Call for Papers

Background:

Semantic communication, a concept first discussed by Shannon and Weaver in 1949, classifies communication challenges into three distinct levels: physical, semantic, and effectiveness. The physical problem concerns the accurate and reliable transmission of the raw data content of a message, which led to the development of information theory—a field that has profoundly influenced modern communication technologies. The semantic problem, in contrast, deals with ensuring that the intended meaning or context of a message is accurately delivered to the receiver. Finally, the effectiveness problem focuses on determining whether the message achieves its intended purpose or prompts the desired action from the recipient. While advancements in physical communications have progressed exponentially since the early days of information theory, laying the groundwork for today's high-performance gaming, entertainment, and media ecosystems, semantic communication has remained underexplored for decades. This stagnation can largely be attributed to the absence of computational and theoretical tools required to implement semantic communication systems effectively.Recent advancements in deep learning, natural language processing (NLP), and computational performance have made it possible to revisit semantic communication as a practical and transformative paradigm. Unlike traditional communication methods that prioritize transmitting raw data with high fidelity, semantic communication focuses on delivering meaning, intent, or relevance while minimizing unnecessary data redundancy. This shift is particularly relevant for addressing modern challenges, such as the growing demand for bandwidth-intensive applications, low-latency connectivity, and efficient energy use in data transmission. Semantic communication enables intelligent and context-aware transmission, making it a promising solution to improve the capacity, scalability, and reliability of current and future communication systems. In summary, semantic communication is revolutionizing media compression and transmission by emphasizing meaning over raw data. This paradigm aligns well with the challenges of next-generation networks, such as 5G, 6G, and IoT, which require solutions for bandwidth optimization, latency reduction, and scalability. Its applications span a wide range of fields, including entertainment, gaming, smart devices, and autonomous systems, making it a critical component of future communication systems.

Goal/Rationale:

In conventional transmission systems, data transmission occurs at the bit level, where the source—whether it be text, audio, images, or video—is converted into a sequence of bits for transmission. At the receiver's end, this bit sequence is decoded to recover the original data. A variety of compression techniques have been developed to efficiently transmit data over limited bandwidth channels. However, all existing compression and transmission methods operate within the constraints of Shannon capacity, which defines the theoretical maximum data rate that can be transmitted over a communication channel without error. These techniques aim to optimize the transmission of data by minimizing distortion, but they still rely on bit-level representations that may not be the most efficient for specific tasks.Traditional bit-level communication systems focus primarily on minimizing distortion during data transmission over physical channels. However, when the goal is to recover data for specific tasks—such as classification, object detection, image segmentation, or similar applications—the bit-level recovery process often results in poor performance. This is because the distortion introduced by the compression techniques affects the task's effectiveness at the receiver's end. Moreover, in bandwidth-constrained environments such as mobile communication channels, conventional bit-level compression techniques have reached their limits in optimizing rate-distortion trade-offs. This is especially problematic when handling the growing demands of real-time, high-resolution multimedia content, such as high-definition video streaming and interactive gaming.

As the scope of data communication has evolved, a significant portion of content—such as text, audio, images, and video—is increasingly analyzed and processed by machines rather than humans. This shift makes it critical to optimize transmission and compression techniques for machine-to-machine (M2M) and machine-to-human (M2H) communication systems. With the proliferation of video-based communications in sectors like autonomous driving, smart factories, gaming, IoT, and remote sensing, there is a growing strain on the already bandwidth-constrained channels. These applications, particularly those involving real-time interactions with high-resolution video, present a significant challenge for conventional communication systems, which are not designed to efficiently handle such high-demand scenarios. While existing systems may manage these tasks in controlled environments, they are unable to meet the needs of modern Video IoT (VIoT) applications in fields like digital manufacturing or autonomous vehicles, where real-time, high-resolution video transmission between devices and humans is critical.

Scope and Information for Participants:

Learning semantic communication concepts is becoming increasingly important for a range of professionals and researchers in various fields. Professionals and researchers across multiple fields need to learn semantic communication concepts to stay at the forefront of technological advancements. These include engineers and developers in telecommunications, media compression, and streaming technologies, who are optimizing bandwidth and enhancing efficiency. AI and machine learning experts, particularly in areas like natural language processing and personalized content delivery, rely on semantic understanding for better decision-making systems. VioT/IoT developers and smart city planners use these concepts to transmit meaningful data in resource-constrained environments. Additionally, cybersecurity professionals must understand semantic communication to ensure secure and privacy-preserving data transmission. Scholars, data scientists, and policymakers also benefit from grasping these ideas to drive innovation, set standards, and regulate emerging technologies.

This symposium will explore how semantic communication can address these emerging challenges in media communications. We will examine how semantic communication can reduce the strain on bandwidth by transmitting only the relevant features needed for specific tasks, thereby optimizing network resources. Additionally, the tutorial will discuss the potential challenges of implementing semantic communication systems and outline strategies to overcome these obstacles. Beyond the communication between people and machines, we will also focus on communication between devices, processes, and objects, highlighting how semantic communication can support the growing complexity of machine-to-machine and device-to-device communication in next-generation networks.

Submission:

Prospective authors are kindly invited to submit full papers that include title, abstract, introduction, tables, figures, conclusion and references. It is unnecessary to submit an abstract in advance. Please submit your papers in English.

Each paper should be no less than 4 pages. One regular registration can cover a paper of 6 pages, and additional pages will be charged. Please format your paper well according to the conference template before submission. Paper Template Download

Please prepare your paper in both .doc/.docx and .pdf format and submit your full paper by email with both formats attached directly to [email protected]

Important Dates:

Publication:

Accepted papers of the symposium will be published in Applied and Computational Engineering (ACE) (Print ISSN 2755-2721), and will be submitted to Conference Proceedings Citation Index (CPCI), Crossref, CNKI, Portico, Engineering Village (Inspec), Google Scholar, and other databases for indexing. The situation may be affected by factors among databases like processing time, workflow, policy, etc.

Publication info

Title: Applied and Computational Engineering (ACE)
Press: EWA Publishing, United Kingdom
ISSN: 2755-2721 2755-273X (electronic)

This symposium is organized by CONF-FMCE 2025 and it will independently proceed the submission and publication process.

* The papers will be exported to production and publication on a regular basis. Early-registered papers are expected to be published online earlier.