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Real-Time Recording and Storage of International Space Station Location

This workflow is designed to obtain real-time latitude, longitude, and timestamp data from the International Space Station and automatically store it in a Google BigQuery database. By using scheduled triggers and API calls, it eliminates the tediousness of manual queries and data entry, ensuring the timeliness and completeness of the data. It is suitable for fields such as aerospace research, educational platforms, and data analysis, facilitating real-time monitoring, analysis, and visualization of the space station's location.

Workflow Diagram
Real-Time Recording and Storage of International Space Station Location Workflow diagram

Workflow Name

Real-Time Recording and Storage of International Space Station Location

Key Features and Highlights

This workflow is triggered at scheduled intervals to automatically call the International Space Station (ISS) location API, retrieving real-time latitude, longitude, and timestamp data of the ISS. The structured location information is securely stored in Google BigQuery, enabling large-scale data analysis and subsequent processing.

Core Problems Addressed

Enables real-time, high-frequency acquisition of the ISS’s current location data with automated storage, eliminating the need for manual querying and data entry. This ensures data timeliness and integrity.

Application Scenarios

  • Monitoring and analysis of ISS trajectories by aerospace research institutions
  • Displaying the ISS real-time location on educational and popular science platforms
  • Trend prediction and visualization based on historical trajectory data by data analysis teams
  • Providing ISS location alerts and positioning services for media outlets or applications

Main Workflow Steps

  1. The workflow is triggered every minute by a Cron node.
  2. An HTTP Request node calls the public API at “https://api.wheretheiss.at” to obtain the ISS’s current real-time latitude, longitude, and timestamp.
  3. A Set node filters and formats the retrieved data fields, extracting key location information.
  4. A Google BigQuery node writes the structured data into a specified BigQuery dataset and table for persistent storage.

Involved Systems or Services

  • Cron: Scheduled trigger for workflow execution
  • HTTP Request: Calls the ISS public API to fetch real-time data
  • Set: Filters and formats data fields
  • Google BigQuery: Cloud-based big data storage service used for storing and managing ISS location information

Target Users and Value

Suitable for aerospace researchers, data analysts, educational institutions, popular science platform developers, and any users requiring real-time access to and analysis of ISS location data. This workflow automates data collection and storage, improving data acquisition efficiency and supporting research and innovation in related fields.