Abstract
With the emergence of fog and edge computing, new possibilities arise regarding the data-driven management of citizens’ mobility in smart cities. Internet of Things (IoT) analytics refers to the use of these technologies, data, and analytical models to describe the current status of the city traffic, to predict its evolution over the coming hours, and to make decisions that increase the efficiency of the transportation system. It involves many challenges such as how to deal and manage real and huge amounts of data, and improving security, privacy, scalability, reliability, and quality of services in the cloud and vehicular network. In this paper, we review the state of the art of IoT in intelligent transportation systems (ITS), identify challenges posed by cloud, fog, and edge computing in ITS, and develop a methodology based on agile optimization algorithms for solving a dynamic ride-sharing problem (DRSP) in the context of edge/fog computing. These algorithms allow us to process, in real time, the data gathered from IoT systems in order to optimize automatic decisions in the city transportation system, including: optimizing the vehicle routing, recommending customized transportation modes to the citizens, generating efficient ride-sharing and car-sharing strategies, create optimal charging station for electric vehicles and different services within urban and interurban areas. A numerical example considering a DRSP is provided, in which the potential of employing edge/fog computing, open data, and agile algorithms is illustrated.
Highlights
In today’s modern society, urban centers are facing the so-called booming of information
When processed by machine learning methods and optimization algorithms, this information can become in valuable knowledge that empowers citizens and support intelligent mobility decisions
The paper discussed the necessity for developing agile algorithms, capable of providing high-quality solutions to large-scale vehicle routing and other transportation-related problems, and to do so in real-time and every few minutes, as new data are gathered via Internet of things (IoT) and open repositories
Summary
In today’s modern society, urban centers are facing the so-called booming of information. -called smart cities have emerged, whose scope combines sustainable development with the intelligent management of gathered data in order to enhance the operation of different services within urban areas, such as waste collection management [1], car-sharing/ride-sharing activities [2], the optimal location of recharging stations for electric vehicles (EVs), among others In this matter, during the past few years, the Internet of things (IoT) has become a popular term that plays a significant role to expand and produce a lot of data through sensors and allows citizens and things to be connected in any situation or with anyone [3]. Utilizing the cloud and edge computing helps to handle terabytes of data extracted from IoT devices—including information about vehicles’ mobility and traffic conditions By analyzing these data and combining them with the concept of ride-sharing, some urban mentioned problems can be reduced or even solved.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
