December 8-11, 2025, Macau SAR, China
Intelligent, Distributed, and Trust‑Aware AIoT Systems
AIDE4IoT workshop will be held virtually online.
The Artificial Intelligence and Data Engineering for IoT (AIDE4IoT) Workshop builds on five successful editions of the IEEE BigData IoTDA series, evolving from IoT Data Analytics toward a broader, AI-oriented vision. The Internet of Things is no longer only about connecting billions of devices—it is about empowering intelligent, adaptive, and collaborative ecosystems that integrate AI, edge computing, and advanced data engineering to sense, reason, and operate in real time.
As IoT devices proliferate across homes, cities, industries, and scientific environments, they generate massive, heterogeneous, and fast-moving data streams. Processing this data efficiently and securely remains a major challenge. Traditional cloud-centric architectures face growing limitations in latency, scalability, and privacy. This has led to the rise of edge and fog computing, federated and continual learning, and lightweight, distributed AI models that can perform computation closer to where data is produced.
AIDE4IoT explores how Artificial Intelligence, Large Language Models (LLMs), and Data Engineering can converge to build sustainable, trustworthy, and resilient IoT systems. It emphasizes real-time stream processing, edge-native intelligence, and the operationalization of foundation models under resource constraints. The workshop also highlights emerging paradigms such as autonomous experimentation, AI-guided sensing, and self-optimizing IoT infrastructures that can adapt to dynamic environments with minimal human intervention.
The goal of AIDE4IoT is to provide researchers, engineers, and practitioners with a forum to discuss innovative solutions, exchange experiences, and build a vibrant community focused on shaping the next generation of AI-driven, decentralized, and sustainable IoT ecosystems. By fostering cross-disciplinary collaboration across AI, IoT, and data systems, the workshop seeks to advance both the technical foundations and ethical dimensions of intelligent connected environments.
The AIDE4IoT Workshop invites original research, experiments, and applications that explore how Artificial Intelligence (AI), Data Engineering, and the Internet of Things (IoT) converge to create intelligent, trustworthy, and sustainable systems.
Topics of interest include, but are not limited to:
AI and Machine Learning for IoT
Lightweight, distributed, and energy-efficient machine learning for edge and fog environments
Transformer distillation, on-device inference, and model compression for constrained devices
Federated, continual, and collaborative learning in decentralized IoT ecosystems
Large Language Models (LLMs) and foundation models for reasoning, decision support, and automation in IoT
Meta-learning, reinforcement learning, and adaptive AI for dynamic IoT contexts
Data Engineering and Analytics
Real-time stream analytics and adaptive dataflows for IoT and cyber-physical systems
Heterogeneous data fusion and multimodal analytics across edge–fog–cloud tiers
Data quality metrics, lineage tracking, and provenance for trustworthy IoT analytics
Distributed databases, storage optimization, and scalable data pipelines for IoT workloads
Benchmarking and open datasets for evaluating AIoT performance and fairness
Systems, Middleware, and Infrastructure
Middleware and orchestration frameworks for intelligent IoT and edge deployments
Micro-clouds, fog nodes, and hybrid architectures for low-latency data processing
Decentralized orchestration, resource allocation, and multi-agent coordination at the edge
Edge intelligence and analytic workloads for latency-sensitive and bandwidth-constrained systems
Process modeling and workflow automation for data-centric IoT applications
Trust, Privacy, and Security
Privacy-preserving and secure data analytics using differential privacy and federated learning
Trust, transparency, and explainability in AI-driven IoT systems
Adversarial robustness, anomaly detection, and resilience against data poisoning and spoofing attacks
Zero-trust and privacy-by-design architectures for connected systems
Ethical, legal, and social implications (ELSI) of AI-enabled IoT and autonomous experimentation
Sustainable and Human-Centric IoT
Green and resource-efficient AI for edge and IoT infrastructures
Human-in-the-loop AI for adaptive and safe decision-making
AI-guided sensing, prediction, and actuation for smart cities, energy, and environmental monitoring
Self-healing, adaptive, and self-optimizing IoT ecosystems
Sustainable AI engineering practices for long-term system maintainability
Applications and Emerging Domains
Smart cities, smart manufacturing, e-health, transportation, and environmental systems
Digital twins, robotic systems, and self-driving laboratories for scientific discovery
Autonomous scientific experimentation and AI-curated hypothesis generation
Context-aware and mobility-driven IoT services
Internet of Things as a Service (IoTaaS) and cloud-edge collaborative models
Nov 7, 2025 Due date for full workshop paper submissions (7:00PM AoE, 3:00AM EST, 12:00PM PST)
Nov 16, 2025: Notification of paper acceptance to authors
Nov 23, 2025: Camera-ready of accepted papers (firm date)
Dec. 8, 2025: Workshop Day (half-day, online)
Dec. 8-11, 2025: IEEE Big Data Conference
Co-Chairs:
Eyhab Al-Masri (University of Washington, USA)
Olivera Kotevska Oak Ridge National Laboratory (ORNL)
Program Committee Members:
Vikas Agarwal (IBM Research, India)
Amr Amrallah (KDDI Research, Inc., Japan)
Abdelmadjid Benarfa (University of Laghouat, Algeria)
Christian Beecks (University of Muenster, Germany)
Chi-Hua Chen (Chunghwa Telecom, Taiwan)
Mingzhe Chen (Princeton University, USA)
Subarna Chatterjee (Harvard University, USA)
Xuan-Hong Dang (IBM Thomas J. Watson Research Center, USA)
Mawaba Dao (Florida Institute of Technology, USA)
Abdelfatteh Haidine (Chouaib Doukkali University, Morocco)
Mohamed Hamdi (University of Toronto)
Ruksana Kabealo (Florida Institute of Technology, USA)
Sergey Kanzhelev (Google, USA)
Ahmed Kawther (Mustansiriyah University, Iraq)
Mena Olyan (University of Waterloo, Canada)
Lauritz Thamsen (Technische Universitat Berlin, Germany)
Angelo Trotta (University of Bologna, Italy)
We welcome contributions describing original ideas, experiments and applications relevant to the workshop theme which have not been published earlier or are not currently pending submission at any other venue. All submitted papers must include the names and affiliations of all authors. Submitted papers will be peer-reviewed by members of the Workshop Program Committee. All accepted papers will be included in the main conference proceedings (see Proceedings section below).
Submission Categories:
Long Papers: 8-10 pages (research at a mature stage, including references & appendices)
Short/Work-in-Progress Papers: 4-6 pages (early or intermediate stage, including references & appendices))
Paper Submission Link:
Templates:
https://www.ieee.org/conferences/publishing/templates.html
Camera Ready Instructions:
TBA
Proceedings:
All papers accepted will be included in the IEEE Big Data Conference Proceedings published by the IEEE Computer Society Press. At least one author of each accepted paper must register for the conference and present the paper at the workshop for the paper to be included in the conference proceedings. Details on the registration will be posted on the main conference's page.
Registration:
Full registration for IEEE BigData 2025 is required for at least one of the authors to participate in the workshop and have the paper published in the proceedings.