A traffic congestion framework for smart Riyadh city based on IoT services

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Abstract

Internet of Things has become one of the most challenging issues in many researches to connect physical things through the internet by creating a virtual identity for everything. Traffic congestion in Riyadh city is chosen due to the proliferation in the number of vehicles on Riyadh roads that is resulting in grumbling by residents. Currently, there are few reliable services offered to residents from the traffic department enabling them to access traffic information. A new traffic congestion framework for Riyadh is proposed to help the development of traffic congestion services. This framework aims to benefit from the current Riyadh road infrastructure and apply the Internet of Things paradigm for detecting traffic congestion with Everything as a Service approach. Sensing devices are used to identify the congestion of the traffic flow through 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 service. By using the services, the users are able to identify the exact location where congestion occurs and an alternate solution can be provided easily. To achieve this, Business Process Execution Language is embedded as a supporting framework layer. Due to the effectiveness in this layer, executable workflows are designed to combine the proposed services with the legacy Riyadh services as individual model. This approach clearly defines how the services are executed through the proposed models. A quantitative evaluation is provided to support the usability of this research.

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APA

Al-Majhad, H. G., Bramantoro, A., Syamsuddin, I., Yunianta, A., Basori, A. H., Prabuwono, A. S., & Barukab, O. M. (2018). A traffic congestion framework for smart Riyadh city based on IoT services. International Journal of Advanced Computer Science and Applications, 9(4), 292–303. https://doi.org/10.14569/IJACSA.2018.090443

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