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Redis 8 beyond caching to uniquely powerful traffic management system.


This content originally appeared on DEV Community and was authored by Seb

This is a submission for the Redis AI Challenge: Beyond the Cache.

What I Built

A real-time air traffic control simulator that can track aircraft positions (latitude, longitude, altitude). Detect potential collisions using geospatial calculations, and visualize aircraft movement on a live map. It also generates alerts when aircraft violate safety thresholds.

Demo

Here is the GitHub repo: https://github.com/SebastianKibiriti/redis-airtraffic-simulator-with-deepseek

How I Used Redis 8

The features of Redis 8 that were used are: GEOADD, for storing the positions of the aircraft + GEORADIUS, for querying other aircrafts nearby.

# Store aircraft positions
redis.geoadd(
    "aircraft:positions",
    {aircraft_id: (longitude, latitude)}
)

# Query nearby aircraft (1km radius)
conflicts = redis.georadius(
    "aircraft:positions",
    current_lng, current_lat, 1, "km"
)

Lua Scripting for collision detection.

-- conflict_check.lua
local nearby = redis.call('GEORADIUS', KEYS[1], ARGV[1], ARGV[2], 1, 'km')
-- Checks altitude differences using ZSCORE

Streams, for real-time alerts. little to no alerts will be missed with faster replication.

# Trigger alert
redis.xadd(
    "conflict_alerts", 
    {"trigger_id": "flight123", "conflicts": "flight456"}
)

# Frontend consumes via WebSocket
alerts = redis.xread({"conflict_alerts": "$"}, block=0)

Multithreaded I/O to optimize performance. This allows for more that 1000+ concurrent aircraft updates to be handled.

The combination of geospatial, streaming, and Lua scripting creates a unique traffic management system.

Architecture Diagram

diagram


This content originally appeared on DEV Community and was authored by Seb