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Our journal welcomes not only original high-quality papers covering the theoretical, experimental and operational aspects of electrical and electronics engineering in mobile radio, motor vehicles and land transportation, but also industry-focused publication focusing on research findings and suggesting ideas that may be useful to those conducting similar research.
In the following, let us provide you with a one-stop destination to know about a recently published article from our industry authors on the use of AI to address the challenge of automating construction site, as well as an article from highly cited researchers on the use of a novel data-oriented approach to clusters of IoT devices. We hope that the short summary of these feature articles written in layman language may make your reading a pleasure!
Decentralized and Asymmetric Multi-Agent Learning in Construction Sites
Yakov Miron, Dan Navon, Yuval Goldfracht, Dotan Di Castro, and Itzik Klein
Full article: IEEE Open Journal of Vehicular Technology, Volume 5
Summary by Yakov Miron: This research tackles the challenge of automating construction site operations by teaching heavy machinery like bulldozers and dump trucks to work together without crashing into each other. By using advanced AI techniques, the study trains these machines to independently plan their movements while understanding and avoiding the actions of others. This decentralized approach not only improves safety but also boosts efficiency in tasks like leveling land or transporting materials. What makes it stand out is the use of behavior cloning—a method where machines learn by mimicking expert strategies—to bridge the gap between simulations and real-world construction environments. The study also introduces a novel way for each machine to focus on its unique task while sharing crucial environmental data, creating seamless teamwork. Ultimately, this research represents a leap forward in making construction sites not just smarter, but also safer and more cost-effective.
Data-Oriented Analysis of Uplink Transmission in Massive IoT System with Limited Channel Information
Jyri Hämäläinen, Rui Dinis, and Mehmet C. Ilter
Full article: IEEE Open Journal of Vehicular Technology, Volume 5
Summary by Rui Dinis: With the growing number of uses for wireless communication, some transmission sessions are now very short and can happen irregularly, i.e., short updates or control signaling between end devices. Traditional transmission strategies, which are optimized for average performance, might not work well in these cases. To address this, a new “data-oriented” design approach was emerged, where the design has started to focus on “session-specific” parameters like the amount of data and available bandwidth unlike the existing approach in place for existing wireless generations. In this work, we have applied data-oriented approach to clusters of IoT devices, where they cooperate with each other along with limited channel information, and have introduced new service requirement formulation based on the data-oriented method.
About the IEEE Open Journal of Vehicular Technology (OJVT)
The IEEE OJVT covers the theoretical, experimental and operational aspects of electrical and electronics engineering in mobile radio, motor vehicles and land transportation. A brief summary of these fields of interest are as follows:
- Mobile radio shall include all terrestrial mobile services
- Motor vehicles shall include the components and systems and motive power for propulsion and auxiliary functions
- Land transportation shall include the components and systems used in both automated and non-automated facets of ground transport technology
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