IoT for the Smart Traffic

Dear Colleagues,

The IoT has evolved rapidly in recent decades, starting with radio frequency identification (RFID) technology in the early 1980s and accelerating wireless sensor networks (WSNs) in the late 1990s and early 2000s. Today, despite the limited functionality, the IoT segment is becoming more significant and interconnected with other technologies. In addition to low-cost hardware, next-generation IoT encompasses more advanced networked devices with increased complexity and heterogeneity, including Internet-enabled self-driving cars, handheld gadgets, industrial robots, and quadcopters.

Today, we are witnessing a steady and continuous penetration of IoT concepts into the automotive industry, where it is possible to manage individual vehicles (hereinafter referred to as moving objects) through cloud networks that are deeply integrated with existing caching and computing systems. For example, end-to-end solutions between many dissimilar IoT devices such as smart road signs, traffic lights and street cameras are possible. This new trend opens the door to enormous benefits. On the one hand, connected vehicles (objects) become able to receive important timely updates and warnings from the road infrastructure, improving safety and driving comfort. On the other hand, it becomes possible to manage data from sensors and significantly save battery power. We also know that due to overpopulation our cities face many problems such as pollution, lack of water, traffic congestion, etc. This challenge is met by the concept of "Smart City" - the creation of a society that can function by effectively using urban infrastructure with using machine learning and artificial intelligence and IO devices such as connected sensors, traffic lights and meters to collect and analyse data. Cities then use this data to improve infrastructure, utilities, services, and people interact with various devices such as smart homes, smart health, smart vehicles, smart agriculture, etc.

Machine learning will help drive autonomous vehicles or unmanned vehicles to reduce traffic delays and reduce pollutant emissions with an e-vehicle. IoT-based intelligent transportation systems make it possible to share information through collaborative systems that communicate traffic data to improve road safety.

In this special issue, we welcome research focused on the application of IoT in the smart city concept, with a focus on smart traffic applications. We encourage work that uses deep learning, artificial intelligence, urban microsimulation, etc. in an original and creative way.

We expect both research and review articles submissions. If you would like to contribute to this special issue, we would greatly appreciate receiving a provisional title and summary of your contribution by email.

Prof. Dr. Konstantin Samouylov
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. IoT is an international peer-reviewed open access quarterly journal published by MDPI.

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• IoT
• IIoT
• big data
• smart cities
• smart traffic
• IoT traffic
• management system
• smart home environment
• traffic congestion
• traffic modeling and simulation
• performance analysis
• machine learning
• congestion prediction