Real-Time Industrial IoT Pipeline & Predictive Maintenance (JESA) (2025)

Freelancer

Informations

Publiée le: 07-03-2026

• Python
• ReactJS / React Native
• Intelligence Artificielle

Description:
During my internship at JESA (Jacobs Engineering S.A), I engineered an end-to-end real-time monitoring pipeline for hydraulic systems. This project focuses on high-frequency sensor data processing and anomaly detection to prevent industrial failures.

Technical Stack & Highlights:

Data Streaming: Architected a real-time data flow using Apache Kafka to handle multi-sensor streams with low latency.

Anomaly Detection (AI): Implemented a Deep Learning (LSTM) model to analyze time-series data and detect technical anomalies before they occur.

Full-Stack Visualization: Developed an interactive dashboard using React and Power BI to visualize live sensor metrics and system health alerts.

Data Management: Optimized a PostgreSQL database for efficient storage and retrieval of industrial sensor history.

Vues: 2