Backend2020

IoT Data Processing Pipeline

Engineered a real-time IoT data pipeline handling 100K+ sensor readings per second with stream processing and machine learning integration.

The Challenge

Process massive streaming data from thousands of IoT sensors in real-time with anomaly detection and predictive analytics.

The Solution

Built Kafka-based streaming architecture with Spark for distributed processing. Integrated ML models for anomaly detection and predictive maintenance. Implemented data retention and analysis pipelines.

Results & Impact

Process 100K+ events per second

Detect anomalies with 98% accuracy

Reduce equipment downtime by 40%

Enable predictive maintenance decisions

Technologies Used

Apache Kafka
Apache Spark
Python
PostgreSQL
AWS Kinesis
TensorFlow

Project Info

Category

Backend

Year

2020

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