会議情報

EWSN 2026: International Conference on Embedded Wireless Systems and Networks

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提出日:
2026-04-24
通知日:
2026-06-15
会議日:
2026-09-16
場所:
Dresden, Germany
年:
23
CORE: a   QUALIS: a2   閲覧: 35416   追跡: 12   出席: 2

論文募集

EWSN 2026 (International Conference on Embedded Wireless Systems and Networks) is a CORE A / QUALIS A2 conference held in Dresden, Germany on 2026-09-16. The paper submission deadline is 2026-04-24. Acceptance notifications are sent on 2026-06-15.

The International Conference on Embedded Wireless Systems and Networks (EWSN) is a highly selective single-track international conference focusing on the latest research in embedded systems and wireless networking and their role as key enablers for visionary scenarios such as the Internet of Things and Cyber-Physical Systems. EWSN invites recent research on networked sensor systems and platforms, the Internet of Things, embedded/edge machine learning, and novel sensor network applications. Feature Topic: Sustainable Embedded Intelligence While the conference welcomes all papers within the scope described above, this year’s edition of EWSN will also highlight a feature topic in Sustainable Embedded Intelligence - an area at the convergence of ultra-low-power AI hardware design, energy-efficient AI algorithms, and reliable low-power communications. This rapidly evolving field is essential for realizing long-lasting, autonomous, and reliable wireless sensor network systems. We especially welcome contributions at the boundary of chip-level innovation and system-level performance, allowing our community to directly engage the expertise and high-tech ecosystem of our host city, a renowned international hotspot for microelectronics. Specific topics for the conference include (but are not exclusively limited to): Sustainable Embedded Intelligence: Boundary between chip-level innovation and system-level performance Applications of wireless embedded networks: Health, automation, manufacturing, transportation, smart cities, etc. Communication and networking for wireless and embedded systems Computing architectures for networked embedded systems Dependability in wireless systems, including reliability, availability, safety, and real-time guarantees Edge-cloud solutions for networked embedded systems Edge/embedded intelligence paradigms, models, and techniques for networked embedded systems Embedded systems for joint sensing and communication with mmWave, Terahertz, Wi-Fi, visible light, etc. Empirical studies, measurement, deployment, and experience reports Experiences, challenges, comparisons of platforms Foundational models: Sensor data analytics, distillation to edge platforms Localization, synchronization, RFID, and RF sensing Machine learning: Deep, federated and multimodal learning on sensor data Machine learning: Computer vision, natural language processing for resource-constrained and mobile platforms Modeling, simulation, and measurement tools for wireless systems New hardware and system design to enable machine learning on sensor data Next-generation/novel wireless networks, including 6G, Wi-Fi HaLow, NearLink Operating systems, middleware, and services for networked embedded systems Privacy and security in networked embedded systems and applications Processing, storage, and management of data in embedded wireless networks Sensor data processing for augmented and virtual reality applications Wearable systems and data processing algorithms The conference will accept two types of papers – Full Papers (max 12 pages) and Short Papers (max 6 pages). Short papers are intended to present preliminary research results or advocate for new research directions; their titles should be prepended with one of the following: “Vision paper:”, “Position paper:”, or “WiP paper:” when they are submitted for review. Authors should carefully consider the distinction between Full Papers and Short Papers; papers submitted in one category will not be considered in the other category.
最終更新 Dou Sun

合格率

Average acceptance rate: 21.5% over 11 years (2004–2014).

時間提出受け入れ受け入れ(%)
2014501224%
2013511223.5%
2012781620.5%
2011871416.1%
20101092119.3%
20091452315.9%
20081102320.9%
20071642213.4%
20061332115.8%
20051003535%
2004762431.6%

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