacy Riyadh services as individual model. It clearly defines how the services are executed through the proposed models. In order to support the usability of this framework, a quantitative evaluation is provided.

Original document

The different versions of the original document can be found in:

• https://ieeexplore.ieee.org/ielx7/8827888/8844048/08844078.pdf

• http://xplorestaging.ieee.org/ielx7/8827888/8844048/08844078.pdf?arnumber=8844078,

http://dx.doi.org/10.1109/comnetsat.2019.8844078

• http://xplorestaging.ieee.org/ielx7/8827888/8844048/08844078.pdf?arnumber=8844078,

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=8844078,

https://academic.microsoft.com/#/detail/2974412989