Satellite Telemetry Streaming and Computation Project

Overview

This project streams real-time satellite telemetry data using the N2YO API and performs distributed computations using Apache Kafka and Apache Spark. The main objectives are:

• Compare Stream Vs. Batch processing via satellite position/path visualization.
• Calculate the satellite closest to a fixed observer location (e.g., Bangalore).
• Determine coverage overlap between multiple satellites.
• Compute motion vectors for each satellite based on positional data over time.

Features

• Live satellite position data ingestion via the N2YO API
• Data publishing to Kafka topics
• Real-time computation using Spark Structured Streaming
• Derived insights based on spatial and temporal analysis
• Real-time satellite tracking
• Satellite Path visualization

Technologies Used

• Python 3
• Apache Kafka
• Apache Zookeeper
• Apache Spark
• REST APIs (N2YO)
• VS Code (Development environment)

Computations

1. Closest Satellite to Observer

   • Compares real-time coordinates of satellites with a fixed observer (Delhi)
   • Uses haversine formula to determine distance

2. Coverage Overlap

   • Checks for overlapping ground footprints between satellite coverages
   • Requires assumptions about coverage radius

3. Motion Vector Calculation

   • Computes velocity vectors using consecutive latitude/longitude positions and timestamps