Technology 5G Network Slicing *Enhanced Mobile Broad Band (eMBB) *Ultra Reliable Low Latency Communication (URLLC) *Massive Machine Type Communication (mMTC) Fog/Edge Computing *Multi-access Edge Computing (MEC) Industrial Use Case Smart Mobility *V2X: Vehicle-to-Vehicle, Vehicle-to-Infrastructure, Vehicle-to-Network, Vehicle-to-Pedestrian Smart Manufacturing *Industry 4.0

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5G Based AI + Blockchain + IoT Convergence AT A Glance
Alex G. Lee1
Technology/Use Case AI Bloclkchain IoT
Technology
5G Network Slicing
*Enhanced Mobile
Broad Band (eMBB)
*Ultra Reliable Low
Latency Communication
(URLLC)
*Massive Machine Type
Communication
(mMTC)
Fog/Edge Computing
*Multi-access Edge
Computing (MEC)
Dynamic network slicing resource
management using reinforcement
learning (e.g., prediction of the
network load of each network slice
based on the incoming connection
and slice usage history; allocation
of incoming devices to appropriate
slice depending on the predicted
network load; dynamically
monitor and predict network
resource utilization); Dynamic
network slicing broker building;
Detection of anomalous behavior
in a network slice
Deep learning based optimal
management and maintenance
(e.g., adaptive edge caching;
optimized edge computing task
offloading, energy consumption
per bit minimization, application
Distributed market for network
slicing brokerage (e.g.,
autonomous slice provisioning
and deployment using secure
real-time dynamic resource
exchange via smart contracts and
consensus algorithms);
Traceability and tracking of
resource usage and dynamic
resource allocation during
dynamic slice usage to meet
SLAs (Service Level
Agreements)
Secure and privacy-preserving
task sharing/offloading processes
among MEC servers at the edge
level (e.g., offloading
traceability, secure resource
trading, smart contract-based
The network slicing can provide
optimized security for IoT
IoT edge networks in
collaboration with MEC servers
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Alex G. Lee, Ph.D Esq., is a principal consultant at TechIPm, LLC.

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relocation optimization, predictive
maintenance of MEC equipments);
Secure offloading against jamming
Attacks; Multi-agent distributed
AI for cooperation and resource
sharing
access control); Facilitating
collaboration among MEC
servers and across different
MEC service providers; Cloud
sourcing for computing/storage
resources
Industrial Use Case
Smart Mobility
*V2X: Vehicle-to-
Vehicle, Vehicle-to-
Infrastructure, Vehicle-
to-Network, Vehicle-to-
Pedestrian
Network slicing optimization for
5G V2X (e.g., traffic safety
service exploiting V2V,
autonomous driving exploiting
V2X, provision/update of HD
maps in real time); MEC server-
assisted hierarchical federated
learning for privacy-preserving
automotive deep learning
applications exploiting 5G V2X
communication (e.g., object
detection and tracking, road
change/events detection,
localization and mapping);
Reinforcement learning based
shared mobility rebalancing
Autonomous management of
MEC resources: offloading/
streaming orchestration for
autonomous vehicle; Secure data
sharing/networking mechanism
for vehicular network;
Decentralized car-sharing/car-
pooling/ride-hailing platforms
Internet of Vehicle (IoV)
network ; Sensor fusion of
vehicular IoT sensing data;
Surrounding/Environment
monitoring ; Real-time data
collection for vehicular Cyber-
Physical System/Digital Twin

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Smart Manufacturing
*Industry 4.0
Network slicing optimization for
smart factory (efficient operations
and reduced service creation time
for manufacturing equipments);
Optimization of production
processes; Automatic recognition
of defect or error or anomaly in the
manufacturing system; Market
demand forecasting for on demand
manufacturing; Predictive
maintenance of manufacturing
equipments; Reinforcement
learning based prescriptive
analytics for production control;
Real-time adaptive control of
additive manufacturing processes;
Optimal energy consumption
management; Autonomous control
of assembly robots
Transparent and sustainable
manufacturing supply chain
management; Distributed &
collaborative smart
manufacturing system; Secure
data sharing/networking
mechanism for manufacturing
system
Real-time monitoring of defect
or error or health status in the
manufacturing system; Real-
time inventory tracking; Real-
time data collection for
manufacturing Cyber-Physical
System/Digital Twin

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