GPS / Vehicle Tracking

Twings

Real-time Flutter Application

SPEED62km/h

Preview coming soon

Overview

Twings gives fleet operators a live map of their vehicles, with clustering to keep the view readable at scale, plus fuel and speed analytics for monitoring vehicle performance in real time.

The Challenge

Rendering many live-moving vehicles on a single map without the screen turning into an unreadable cluster of overlapping markers, while keeping speed and fuel data updating smoothly alongside the map.

My Role

I worked on the UI development of the application, focused on the Google Maps integration, vehicle clustering, live speed meter, and the analytics and localization layers around them.

Technical Approach

Integrated Google Maps with live position updates so vehicle markers move on the map as new GPS data arrives.
Implemented marker clustering so the map stays legible when many vehicles are visible in the same viewport.
Built a live speed meter UI driven by streaming GPS speed data for at-a-glance vehicle monitoring.
Added fuel reports and analytics charts summarizing vehicle activity over time.
Implemented localization so the interface supports multiple languages for different regional fleets.

Technical Challenges & Solutions

Plotting every vehicle individually became unreadable once fleet size grew and vehicles clustered geographically.

Solution — Applied marker clustering that groups nearby vehicles at lower zoom levels and expands into individual markers as the user zooms in.

Continuous GPS updates for many vehicles risked taxing the map renderer and causing UI jank.

Solution — Throttled marker position updates to the map layer and only re-rendered clusters affected by new data instead of the full marker set.

Technical Architecture

A Flutter UI layer over a Google Maps integration, with marker clustering that groups nearby vehicles at low zoom and expands into individual markers as the user zooms in. Live position and speed updates are throttled at the map layer so only clusters affected by new GPS data re-render, keeping the map responsive under continuous fleet-wide updates.

Outcome

Delivered a responsive real-time tracking interface capable of displaying and clustering multiple live vehicles on a map alongside fuel and speed analytics.