Conference Information

SmartData 2026: IEEE International Conference on Smart Data

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Submission Date:
2026-06-15
Notification Date:
2026-09-01
Conference Date:
2026-11-30
Location:
Montbeliard, France
Years:
12
Viewed: 25017   Tracked: 7   Attend: 0

Call For Papers

SmartData 2026 (IEEE International Conference on Smart Data) is an academic conference held in Montbeliard, France on 2026-11-30. The paper submission deadline is 2026-06-15. Acceptance notifications are sent on 2026-09-01.

Introduction Smart data aims to filter out the noise data and produce valuable data, which can be effectively used by enterprises and governments for planning, operation, monitoring, control, and intelligent decision making. Although unprecedentedly large amount of sensory data can be collected with the advancement of the Cyber-Physical-Social systems, the key is to explore how big data can become smart data and offer intelligence. Advanced big data modeling and analytics are indispensable for discovering the underlying structure from retrieved data and further acquiring smart data. The IEEE SmartData 2026 is to promote community-wide discussion identifying the computational intelligence technologies and theories for harvesting smart data from big data. It will provide a high-profile, leading-edge forum for scientists, engineers and researchers to discuss and exchange novel ideas, results, experiences and work-in-process on all aspects of smart data. Topics for submissions include but are not limited to the following theory, technology, and applications. Topics Topics for submissions include but not limited to the following: Track 1: Data Governance, Ethics & Foundations AI and Data Ethics Data Privacy & Security in the Age of LLMs Data Provenance, Trust & Lineage Fairness, Accountability & Transparency (FAT) in AI Modern Data Governance Strategies & Frameworks Data Quality, Cleaning & Integration Distributed & Decentralized Data Systems Blockchain for Data Management Track 2: Smart Data Infrastructure & Systems Cloud, Edge & Fog Computing for Smart Data High-Performance & Parallel Computing for Big Data Open Source Big Data Ecosystems (Spark, Flink, etc.) System Architectures for Smart Data Pipelines Energy-Efficient & Green Data Processing 6G-Enabled Data Infrastructure Serverless & Microservices Architectures Data Streaming & Real-Time Processing Track 3: Machine Learning & AI Algorithms Core Machine Learning & Deep Learning Algorithms Generative AI & Large Language Models (LLMs) Reinforcement Learning & Decision Making Federated & Collaborative Learning Transfer Learning & Domain Adaptation Explainable AI (XAI) & Interpretable Models Graph Neural Networks & Geometric Deep Learning Nature-Inspired & Evolutionary Computing Foundation Models & Multimodal AI Track 4: AI-driven Analytics & Cybersecurity Secure & Privacy-Preserving Analytics AI for Cybersecurity & Threat Intelligence Social Media, Web & Behavioral Analytics Graph Analytics & Network Science Anomaly Detection & Intrusion Detection Systems LLM-based Security Analysis & Vulnerability Detection Track 5: Smart Data Applications Smart Data Applications in All Fields (Health, Finance, etc.) Data as a Service (DaaS) & Data Marketplaces Smart City & Urban Computing Autonomous Systems & Self-Driving Vehicles Crowdsourcing & Human-in-the-Loop Systems Digital Twins & Simulation-Driven Data Ethical & Societal Impact of Smart Data Applications Track 6: Smart Data in Internet of Things (IoT) Network Design, Scheduling & Optimization for IoT Age of Information for Data Collection & Analytics in IoT Learning-Based Decision-Making with Smart Data in IoT Mobile Data Collection, Transmission & Analytics in IoT TinyML & Edge AI for Resource-Constrained IoT Devices Security & Privacy in IoT Data Ecosystems IoT Data Protocols & Standards (MQTT, CoAP, Matter) Ambient Intelligence & Smart Environment Sensing
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