The AI Revolution: Driving the Evolution of Robotics and Smart Systems

Topic Information

Dear Colleagues,

The integration of Artificial Intelligence (AI) into robotics and smart systems is ushering in a new era of innovation and efficiency. This call for papers invites researchers, practitioners, and industry experts to explore AI-driven advancements in robotics, machine learning, and intelligent systems. The topics of interest include, but are not limited to, autonomous robotics, AI in industrial automation, smart home, and city technologies, healthcare robotics, human–robot interaction, and ethical considerations in AI deployment. We seek groundbreaking research, case studies, and practical applications that demonstrate how AI can enable smarter, more adaptive, and autonomous systems across various sectors. Accepted papers will contribute to a deeper understanding of AI’s role in shaping future technologies and driving digital transformation for a more sustainable, efficient, and intelligent society.

Dr. Zhan Li
Dr. Chunxu Li
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
AI ai	5.0	6.9	2020	20.7 Days	CHF 1600	Submit
Automation automation	2.0	4.1	2020	23.4 Days	CHF 1200	Submit
Sensors sensors	3.5	8.2	2001	19.7 Days	CHF 2600	Submit
Smart Cities smartcities	5.5	14.7	2018	26.8 Days	CHF 2000	Submit
Technologies technologies	3.6	8.5	2013	21.8 Days	CHF 1600	Submit

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Published Papers (1 paper)

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All AI Automation Sensors Smart Cities Technologies

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Open AccessReview

Recent Advances in Portable Dry Electrode EEG: Architecture and Applications in Brain-Computer Interfaces

by Meihong Zhang, Bocheng Qian, Jianming Gao, Shaokai Zhao, Yibo Cui, Zhiguo Luo, Kecheng Shi and Erwei Yin

Sensors 2025, 25(16), 5215; https://doi.org/10.3390/s25165215 - 21 Aug 2025

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Abstract

As brain–computer interface (BCI) technology continues to advance, research on human brain function has gradually transitioned from theoretical investigation to practical engineering applications. To support EEG signal acquisition in a variety of real-world scenarios, BCI electrode systems must demonstrate a balanced combination of [...] Read more.

As brain–computer interface (BCI) technology continues to advance, research on human brain function has gradually transitioned from theoretical investigation to practical engineering applications. To support EEG signal acquisition in a variety of real-world scenarios, BCI electrode systems must demonstrate a balanced combination of electrical performance, wearing comfort, and portability. Dry electrodes have emerged as a promising alternative for EEG acquisition due to their ability to operate without conductive gel or complex skin preparation. This paper reviews the latest progress in dry electrode EEG systems, summarizing key achievements in hardware design with a focus on structural innovation and material development. It also examines application advances in several representative BCI domains, including emotion recognition, fatigue and drowsiness detection, motor imagery, and steady-state visual evoked potentials, while analyzing system-level performance. Finally, the paper critically assesses existing challenges and identifies critical future research priorities. Key recommendations include developing a standardized evaluation framework to bolster research reliability, enhancing generalization performance, and fostering coordinated hardware-algorithm optimization. These steps are crucial for advancing the practical implementation of these technologies across diverse scenarios. With this survey, we aim to offer a comprehensive reference and roadmap for researchers engaged in the development and implementation of next-generation dry electrode EEG-based BCI systems. Full article

(This article belongs to the Topic The AI Revolution: Driving the Evolution of Robotics and Smart Systems)

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