AICONN stands for "AI Connectivity" and it means connecting AI
AICONN
Our vision is contributed by creating a large AI ecosystem like a forest in the African grasslands.
Resource Management in the Energy Industry
• Water pipe leak detection algorithm through AI model
• Minimize damage through proactive measures by predicting leaks in advance
• Efficiently measure leak location, leak status, and leak volume
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1
Design
AI-based intelligent leak integration
Solution platform design,
AI-based pipe acceleration signal abnormal detection development,
Leak location prediction development -
2
Development
AI-based leak data prediction platform,
AI-based leak location calculation,
Calculation of leaks and leaks -
3
Validation
AI-based leak platform and model field validation and optimization
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4
Commercialization
Commercialization of AI-based leak detection platform and algorithm
Energy Management – Motor Predictive Diagnosis
• Build AI motor diagnosis predictive maintenance system
• Real-time diagnosis by predicting motor failure with an AI model through vibration sensor data
Data Exploration
Sensor data collection
vibration frequency
Data Cleansing
Vibration & current data
Check data distribution
Raw data selection
Normal/abnormal frequency confirmation
Labeling data
Feature Extraction
Feature engineering for time-based and spectrum-based
AI Model & Prediction
Selection of algorithms such as XGBoost, LigthGBM, SVM, Neural Networks, etc.
AI learning and fault diagnosis
AI Deployment
Building motor diagnosis dashboard
Advancement of AI-based Sensor Measurement Performance
• Storage management of collected fine dust data
• Advancement of performance of fine dust measurement devices based on artificial intelligence analysis
• Algorithm application through interworking and analysis of fine dust data
• Flexible prediction system operation for each location/device
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1
Data Collecting
Fine-dust sensor data collection
Collected fine dust data storage management -
2
AI Algorithms
Advanced measurement device performance by using AI filter algorithm for fine dust sensor with smoothing filtration
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3
Measure Fine-dust
Application of AI algorithm to fine dust measuring device Distribution of improved fine dust measurement values
Platform
• Define the problem to solve sensor-based data
• Collect and analyze data required for AIoT model training
• Build API for each AI model according to machine learning and deep learning algorithms
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Sensor & Module Design
• High sensitivity sensor selection
• LTE-based interface
• Low power module designIoT Sensor
Sensor - Applicable to various materials
Connectivity smartphone - Field exploration
LTE & IoT network to LoRa support available -
AIoT Management System
• Artificial intelligence IoT platform
• Build AI predictive models
• Crack, fault diagnosis, location predictionAIoTCloud
Crack, fault diagnosis and location calculation
Strengthen security by using domestic servers
AI analysis-based crack, failure prediction -
SaaS Platform Integration
• Integrated SaaS platform management system
• Report of analysis and diagnosis result
• Diagnostic visualization dashboardDiagnosis APP
Provide maintenance report of fault diagnosis
Web-based service linked with GIS
Provides status through accumulated analysis data - 원격상시
- Web
AICONN AIoT Cloud Orchestration
• Provides orchestration platform that builds data pipelines for ML & DL models for each application
• Implement of kubwa MLOps in on-premise and cloud environments based on Docker and Kubernetes container
• Achieve the goals of open, convergence, and flow with kubwa AIoT

AICONN Edu: B2B
AICONN Edu provides educational course to satisfy the needs for DT (Digital Transformation) in various fields and the use of professional AI.
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Manufacturing AI Practitioner Training
Empower practitioners in data analytics and AI capabilities
1. Understanding sensor and facility data
2. Machine learning, deep Learning
3. Anomaly detection, time-series analysis
4. XAI explainable/interpretable AI -
AIoT Practitioner Training
Empower AIoT capabilities from data collection to analytics
1. Understanding IoT sensor data
2. AIoT data analysis methodology
3. Machine learning, deep learning
4. AIoT cloud, edge deployment -
DT Competency Training
Empower DT capabilities from data collection to analytics
1. DT and AI introduction methodology
2. Understanding data types and AI applications
3. AI problem definition and insight
4. Solving data-driven problems