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Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
Volume-3 | Issue-3

Deniable Authentication Encryption for Privacy Protection using Blockchain
Volume-3 | Issue-3

Blockchain-Enabled Federated Learning on Kubernetes for Air Quality Prediction Applications
Volume-3 | Issue-3

Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
Volume-3 | Issue-4

Hybrid Parallel Image Processing Algorithm for Binary Images with Image Thinning Technique
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Smart Medical Nursing Care Unit based on Internet of Things for Emergency Healthcare
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QoS-aware Virtual Machine (VM) for Optimal Resource Utilization and Energy Conservation
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Probabilistic Neural Network based Managing Algorithm for Building Automation System
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Fusion based Feature Extraction Analysis of ECG Signal Interpretation - A Systematic Approach
Volume-3 | Issue-1

Multi-scale CNN Approach for Accurate Detection of Underwater Static Fish Image
Volume-3 | Issue-3

Real Time Anomaly Detection Techniques Using PySpark Frame Work
Volume-2 | Issue-1

Deniable Authentication Encryption for Privacy Protection using Blockchain
Volume-3 | Issue-3

Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
Volume-3 | Issue-4

Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
Volume-3 | Issue-3

Audio Tagging Using CNN Based Audio Neural Networks for Massive Data Processing
Volume-3 | Issue-4

Frontiers of AI beyond 2030: Novel Perspectives
Volume-4 | Issue-4

Smart Medical Nursing Care Unit based on Internet of Things for Emergency Healthcare
Volume-3 | Issue-4

Early Stage Detection of Crack in Glasses by Hybrid CNN Transformation Approach
Volume-3 | Issue-4

ARTIFICIAL INTELLIGENCE APPLICATION IN SMART WAREHOUSING ENVIRONMENT FOR AUTOMATED LOGISTICS
Volume-1 | Issue-2

Deep Convolution Neural Network Model for Credit-Card Fraud Detection and Alert
Volume-3 | Issue-2

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Volume - 3 | Issue - 3 | september 2021

Blockchain-Enabled Federated Learning on Kubernetes for Air Quality Prediction Applications
Pages: 196-217
Published
30 August, 2021
Abstract

The biggest realization of the Machine Learning (ML) in societal applications, including air quality prediction, has been the inclusion of novel learning techniques with the focus on solving privacy and scalability issues which capture the inventiveness of tens of thousands of data scientists. Transferring learning models across multi-regions or locations has been a considerable challenge as sufficient technologies were not adopted in the recent past. This paper proposes a Blockchain- enabled Federated Learning Air Quality Prediction (BFL-AQP) framework on Kubernetes cluster which transfers the learning model parameters of ML algorithms across distributed cluster nodes and predicts the air quality parameters of different locations. Experiments were carried out to explore the frame- work and transfer learning models of air quality prediction parameters. Besides, the performance aspects of increasing the Kubernetes cluster nodes of blockchains in the federated learning environment were studied; the time taken to establish seven blockchain organizations on top of the Kubernetes cluster while investigating into the federated learning algorithms namely Federated Random Forests (FRF) and Federated Linear Regression (FLR) for air quality predictions, were revealed in the paper.

Keywords

Air Quality Blockchain Federated Learning Kubernetes Smart cities

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