In the era of Artificial General Intelligence, wireless artificial intelligent computing systems (WAICS), such as the Internet of Things, have emerged as critical data sources due to their extensive involvement of smart devices and superior capabilities for seamless data collection and communication across multiple dimensions. WAICS serves as an ideal foundation for data analysis across a wide array of platforms and applications. Within WAICS, participants bring their smart devices to form an interconnected, heterogeneous, and socialized system. These devices are linked both physically and contextually, enabling collaboration for data communication, where data collected from various devices provide a complementary and comprehensive representation of monitored objects. For instance, the Internet of Vehicles can jointly gather information depicting roadside conditions, with nearby vehicles communicating to achieve autonomous and intelligent operation.

However, efficient and effective data processing in WAICS is complex and presents challenges arising from both physical and contextual linkages. First, fundamental support for data collection and sharing is crucial, as WAICS increasingly powers AI-driven services that depend on the continuous and smooth sharing and processing of sensing data. Thus, reliable and scalable communication among devices is essential. Second, the contextual linkage among devices introduces challenges for advanced AI methods to effectively analyze data within WAICS. Smart devices collect data in more complex environments and tasks, which necessitates that methods for data analysis be more robust, adaptive, and personalized. Despite significant achievements in recent years, these challenges remain unresolved, particularly with the rise of novel technologies like large language models, digital twins, and the metaverse.

This special issue seeks innovative ideas and solutions that address the fundamental challenges of efficient and effective data processing in WAICS. Contributions may include, but are not limited to, novel theories, frameworks, methodologies, techniques, and applications across data sensing, management, communication, and computing. We hope this special issue will establish a virtual research forum for gathering and sharing insights that will advance the design and implementation of WAICS.

The topics of interest include, but are not limited to

• Fundamental theories and concepts supporting data processing in WAICS
• Design of novel protocols for wireless communication in WAICS
• Design and analysis of network topologies for WAICS
• Paradigms and models for data acquisition and sharing in WAICS
• Data storage and data management in WAICS
• Security and data privacy in WAICS
• Fairness, rationality and sustainability for data processing in WAICS
• Machine learning and deep learning models for data processing in WAICS
• Computer vision techniques for services upon WAICS
• Design of federated learning upon WAICS
• Design of digital twins and metaverse upon WAICS
• Design of online social networks upon WAICS
• Novel sensing devices and communication techniques for WAICS
• Design on data visualization for WAICS
• Demos, applications and systems for WAICS

SUBMISSION GUIDELINES

Authors should prepare papers in accordance with the format requirements of Tsinghua Science and Technology, with reference to the Instruction given at https://www.sciopen.com/journal/1007-0214, and submit the complete manuscript through the online manuscript submission system at https://mc03.manuscriptcentral.com/tst with manuscript type as “Special Issue on AdvancedWAICS”.

Important Dates

Submission Deadline: October 30, 2024

Guest Editors

Zhipeng Cai, IEEE Fellow, Georgia State University, USA, zcai@gsu.edu

Suparna De, University of Surrey, UK, s.de@ieee.org

Yue Wang, Georgia State University, USA, ywang182@gsu.edu

Honghui Xu, Kennesaw State University, USA, hxu10@kennesaw.edu