National Seismic Data Pipeline
Developed an end-to-end ETL pipeline automating data acquisition from over 300 remote seismic sensors across Australia, ensuring real-time updates for the national Earthquakes Portal used by emergency services.
Client
Geoscience Australia
Key Results
Sensors Integrated
Data Processing
Manual Work Reduced
Emergency Response
The Challenge
Manual data collection from hundreds of distributed seismic sensors was slow, error-prone, and created critical delays in earthquake monitoring that could impact emergency response times.
Key challenges included:
- Manual collection from 300+ remote sensors
- Inconsistent data formats (miniseed files)
- Delays impacting emergency response capabilities
- No fault tolerance for network interruptions
- Limited scalability for growing sensor network
Why It Matters
Australia experiences thousands of earthquakes annually. Rapid detection and notification is critical for emergency services, infrastructure operators, and public safety. Every minute of delay can impact response effectiveness.
Emergency Response Impact
The Earthquakes Portal serves as a primary source of seismic data for emergency services across Australia, making real-time data availability essential for disaster response.
Our Solution
We built a fully automated, fault-tolerant pipeline that collects high-sample miniseed files from remote sensors, processes them in near real-time, and publishes charts and alerts on the customer-facing portal.
Collection
Automated data acquisition from 300+ sensors
Ingestion
AWS Lambda functions process incoming data
Processing
Parse and validate miniseed files
Storage
PostgreSQL with optimized indexing
Publish
Real-time charts and alerts
Automated Data Collection
Built scheduled collectors that automatically retrieve miniseed files from distributed sensors without manual intervention.
AWS Lambda Processing
Serverless functions process incoming seismic data, parsing and validating files before storage.
Fault-Tolerant Architecture
Implemented automatic retry mechanisms and dead-letter queues to handle network interruptions and sensor failures.
S3 Data Lake
Raw miniseed files stored in S3 with lifecycle policies for cost-effective long-term retention.
Real-time Processing
Near real-time processing pipeline ensures minimal delay between sensor reading and portal update.
Alert Generation
Automated alerting system notifies relevant parties when significant seismic events are detected.
Technology Stack
Project Impact
Operational Transformation
- Eliminated 95% of manual data collection work
- Reduced data latency from hours to minutes
- 24/7 automated monitoring and collection
- Scalable architecture for growing sensor network
Emergency Response
- Near real-time seismic event detection
- Automated alerts for emergency services
- Reliable data for disaster response planning
- Critical infrastructure for national safety