A Comprehensive and Effective Framework for Traffic Congestion Problem Based on the Integration of IoT and Data Analytics

Abstract

Traffic congestion is still a challenge faced by most countries of the world. However, it can be solved most effectively by integrating modern technologies such as Internet of Things (IoT), fog computing, cloud computing, data analytics, and so on, into a framework that exploits the strengths of these technologies to address specific problems faced in traffic management. Unfortunately, no such framework that addresses the reliability, flexibility, and efficiency issues of smart-traffic management exists. Therefore, this paper proposes a comprehensive framework to achieve a reliable, flexible, and efficient solution for the problem of traffic congestion. The proposed framework has four layers. The first layer, namely, the sensing layer, uses multiple data sources to ensure a reliable and accurate measurement of the traffic status of the streets, and forwards these data to the second layer. The second layer, namely, the fog layer, consumes these data to make efficient decisions and also forwards them to the third layer. The third layer, the cloud layer, permanently stores these data for analytics and knowledge discoveries. Finally, the fourth layer, the services layer, provides assistant services for traffic management. We also discuss the functional model of the framework and the technologies that can be used at each level of the model. We propose a smart-traffic light algorithm at level 1 for the efficient management of congestion at intersections, tweet-classification and image-processing algorithms at level 2 for reliable and accurate decision-making, and support services at level 4 of the functional model. We also evaluated the proposed smart-traffic light algorithm for its efficiency, and the tweet classification and image-processing algorithms for their accuracy.

Blending Human Ware with Software and Hardware in the Design of Smart Cities

“…Cloud computing may also be utilized to construct databases and platforms for medical and health services. Additionally, patients may register remotely through the IoT, and this healthcare access can be provided to 100% of the urban population quite easily [101,102]. Cloud computing can perform real-time forecasting and evaluation of traffic conditions, analyze traffic development trends, offer trustworthy decision-making resources for traffic management departments, and facilitate road traffic guidance.…”

“…Based on the current remote monitoring system of traffic, the traffic signal lights are managed and controlled to achieve adequate traffic flow control, and almost eliminate the likelihood of an accident. The standardization and unification of road traffic management may also be achieved by remote traffic control and electronic toll collection, eliminating the problem of slack law enforcement brought on by "human-friendly" management and promoting society's peaceful and steady growth [102]. IoT devices are often widely dispersed across different regions, Blending Human Ware with Software and Hardware in the Design of Smart Cities DOI: http://dx.doi.org/10.5772/intechopen.109053 but they all transmit data to a single central system [109].…”

A Novel Approach for Traffic Congestion Mitigation Based on Fog Computing Using IFogsimulator

“…The high-traffic cities around the world have the opportunity to reduce congestion by using a traffic control system based on the open fog computing model [16].…”

Deep Learning for Resource Management in Internet of Things Networks: A Bibliometric Analysis and Comprehensive Review

“…Examples of the IoT applications under the category of smart health [52] - [55] include the monitoring of the organs or health conditions of a patient, remote surgery, diagnosing a patient's health condition(s), authentication of patients, and making real-time information about a patient's health condition available to the appropriate remote healthcare centers [56], [57]. Examples of the IoT applications under the class of smart city include intelligent transportation [58] - [62], assisted driving [63] and [64], passenger services, logistic services [65] and [66], car parking and counting [67] - [70], fleet management [71] - [73], emergency reporting services [74] - [76], and intelligent traffic control [77] - [79]. For instance, in smart water quality sensing and water supply applications, IoT technology could assist to efficiently monitor changes in water quality, control the distribution of clean water for various consumption uses, guarantee the safety of the public health since it helps to increase access to clean water, and prevents the distribution of unclean water to the public.…”