Abstract
Objective: Ranking in many areas has been a big problem for a long time. The authors tried to use a novel ranking approach to find out the most popular research interest among all the research fields. The authors have assumed that the selection of a research area is a tedious task.
Methods: Therefore, they tried to propose a mechanism named METHWORK (Methodology With the Opted Related Keywords) to choose popular research trends. Google-based searching was applied to find samples in the initial state of this approach. The METHWORK was tested with respect to a case of ranking of research trends within the IoET (Internet of Environmental Things). To find ranks, the first phase is to assess the popularity of the topics in the existing published research papers. To find out the correctness of the ranking found using METHWORK, the authors performed χ2 hypothesis testing while making a comparison with current ranking techniques.
Results: The methodology proposed is a milestone to find out the research trends within a broad research area.
Conclusion: The results of the test indicated that the approach could be applied to determine trends in any research discipline and proved the applicability of the proposed approach.
Keywords: IoT, SLR, dense ranking, Opted Related Keywords (ORK), VANET, METHWORK.
Graphical Abstract
Call for Papers in Thematic Issues
?The New Era of Computational Intelligence: Big Data Applications in Health Care?
Analyzing healthcare data has remained a tedious task for data analysts in the current age of research due the nonlinear nature of data. With data sources multiplying and their complexity rising, the most common challenge for medical analysts today is obtaining relevant data for those that need it. The challenge ...read more
Advanced Applications of Artificial Intelligence in Manufacturing Technologies
As one of the most advanced fields of study and technology in existence today, artificial intelligence (AI) is finding more and more applications in production and daily life, especially in the industrial sector. This showcases the many applications of AI in mechanical production, including but not limited to: improving worker ...read more
Advancements in AI and Machine Learning for Enhanced Computer Vision Applications
This special thematic issue is meticulously crafted to provide an extensive exploration of the intricate interplay between Artificial Intelligence (AI) and Machine Learning (ML) within the expansive domain of Computer Vision. The scope of this issue is ambitiously designed to cover a diverse range of topics, incorporating cutting-edge research, advanced ...read more
Advancing Computer Vision and Multimedia Communication for Seamless Human-Machine Interaction
The rapid advancements in computer vision and multimedia communication technologies are revolutionizing the way humans interact with machines. These technologies have the potential to enable seamless and natural human-machine interaction, creating new possibilities for communication, collaboration, and entertainment. The findings will have a significant impact on the development of new ...read more
Related Books
IoT-enabled Sensor Networks: Architecture, Methodologies, Security, and Futuristic Applications
AIoT and Big Data Analytics for Smart Healthcare Applications
Research Trends in Artificial Intelligence: Internet of Things
Artificial Intelligence and Multimedia Data Engineering
Basics of Python Programming: A Quick Guide for Beginners
Blockchain Technology in Healthcare - Concepts, Methodologies, and Applications
Artificial Intelligence and Knowledge Processing: Methods and Applications
Handbook of Artificial Intelligence
Amazon Web Services: the Definitive Guide for Beginners and Advanced Users
The Role of AI in Enhancing IoT-Cloud Applications
50