Special Issue "Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities"

Submission Deadline: 30 September 2021
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Guest Editors
Dr. Shabir Ahmad, Gachon University, South Korea.
Dr. Muhammad Fayaz, University of Central Asia, Russia.
Dr. Faheem Khan, University of Laki Marwat, Pakistan.

Summary

The Internet of Things (IoT) has been playing a vital role in adding value to human lives. In recent years, IoT applications have been coupled with Machine Learning techniques to form Intelligent IoT applications. However, for intelligent IoT nodes, the machine learning technologies should be lightweight to meet the constrained capabilities of the embedded hardware. This Special Issue aims to highlight advances in the open research topics in this field, which include, but are not limited to, the following:

1. Optimize Existing Machine Learning architecture for embedded IoT devices;

2. Lightweight Machine Learning architecture and frameworks;

3. Distributed Predictive Optimization;

4. Communication network design and optimization;

5. Energy saving and energy harvesting methods and techniques;

6. Blockchain for security and privacy;

7. Data collection and management methods (big data and data retrieval);

8. Data replication and distribution management on IoT edge nodes;

9. Lightweight Intelligent IoT service orchestration;

10. Intelligent IoT for lightweight driver assistance systems in Electric Vehicles.


Keywords
Model Optimization
Smart Cities
Internet of Things
Blockchain
Service Orchestration
Computer Vision
Medical Image Processing
Digital Twin
Virtualization