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AI for Good Innovate for Impact
Use Case 13: Analysing Impact of Regional Weather on PLC-based
Data Transmission in Malaysia, and Nigeria� Change 4.2-Climate
Organization: Wireless & Photonic Networks (WiPNet) Research Center, Universiti Putra
Malaysia (UPM)
Country: Malaysia and Nigeria
Contact Persons:
Muhammad Adamu, m.adamu.ce@ gmail .com
Prof. Dr. Ir. Aduwati Sali, aduwati@ upm .edu .my
1 Use Case Summary Table
Item Details
Category Climate Change/Natural Disaster
Problem Addressed The changing of climate threatens data communication by disrupting
weather patterns and shapes which make it becoming more adverse and
extreme thereby causing potential impact on the performance of data
transmission rate (Throughput).
Key Aspects of Solu- Investigating significant weather events that potentially influence Power
tion Line Communication(PLC)-based transmission systems regarding
Throughput (data rate).
Technology Utilising traditional Machine Learning(ML)approach of ‘Neural Network
Keywords Regularization(NNR)to analyse the potential impact of events on
PLC-based data transmission with respect to Throughput performance.
Data Availability Investigating industrial practices to assess compliance with relevant stan-
dards (International Telecommunication Union(ITU)-T G.996X, IEEE 1901).
Metadata Related projects will be used for comparison.
Model Training Power Line Communication (PLC), Throughput, Weather Events, Machine
Learning (ML), Neural Network Regression (NNR).
Pilot Deployment Public
Code Repositories Text (datasets, and scripts (Python, MATLAB))
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