会議情報

SenSys 2026: ACM/IEEE Conference on Embedded Artificial Intelligence and Sensing Systems

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投稿締切日:
2025-11-06
通知日:
2026-01-29
開催日:
2026-05-11
開催地:
Saint-Malo, France
開催回数:
24
CCF: B   QUALIS: A1   閲覧: 71650   フォロー: 89   参加: 12

論文募集

SenSys 2026 (ACM/IEEE Conference on Embedded Artificial Intelligence and Sensing Systems) is a CCF B / QUALIS A1 conference held in Saint-Malo, France on 2026-05-11. The paper submission deadline is 2025-11-06. Acceptance notifications are sent on 2026-01-29.

We are excited to announce the International Conference on Embedded Artificial Intelligence and Sensing Systems (SenSys 2026), co-located with the CPS-IoT Week. SenSys 2026 merges SenSys, IPSN, and IoTDI into a single, top-ranked, flagship event. The original three conferences have driven innovation across multiple disciplines, including sensor networks, embedded systems, mobile computing, machine learning, wireless communications, signal processing, embedded AI, cyber-physical systems, and AI-driven applications. SenSys 2026 unites these communities to foster a high-impact forum that advances research at the intersection of sensing systems and embedded artificial intelligence. SenSys 2026 is still pending the final approval of ACM and IEEE. Regular technical papers will be published in the ACM conference proceedings, while demos and posters will be published in the IEEE conference proceedings. All content will be cross-indexed. Topics of Interest SenSys 2026 welcomes groundbreaking research in areas traditionally covered by SenSys, IPSN, and IoTDI, as well as other emerging fields. Topics include, but are not limited to: Sensors and Networked Sensing Systems Novel sensor technologies and deployments Heterogeneous sensor networks and data fusion Edge computing, fog computing, and real-time IoT/CPS systems Localization, synchronization, RFID, and RF sensing VLC and visible light-based sensing Digital twins for real-world systems and applications Platforms, Networking, and Communication Protocols New communication paradigms for ubiquitous connectivity Systems for extreme environments (e.g., underwater, aerial, space) Low-power wireless protocols Novel IoT protocols and network abstractions, including for 5G/6G and other architectures Satellite systems and applications, including CubeSats Embedded AI, Information Processing, and Machine Learning Resource-efficient machine learning for embedded and mobile platforms Information processing in sensor networks and embedded systems Large foundational models and their distillation to edge platforms Large language models and multi-modal large models for embedded systems Federated learning, neural architecture search for edge devices Collaborative sensing with AI-driven inference models Algorithms, Data, and Theory Analytic foundations for embedded sensing systems Data science-related issues, such as methods, tools, and analysis Coding, compression, and information theory Theoretical foundations and fundamental bounds Applications and Real-world Deployments Smart cities, smart buildings, and industrial IoT (IIoT) AR/VR and metaverse-inspired challenges Autonomous vehicles, unmanned aerial vehicles (UAVs), and drones Applications in healthcare, fitness, and wellness Personal, wearable, and other human-centric embedded systems Experiences from real-world deployments and lessons learned Security and Privacy in Embedded Sensing Systems Secure and privacy-sensitive sensing systems IoT data marketplaces, compression, and semantic summarization Decentralization and blockchain for embedded sensing systems Secure communications for the IoT Fault-tolerance, dependability, and robustness in embedded platforms and applications Fairness, equity, and transparency issues in IoT and CPS Novel Paradigms and Architectures for Embedded Sensing Systems Energy-efficient, sustainable system designs Edge AI and its implications for system latency, power, and complexity Human-machine interaction, including gesture recognition and voice-based systems IoT and CPS for sustainability, such as smart grids and energy management Visions, Experiences, Tools, Datasets, and Benchmarks (optional short paper format) Visions, grand challenges, or new directions Experiences, insights, challenges, and lessons learned from real-world deployments Benchmarks for evaluating systems, models, algorithms, or tools Tools, toolkits, or frameworks that advance research in embedded AI and sensing systems Datasets that support research in embedded AI and sensing systems Authors submitting papers in the last category (Visions, Experiences, Tools, Datasets, and Benchmarks) may choose between a full paper (12 pages) or a short paper (6 pages). Short papers will be judged on originality, potential impact, and clarity, even without extensive evaluation. Both types of papers will be presented orally at the conference.
最終更新：Dou Sun（）

採択率

平均採択率: 17.4% 10 年間 (2003–2017).

年投稿数採択数採択率(%)
20171512617.2%
20111232419.5%
20101452517.2%
20091192117.6%
20081532516.3%
20071492516.8%
20061222419.7%
20051182117.8%
20041452114.5%
20031372417.5%

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関連ジャーナル

CCF正式名称インパクトファクター出版社ISSN
Sensing and Bio-Sensing Research4.9Elsevier2214-1804
Design Automation for Embedded Systems0.9Springer0929-5585
BSoftware & Systems Modeling3.2Springer1619-1366
BPattern Recognition7.6Elsevier0031-3203
BIEEE Transactions on Neural Networks and Learning Systems8.9IEEE1045-9227
BInformation Sciences6.8Elsevier0020-0255
BComputer Networks4.6Elsevier1389-1286
BComputers & Security5.4Elsevier0167-4048
BIEEE Transactions on Intelligent Transportation Systems8.4IEEE1524-9050
BJournal of Systems and Software4.1Elsevier0164-1212

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