2021 International Workshop on

Decentralized AI and Computing on IoT


July 14, 2021 (Virtual)


Important Dates

Paper Submission Deadline

June15, 2021

Acceptance Notification

June 30, 2021

Camera Ready Submission

July 5, 2021

Early Registration

July 8, 2021

Workshop Date

July 14, 2021

Scope

The objective of 2021 IEEE International Workshop on Decentralized AI and Computing on IoT (DACI2021) is to facilitate the exchange between researchers, engineers, and practitioners in Decentralized AI, one of the most promising trends in the AI and IoT fields, brings many new practices, opportunities, and at the same time, challenges. Emerging applications span over many areas, such as assisted living, wearable computer, mobile health, disaster relief, material delivery, autonomous transportation, robotics, emergency management, block chain, and many others. DACI aims to identify advancements, challenges and new opportunities in Decentralized AI and Computing on IoT.

With the quick boosting IoT and edge devices, as well as their increasing computing capabilities, how to leverage these resources to effectively advance a variety of emerging applications is crucial. Advanced research on the distributed AI architecture, wearable computing, edge computing, mobile health, machine learning and control, energy efficiency, implementation, trustworthiness, and various applications are all enabling factors for the field. The corresponding research outcomes, findings, and questions are of significant value to advance the field. DACI2021, will provide a high-quality forum for participants from the communities, and advance the discussion from theories and algorithms, to implementations and applications, as well as promising and emerging topics.


Topics of interest include but not limited to:

  • Distributed AI on Pervasive Devices

  • Mobile Health Monitoring and AI

  • Edge Computing

  • Wearable Monitoring and Computing

  • Distributed Big Data Mining on IoT

  • AI-backed IoT Security

  • Fog Computing

  • Pervasive Health Monitoring and Machine Learning

  • Scalable AI Implementation on IoT

  • Energy-efficient IoT Computing

  • Decentralized Learning and Control for Robotics

  • Decentralized AI in Smart City IoT

  • Decentralized AI in Smart Health IoT

  • Decentralized AI in Vehicle-to-X

  • Decentralized AI in Block Chain

  • Smart Contracts

  • Security and Privacy in Decentralized AI

  • Trustworthy Decentralized AI