A Review of Machine Learning and IoT in Smart Transportation

By Fotios Zantalis, Grigorios E. Koulouras, Sotiris Karabetsos, Dionisis Kandris. Future Internet, 2019

509 citations recorded by the source corpus.

With the rise of the Internet of Things (IoT), applications have become smarter and connected devices give rise to their exploitation in all aspects of a modern city. As the volume of the collected data increases, Machine Learning (ML) techniques are applied to further enhance the intelligence and the capabilities of an application. The field of smart transportation has attracted many researchers and it has been approached with both ML and IoT techniques. In this review, smart transportation is considered to be an umbrella term that covers route optimization, parking, street lights, accident prevention/detection, road anomalies, and infrastructure applications. The purpose of this paper is to make a self-contained review of ML techniques and IoT applications in Intelligent Transportation Systems (ITS) and obtain a clear view of the trends in the aforementioned fields and spot possible coverage needs. From the reviewed articles it becomes profound that there is a possible lack of ML coverage for the Smart Lighting Systems and Smart Parking applications. Additionally, route optimization, parking, and accident/detection tend to be the most popular ITS applications among researchers.

Subfields: Building and Construction, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/c4706f9fd62527c8576613fbcdb266559c08b405

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. D. M. Abdullah
2. Adnan Mohsin Abdulazeez
3. John G. Keogh

In Mechanical Engineering

1. D. M. Abdullah
2. Adnan Mohsin Abdulazeez
3. Joseph Homer Saleh
4. Zhaoyi Xu

Citations in the corpus

• Applications of Wireless Sensor Networks: An Up-to-Date Survey (2020, methodology): “WSNs can be utilized monitoring in order to reduce tra ffi c, indicate car parking spots, etc. [46] In [47] a WSN ‐ based intelligent car parking system is proposed.”
• Machine Learning Applications based on SVM Classification A Review (2021, methodology): “Machine Learning algorithms were used for solving different types of problems in data classification [4,5,6,7].”
• Leveraging the Internet of Things and Blockchain Technology in Supply Chain Management (2019, background): “…and enhance competitiveness, companies are applying novel technologies such as the Internet of Things (IoT), cloud computing, business analytics, artificial intelligence, machine learning, and Blockchain technology [3–5], as well as innovative concepts such as the so-called physical Internet [6].”
• Machine Learning for Reliability Engineering and Safety Applications: Review of Current Status and Future Opportunities (2020, background): “Machine learning pervades an increasing number of fields, from banking and finance [1, 2, 3] to healthcare [4, 5, 6], robotics [7, 8, 9], transportation [10, 11, 12], e-commerce [13, 14, 15], and social networks to mention a few.”
• From Artificial Intelligence to Explainable Artificial Intelligence in Industry 4.0: A Survey on What, How, and Where (2022, background): “IoT, cloud computing, and big data advancement also improve transportation services [76].”