Real time vechile tracking using django channels and react

I want to implement real time tracking for vehicles but I don't know most of my things are not working. I use the geolocation API to get current device location and send those locations(latitude, longitude) to backend every five seconds. Then using django channels and Daphne I implement routing APIs I will use in react with the websockets but things take a delay to respond. I was requesting for yhe way I can design the database efficiently and the way I can handle the websocket connections

I tried to create the real time tracking using leaflet maps so that I can see the image move smoothly on the map but it just jumps or let me say it doesn't work as expected

I apprehend the demanding situations you're facing with actual-time tracking. let's ruin down the issues and discover solutions:

efficient Database layout

  1. Database Schema: make sure your database schema is optimized for actual-time facts. Use indexing on often queried fields like range and longitude to speed up searches.
  2. Normalization: balance normalization with overall performance desires. Denormalize statistics if vital to lessen the quantity of joins and enhance query performance. three. facts Partitioning: Partition your statistics primarily based on time or geographical areas to control huge datasets efficiently.

managing WebSocket Connections

  1. Scalability: Use a scalable WebSocket server like Socket.IO with Node.js. It handles multiple connections efficaciously and gives fallback options for older browsers.
  2. Connection control: enforce connection pooling and reuse connections to limit overhead.
  3. error handling: make certain strong error managing to manage disconnections and reconnections gracefully.

Leaflet Maps real-Time tracking

  1. Leaflet Realtime Plugin: Use the Leaflet Realtime plugin to deal with real-time facts on maps. It helps GeoJSON and can paintings with push information from WebSockets.
  2. data Refresh charge: modify the statistics refresh fee to stability among real-time updates and performance. Too common updates can cause lag.
  3. Map Optimization: Optimize map rendering through proscribing the quantity of markers and the use of clustering strategies to manipulate large datasets.

could you like greater precise guidance on any of these factors?

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