|
Standards encourage innovation in the industry and shorten the time-to-market of products and technologies. We welcome any submission focusing on research findings from standards development activities, especially those from IEEE Standards Association, that are primarily of interest to our Society membership. In addition, we welcome 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 two recently published articles from our industry authors: one is related to the millimeter-based IEEE 802.11 sensing and another is related to the development of a smart EV charging recommender system. We hope that the short summary of these feature articles written in layman language may make your reading a pleasure.
Invited paper: IEEE 802.11bf DMG Sensing: Enabling High-Resolution mmWave Wi-Fi Sensing
Steve Blandino, Tanguy Ropitault, Claudio R. C. M. da Silva, Anirudha Sahoo, and Nada Golmie
Full article: IEEE Open Journal of Vehicular Technology, Volume 5
Summary by Steve Blandino: Wi-Fi is no longer just for communication: the latest extension of IEEE 802.11bf includes sensing capabilities, where Wi-Fi systems can recognize gestures, monitor heart rates, and track objects in real time, all while minimizing the impact on communication performance. Our analysis highlights the key features of the Directional Multi-Gigabit (DMG) sensing procedure in IEEE 802.11bf and the revisions to the existing specifications to enable high-resolution mmWave Wi-Fi sensing. We develop an open-source simulation platform to evaluate the DMG sensing performance and quantify the sensing accuracy and the overhead introduced on the data transmission.
A Physics-Informed Cold-Start Capability for xEV Charging Recommender System
Raik Orbay, Aditya Pratap Singh, Johannes Emilsson, Michele Becciani, Evelina Wikner, and Victor Gustafson
Full article: IEEE Open Journal of Vehicular Technology, Volume 5
Summary by Aditya Pratap Singh: This research develops a smart system to improve electric vehicle (EV) charging by personalizing power recommendations based on battery behavior and driving habits. It solves the "cold-start problem," where little user data exists, by using physics-based battery models and AI-driven simulations. The system predicts ideal charging patterns, tailoring recommendations to driving styles for example aggressive drivers get faster, high-energy charging curves, while cautious drivers get lower-energy options. In the research several key charging patterns were identified to cover most user needs. This approach enables the system to function effectively even without extensive user data. Through enhancing charging speed, safety, and user satisfaction, this solution aims to boost EV adoption and create a better experience for drivers.
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
| 
