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ICIEA2021 Special Session on Artificial Intelligence for Industrial Internet of Things (IIoT)


Session Organizers: Zhenghua Chen and Yanbing Yang and Chaoyang Jiang


CALL FOR PAPERS

Industrial Internet of Things (IIoT) has attracted much attention in recent years, due to its great potential for improving productivity and reliability of industrial systems. It consists of several key components, e.g., sensors, communication modules, actuators, edge devices, etc. By leveraging intelligent sensing, effective communication, smart monitoring and operation, IIoT builds a complete ecosystem for various industrial applications, such as smart manufacturing, smart building and smart city. With the huge data generated by IIoT, how to effectively gather and analyse the data will play a key role. Artificial intelligence can be an idea candidate with its strong capacity for data analytics.

 

This invited session intends to prompt emerging techniques on artificial intelligence for IIoT applications. Original innovative research papers addressing the following technology areas and their potential applications are invited:

 

•   Intelligent Sensing: localization, navigation, human computer interaction, machine health monitoring, fault diagnosis and prognosis

 

    Advanced Communication: visible light communication, 5G, LoRa, WiFi

 

•   Efficient Operation: Block chain, evolutional computing, multi-objective optimization

 

•  Edge Computing: model compression, neural network pruning, knowledge distillation

 

Submissions:

Papers are invited from prospective authors with interest on the related areas. All papers must be submitted electronically in PDF format by the submission deadline.


Special Session Organizers:
Zhenghua Chen, Institute for Infocomm Research (I2R) A*STAR, Singapore

Chen_zhenghua@i2r.a-star.edu.sg


Yanbing Yang, College of Computer Science, Sichuan University, Chengdu, China

yangyanbing@scu.edu.cn

 

Chaoyang Jiang, School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China

cjiang@bit.edu.cn

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