زهرا پنجی

Abstract

Vehicle smartification has emerged as a transformative trend in the tra  ortation industry, particularly in enhancing safety, efficiency, and driving comfort. This concept is influenced by technological advancements, especially in the fields of communications, robotics, and data mining, moving towards the development of autonomous vehicles and intelligent tra  ortation systems. The aim of this research is to identify emerging topics and recent trends in vehicle smartification by analyzing the content of articles and patents. In Chapter Two, the relevant literature, associated concepts, the history of smartification trends in the automotive industry, and the background of the research are examined.

In the methodology section of this research, data science methodology and text mining techniques were utilized. By following the steps of this methodology, the information needs were first identified, and then data were collected from two primary sources: patents from the Lens scientific database and articles from the Web of Science database. This data set includes ۲۶۵,۰۰۴ patents and ۳۹,۶۸۸ articles from the period between ۲۰۱۵ and ۲۰۲۴. Through the implementation of descriptive modeling and social network analysis, emerging trends and topics in the field of vehicle smartification were thoroughly analyzed.

The results indicate that in ۲۰۲۳, the highest number of registered patents (۳۴,۴۹۴ patents) has been recorded, with Hyundai Motor leading the field with ۹,۱۰۲ patents. Additionally, the primary author of the articles in this domain is Mr. Zhang, and the main producers of knowledge in this area are China, the United States, and South Korea. The analyses reveal that emerging trends include advanced robotics, wireless communications, and intelligent tra  ortation management. The main keywords in this field include "autonomous vehicles," "communication systems," and "artificial intelligence," which have influenced the progression of smartification in the automotive industry. Furthermore, changes in keywords indicate a shift in focus towards aerial vehicles and the development of powerful processing systems, which are shaping a new future for intelligent tra  ortation.

mining, intelligent tra  ortation management.