AI Data Development & Modeling
End-to-end AI pipeline: data integration from Elasticsearch, PostgreSQL migration to Azure, TensorFlow model for proactive device error detection.
A comprehensive AI and data engineering project spanning the full pipeline from raw data to deployed model. Data was integrated and cleansed from multiple heterogeneous sources including Elasticsearch, device log files, device registration data, and CSV exports. Data was migrated from PostgreSQL to Azure Databricks and structured ETL pipelines were set up in Azure Data Warehouse. A TensorFlow model was developed and trained for device analysis — detecting hardware errors proactively before failure. The system applied data governance policies to ensure reliability and consistency across sources. The full pipeline and model were containerized and deployed using Docker and Kubernetes on Azure Databricks, with continuous monitoring and iterative performance optimization.
Android IoT Gateway
Analysis, specification, design, and implementation of IoT-based applications with Azure data migration.
Vehicle Production & Testing App
Complex cross-platform mobile app for testing and maintaining newly produced vehicles on the factory floor.
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