Maritime Intelligence Platform

Crow's Nest

A global maritime tracking system processing real-time AIS data for transportation, security, and environmental monitoring.

Overview

While at Sparkgeo, I contributed to SecureWatch Maritime, now rebranded as Crow's Nest under Maxar. This innovative platform processes and visualizes global maritime data, supporting various industries including transportation, security, and environmental monitoring through real-time vessel tracking and analysis.

The Challenge

The primary challenge was developing a system capable of processing vast amounts of global Automatic Identification System (AIS) messages in near real-time. This required building a scalable infrastructure that could:

  • Handle millions of daily messages from vessels worldwide
  • Process raw data into actionable insights
  • Deliver information to end users with minimal latency
  • Scale efficiently with growing maritime traffic

Solution

I helped architect and implement a robust backend infrastructure leveraging cloud services and modern technologies.

Core Features

  • Real-time AIS message processing
  • Global vessel tracking and visualization
  • Scalable data pipeline architecture
  • Advanced maritime analytics
  • Comprehensive search capabilities

Tech Stack

  • Cloud Services: AWS Lambda, S3, Kinesis
  • Data Processing: Python, Docker
  • Search & Analytics: Elasticsearch (ELK Stack)
  • Data Pipeline: Logstash for data transformation
  • Infrastructure: Serverless architecture

Key Outcomes

  • Processing Efficiency: Successfully handled millions of daily AIS messages with minimal latency
  • Real-World Impact: Enabled detection of illegal activities including:
    • Illicit fishing operations
    • Human trafficking patterns
    • Maritime security threats
  • Scalable Architecture: Built to accommodate growing maritime traffic and data volumes
  • Actionable Intelligence: Transformed raw AIS data into valuable insights for stakeholders

Personal Contribution

As a backend developer, I focused on:

  • Designing and implementing serverless architecture using AWS Lambda
  • Developing Python scripts for geospatial data processing
  • Integrating Elasticsearch for powerful data querying and analytics
  • Implementing Docker-based microservices
  • Ensuring system scalability and reliability

Conclusion

Crow's Nest demonstrates the power of modern cloud architecture and data processing in addressing global maritime challenges. The project showcases expertise in handling large-scale geospatial data, cloud infrastructure, and real-time processing systems.

The platform continues to evolve under Maxar, providing critical maritime intelligence to organizations worldwide and contributing to safer, more transparent maritime operations.

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