IEEE Annual Congress on Artificial Intelligence of Things (IEEE AIoT)

3-5 Dec 2025 · Osaka, Japan.

http://www.ieee-aiot.org/2025

Call for Papers

IEEE AIoT 2025 aims at bringing together interested parties (universities, research centers, industries and stakeholders) from around the world working in the fields of AI and Internet of Things to exchange opinions, discuss brand-new ideas, developing innovative and emerging solutions, and establishing new collaborations.

Scope and Objectives

Artificial Intelligence (AI) and the Internet of Things (IoT) are two of the most rapidly evolving and interdependent fields of technology. The convergence of these two fields is leading to the creation of an emerging interdiscipline field, dubbed the Artificial Intelligence of Things (AIoT). The AIoT represents the integration of AI technologies into IoT systems and devices, enabling them to interact with their environment in more sophisticated and intelligent ways. By combining IoT with AI, the data collected by distributed nodes can be utilized by applying AI techniques such as machine learning and deep learning. As a result, machine learning capabilities are moved closer to the data source.

The IEEE AIoT Conference aims to explore the integration of artificial intelligence (AI) technologies into the Internet of Things (IoT) systems and devices, enabling them to interact with their environment in more sophisticated and intelligent ways. The conference will focus on the following areas:

• AIoT Architectures, Frameworks, and Algorithms: Developing novel AIoT architectures, frameworks, and algorithms for deploying state-of-the-art machine learning and deep learning algorithms on IoT and edge devices, realising the so-called Edge AI or Edge Intelligence;
• AIoT Applications: Identifying and exploring new AIoT applications, including healthcare, smart homes, industrial automation, transportation, and digital agriculture;
• Standards and Interoperability: Developing standards and protocols for AIoT systems and ensuring interoperability between different platforms and devices; and
• Ethics and Security: Addressing ethical and security concerns related to AIoT, such as privacy, transparency, and accountability.

Authors are cordially invited to submit their original papers within the artificial intelligence of things area. The topics include but are not limited to:

1. Edge Computing and Intelligence in AI and IoT
2. Machine Learning for IoT Applications
3. Mobile deployment of Large Language Models (LLMs)
4. LLMs for AIoT applications
5. Smart Cities: AI and IoT Solutions
6. Security and Privacy in AI-driven IoT Systems
7. 5G and its Impact on AI and IoT
8. Blockchain Technology for Securing IoT Devices
9. Human-Machine Interaction in IoT Environments
10. IoT Sensors and Actuators: Innovations and Advances
11. AI-driven Predictive Maintenance in IoT
12. Energy-Efficient AI Algorithms for IoT Devices
13. IoT in Healthcare: Applications and Challenges
14. Industrial IoT (IIoT) and AI for Manufacturing
15. Smart Agriculture: AI and IoT in Precision Farming
16. Ethical Considerations in AI-powered IoT Systems
17. IoT Standards and Interoperability
18. Robotic Process Automation (RPA) in IoT
19. AI-driven Automation in Supply Chain Management
20. IoT Analytics and Big Data Processing
21. AI in Edge Devices: Challenges and Solutions
22. Wireless Sensor Networks in AI and IoT
23. IoT for Environmental Monitoring and Sustainability
24. AI and IoT in Transportation and Logistics
25. Cross-domain Integration of AI and IoT Technologies

Track 1: Big Data Analytics and IoT Applications(Track CFP)

• Scalable data analytics for IoT ecosystems
• Real-time data processing and stream analytics
• IoT-enabled smart cities and urban planning
• Predictive maintenance using IoT and machine learning
• Edge and fog computing for IoT applications
• Cybersecurity and privacy-preserving analytics in IoT systems
• AI-driven insights from IoT-generated big data
• Blockchain for secure IoT networks
• Smart healthcare applications with IoT and big data
• Industrial IoT (IIoT) for manufacturing and supply chain optimization
• Advanced data mining techniques for massive data

Track 2: AI for IoT Communications and Networking (Track CFP)

• AI-enhanced Authentication for IoT Devices
• AI-based Access Control for IoT
• AI for Truth Verification and Management in IoT
• AI for Data Privacy in IoT Devices and Services
• Federated Learning in IoT Security
• Edge-Deployed AI Security in IoT
• Incentive Strategies for AI Interaction in IoT
• AI Applications for Smart City IoT Security
• Data Security for AI-powered IoT
• Attacks Prevention in Software-Defined IoT leveraging AI
• Security in SD-IoT leveraging AI
• Privacy-enhancing Technologies in Intelligent IoT Systems
• AI-enabled Attacks and Defenses for IoT Devices and Services
• AI for Communication Security of IoT Devices
• Malware Analysis for Intelligent IoT
• Vulnerability Analysis for AI-integrated IoT Devices
• Intelligent Forensics Tools, Techniques, and Procedures for IoT
• Emerging Data Bias Security Issues in Intelligent IoT Systems
• Lightweight Hardware Verification in Intelligent IoT Systems

Track 3: Edge, Cloud, and Fog Computing in IoT (Track CFP)

• Resource management and allocation in Edge-Fog-Cloud for IoT
• Joint scheduling and optimization of networking and distributed computing resources for IoT
• Edge/fog computing and network services architecture for IoT
• IoT Middleware for cloud/fog computing applications
• Resource slicing in the IoT computing continuum
• Autonomic distributed service and network management
• Business models for the IoT computing continuum
• QoS/QoE management for static and mobile IoT applications in Edge-Fog-Cloud
• Machine learning and distributed learning for edge-fog-cloud resource management for IoT
• Distributed learning deployment, management and applications for IoT
• DNN Partitioning and Offloading in Edge-Fog-Cloud for IoT
• AI Models (including LLMs) with edge-fog-cloud computing: inference and training
• IoT-enabled Edge Intelligence
• AI empowered autonomous edge intelligence for IoT
• Edge Computing Architectures and Protocols for IoT
• Cloud and Fog Computing for Scalable IoT Systems
• Fog Computing as an IoT Middleware
• Fog and Edge Networking in IoT
• Security and Privacy for IoT in Edge, Cloud, and Fog Computing
• Latency Optimization and Real-time Processing in IoT
• AI and Machine Learning in Edge, Cloud, and Fog IoT
• IoT Data Management and Distributed Storage
• Energy-Efficient IoT Systems with Edge and Fog Computing
• IoT Integration with 5G and Next-Generation Networks
• IoT in Smart Cities: Leveraging Edge, Cloud, and Fog Computing
• IoT Application Case Studies
• Industrial IoT (IIoT) and Edge, Cloud and Fog Computing
• Interoperability and Standardization in IoT Computing Models
• Next-Generation Computing Models for IoT

Track 4: Security, Trust, Privacy in AI and IoT(Track CFP)

• AI-enhanced Authentication for IoT Devices
• AI-based Access Control for IoT
• AI for Truth Verification and Management in IoT
• AI for Data Privacy in IoT Devices and Services
• Federated Learning in IoT Security
• Edge-Deployed AI Security in IoT
• Incentive Strategies for AI Interaction in IoT
• AI Applications for Smart City IoT Security
• Data Security for AI-powered IoT
• Privacy-enhancing Technologies in Intelligent IoT Systems
• AI-enabled Attacks and Defenses for IoT Devices and Services
• AI for Communication Security of IoT Devices
• Malware Analysis for Intelligent IoT
• Vulnerability Analysis for AI-integrated IoT Devices
• Intelligent Forensics Tools, Techniques, and Procedures for IoT
• Emerging Data Bias Security Issues in Intelligent IoT Systems
• Lightweight Hardware Verification in Intelligent IoT Systems
• Side-Channel Attacks and Defense in Intelligent IoT Systems
• The implications of machine unlearning for security, trust, and privacy in AI and IoT

Track 5: Ubiquitous IoT: Space, Air, Ground, and Sea (Track CFP)

• Energy-efficient tinyML for critical applications
• Trustworthy AI for autonomous vehicles
• Federated Learning in mission control and decision support
• Satellite-enabled communication for Ubiquitous IoT platforms
• 5G/6G network slicing for civil and military platforms
• AI-assisted Cyberwarfare in Beyond Visual Line of Sight (BVLOS) communications
• Securing AI-enabled IoT and OT platforms

Submission Procedures

Submitted manuscripts must be prepared according to IEEE Computer Society Proceedings Format (double column, 10pt font, letter paper) and submitted in the PDF format. The manuscript submitted for review should be no longer than 8 pages. After the manuscript is accepted, the camera-ready paper may have up to 10 pages, subject to an additional fee per extra page. Manuscripts should be submitted to one of the research tracks. Submitted manuscripts must not contain previously published material or be under consideration for publication in another conference or journal at the time of submission. The accepted papers will be included in IEEE Xplore.

Paper Submission and Publication

Details of paper submission and publication can be found here.

Organization Committee

Details of organization committee can be found here.

Important Dates

• July 1, 2025

  Paper Submission Due

• October 3, 2025

  Notification of Acceptance

• November 3, 2025

  Final Manuscript (Camera Ready)