Building Real-Time Location Apps with Flutter and Supabase: A Practical Methodology

Modern mobile apps increasingly rely on real-time data, location awareness, and secure backend logic. In this tutorial-driven methodology, a full Uber-style ride-hailing experience is built using Flutter for the frontend and Supabase for the backend. While the example focuses on an Uber clone, the underlying approach is broadly applicable to many location-based, real-time applications.

This article breaks down the core methodology and explains why it works so well for building scalable, production-ready apps.

1. Start with a Clear App State Model

The foundation of the app is a finite state machine that defines the user journey. Instead of letting UI logic sprawl, the app progresses through clearly defined states such as:

  • Choosing a destination

  • Confirming an estimated fare

  • Waiting for a driver

  • Riding to the destination

  • Completing the ride

This approach keeps the UI predictable and makes it easier to layer in real-time updates later. Any app with a multi-step flow benefits from this pattern.

2. Use Flutter for Cross-Platform, Map-Driven UI

Flutter provides a single codebase for iOS and Android while still delivering smooth, native-feeling animations. In this methodology:

  • Google Maps is embedded directly into the Flutter UI.

  • User location is accessed via device permissions.

  • Custom markers and polylines visualize destinations, routes, and moving vehicles.

Because Flutter widgets are declarative, UI changes naturally reflect changes in app state, reducing complex conditional logic.

3. Keep API Keys Secure with Supabase Edge Functions

One of the most important architectural decisions is not calling third-party APIs directly from the client.

Instead:

  • Sensitive calls (like Google Routes API requests) are made from Supabase Edge Functions.

  • API keys live in environment variables, never in the Flutter app.

  • The Flutter app calls the Edge Function, which proxies the request securely.

This pattern prevents key leakage, reduces abuse risk, and centralizes business logic.

4. Use Postgres + Realtime for Live App Updates

Supabase’s Postgres database is paired with Realtime subscriptions, enabling instant updates across devices:

  • Driver location updates stream live to the rider’s app.

  • Ride status changes propagate automatically.

  • No manual polling or custom WebSocket servers are required.

Database triggers and functions handle transitions like “driver assigned” or “ride started,” keeping backend logic consistent and auditable.

5. Simulate External Actors with Scripts

Since the tutorial focuses on the rider-facing app, driver behavior is simulated using scripts:

  • A script updates driver locations over time.

  • These updates flow through the database and realtime layer.

  • The app reacts exactly as it would with a real driver.

This technique is extremely useful for testing real-time systems without needing multiple live clients.

6. Gradually Layer Features Instead of Building Everything at Once

The methodology intentionally builds the app in layers:

  1. Show the map

  2. Get user location

  3. Select a destination

  4. Draw a route

  5. Estimate duration and fare

  6. Add realtime driver matching

Each step produces a working app, reducing debugging complexity and making it easier to validate assumptions early.

7. Why This Methodology Works

This approach succeeds because it:

  • Separates UI, business logic, and infrastructure cleanly

  • Uses managed backend services instead of custom servers

  • Treats real-time data as a first-class feature

  • Scales naturally from prototype to production

The result is not just a demo app, but a reusable blueprint for real-world systems.

If you abstract the methodology shown in the video (Flutter + Supabase + real-time data + maps/edge functions + state-driven UI), you can reuse it to build a whole family of location-aware, real-time, multi-actor apps.

Below is a structured breakdown of what kinds of apps naturally fall out of this approach, and why they work so well with the same architecture.

App Ideas

1. Logistics & Delivery Apps

Examples

  • Food delivery

  • Courier services

  • Pharmacy delivery

  • Warehouse-to-store logistics

Why it fits

  • Pickup → dropoff flow maps exactly to Uber’s ride lifecycle

  • Drivers are just mobile agents with GPS

  • Orders are rows in a database with state transitions

What changes

  • Pricing logic

  • Order metadata

  • Driver constraints (vehicle type, capacity)

2. On-Demand Services Marketplaces

Examples

  • Plumbers, electricians, cleaners

  • Home repair services

  • Mobile car washing

Why it fits

  • Customers request a service

  • Nearby providers receive and accept jobs

  • Real-time tracking + status updates

Extra features

  • Time windows instead of routes

  • Skill matching

  • Reviews & ratings tables

3. Fleet Tracking & Asset Monitoring

Examples

  • Company vehicle tracking

  • Construction equipment monitoring

  • Rental scooters or bikes

Why it fits

  • Same GPS streaming

  • Same map visualization

  • Same realtime subscriptions

Key difference

  • No “request” flow—just continuous telemetry

  • Heavier focus on dashboards and analytics

4. Emergency & Dispatch Systems

Examples

  • Private ambulance dispatch

  • Security patrol routing

  • Campus safety response

Why it fits

  • Fast state transitions

  • Priority-based routing

  • Multi-agent coordination

Enhancements

  • Priority queues

  • Geo-fencing

  • SLA timers

5. Social & Collaborative Location Apps

Examples

  • Friend live-location sharing

  • Event coordination apps

  • Group travel planners

Why it fits

  • Realtime presence

  • Shared map state

  • Lightweight auth (anonymous or magic links)

Variations

  • Ephemeral sessions

  • Shared destinations

  • Group roles (host vs guest)

6. Marketplace Matching Platforms (Non-Map)

Even without maps, the state machine + realtime DB pattern still applies.

Examples

  • Freelance job matching

  • Tutor ↔ student sessions

  • Mentor matching platforms

Mapping conceptually

  • Location → availability

  • Route → session lifecycle

  • Driver → service provider

7. Gaming & Simulation Apps

Examples

  • Multiplayer map-based games

  • Strategy games with moving units

  • Real-time simulations

Why it works

  • Supabase realtime = game state sync

  • Flutter = fast UI iteration

  • Edge Functions = authoritative logic

8. Smart City & IoT Dashboards

Examples

  • Traffic monitoring

  • Parking availability

  • Public transport tracking

Why it fits

  • Sensors → database

  • Database → realtime UI

  • Maps as the primary interface

9. Appointment & Scheduling Platforms

Examples

  • Doctor home visits

  • Mobile beauty services

  • Field inspections

Reuse

  • Time-based state instead of distance

  • Matching logic still identical

  • Realtime updates still critical

10. Internal Enterprise Tools

Examples

  • Sales rep tracking

  • Field technician dispatch

  • On-site audit tools

Why companies love this stack

  • Fast to build

  • No custom backend infra

  • Easy role-based access control

Build an Uber Clone with Flutter + Supabase (Step-by-Step Companion Guide)

This is a “follow-along” checklist you can keep next to the video so you always know what to do next, plus terminal commands and copy/paste prompts you can use with ChatGPT/Claude to speed up coding.

0) Prereqs (do this once)

Install tooling

  • Flutter SDK + your IDE (VS Code / Android Studio)

  • Android Studio + an Android emulator (or a physical device)

  • Xcode (macOS) if you’ll run on iOS

  • Supabase account

  • Google Maps Platform account (billing enabled)

Create API keys

In Google Cloud Console:

  • Enable: Maps SDK (Android/iOS) + Routes API (and any others used in the video)

  • Create an API key:

    • Restrict it by package/bundle id as you get further along (recommended)

1) Create the Flutter project (00:00 →)

Terminal

flutter create uber_clone
cd uber_clone
flutter run

Prompt (optional)

“Act as a Flutter lead. Suggest a clean folder structure for an Uber-like app using state management + repository pattern + service layer. Keep it beginner-friendly.”

2) Add dependencies (00:42)

The video adds packages for Maps, location, state management, networking, and Supabase.

Terminal (one way to do it)

flutter pub add supabase_flutter
flutter pub add google_maps_flutter
flutter pub add geolocator
flutter pub add permission_handler
flutter pub add flutter_polyline_points
flutter pub add http

If the video uses different packages (e.g., Riverpod/BLoC, freezed, etc.), follow the video’s exact list.

Prompt

“Based on these dependencies: (paste your pubspec.yaml), explain what each one does and where it should be used in the app.”

3) Configure Google Maps on Android + iOS (02:30)

Android (typical)

  1. Add your Maps key in android/app/src/main/AndroidManifest.xml:

    <meta-data
  android:name="com.google.android.geo.API_KEY"
  android:value="YOUR_GOOGLE_MAPS_KEY"/>

  2. Ensure your minSdkVersion and Gradle setup match the plugin docs.

iOS (typical)

  1. Add key to ios/Runner/AppDelegate.swift (or Info.plist approach depending on setup)

  2. Run:

    cd ios && pod install && cd ..

Prompt

“I’m setting up google_maps_flutter. Here are my AndroidManifest + AppDelegate files. Tell me exactly what to add/verify and common mistakes.”

4) Routes API overview (05:37)

Goal: Draw a route from origin → destination.

You’ll typically:

  • Send origin + destination to a backend function

  • Backend calls Google Routes API

  • Backend returns route polyline + distance + duration

  • Flutter decodes polyline and draws it on the map

Prompt

“Explain the minimal request/response structure for Google Routes API for driving directions, and what fields I should return to Flutter (polyline, distance, duration).”

5) Create a Supabase Edge Function to call Routes API (06:20)

Install Supabase CLI (if needed)

supabase --version

If not installed, install via Supabase docs method for your OS.

Initialize + link your project

supabase init
supabase login
supabase link --project-ref YOUR_PROJECT_REF

Create the function

supabase functions new routes

Common structure (pseudo)

  • supabase/functions/routes/index.ts

  • Read request JSON: { origin, destination }

  • Call Google Routes API with your server-side key

  • Return cleaned JSON to the client

Local serve + test (optional)

supabase functions serve --no-verify-jwt

Deploy

supabase functions deploy routes

Set secrets (Google API key)

supabase secrets set GOOGLE_MAPS_API_KEY="YOUR_KEY"

Prompt

“Write a Supabase Edge Function (Deno) named routes that:

  1. accepts origin/destination lat/lng

  2. calls Google Routes API

  3. returns encoded polyline + distance meters + duration seconds
    Include CORS headers and good error handling.”

6) Deploy & test the Edge Function (14:17)

Test via curl (example)

curl -i -X POST "https://YOUR_PROJECT_REF.functions.supabase.co/routes" \
  -H "Content-Type: application/json" \
  -d '{
    "origin": {"lat": 37.773972, "lng": -122.431297},
    "destination": {"lat": 37.784056, "lng": -122.407499}
  }'

Prompt

“Given this Edge Function response JSON (paste it), show me the Dart model + parsing code to extract polyline/distance/duration.”

7) Define app states (17:08)

Typical state machine for this app:

  1. Idle / Locating user

  2. Choosing destination

  3. Confirming fare

  4. Finding driver

  5. Driver assigned / en route

  6. Ride in progress

  7. Ride complete / reset

Prompt

“Design a simple state machine enum for these ride states and show how to transition between them in Flutter with clean UI separation.”

8) Request location permission (18:42)

Flutter: check permission + get current position

Use geolocator + permission_handler (depending on the video).

Prompt

“Write a robust location permission flow in Flutter (Android+iOS) with:

  • first run request

  • graceful fallback if denied

  • user messaging + settings deep link”

9) Implement “choose destination” state (27:11)

You’ll typically:

  • Show the map centered on user

  • Let user pan/zoom

  • Use a “pin” in the center or tap-to-place marker

  • Reverse-geocode address (if used in the video)

  • Save the chosen destination lat/lng

Prompt

“Give me a Flutter GoogleMap screen where:

  • user location is shown

  • a center pin indicates the chosen destination

  • when user taps ‘Confirm’, I store camera target lat/lng as destination”

10) Drop a pin marker for destination (39:07)

  • Create destination marker

  • Update marker when destination changes

Prompt

“Show how to manage Google Map markers in Flutter cleanly (immutable marker sets, updates without glitches).”

11) Draw the route polyline (42:11)

Flow:

  1. Call Edge Function with origin/destination

  2. Receive encoded polyline

  3. Decode to List<LatLng>

  4. Set polylines on the map

Prompt

“Given an encoded polyline string, write Dart code to decode it into List<LatLng> and render it as a Polyline on google_maps_flutter.”

12) Bottom sheet to confirm fare (48:11)

  • Show distance/time/fare estimate

  • CTA: “Confirm ride” / “Request”

Prompt

“Draft a clean bottom sheet UI for fare confirmation:

  • distance, duration, price breakdown

  • primary CTA

  • handle loading state while fare is calculating”

13) Supabase DB: tables, functions, triggers (57:42)

Typical entities:

  • rides (status, origin, destination, fare, rider_id, driver_id)

  • drivers (current_location, availability)

  • ride_events (optional audit log)

SQL (example skeleton — align to the video)

-- rides table (simplified)
create table if not exists rides (
  id uuid primary key default gen_random_uuid(),
  rider_id uuid,
  driver_id uuid,
  status text not null,
  origin_lat double precision,
  origin_lng double precision,
  dest_lat double precision,
  dest_lng double precision,
  fare_cents integer,
  created_at timestamptz default now()
);

Prompt

“Based on an Uber-like flow, propose a minimal Supabase schema (rides/drivers) + RLS policies for:

  • anonymous riders can create a ride

  • only assigned driver can update ride status/location

  • rider can read their ride”

14) Implement “find a driver” (1:06:00)

Common pattern:

  • Rider creates ride row in Supabase

  • Server function matches a driver

  • App subscribes to real-time updates on the ride row

  • When driver is assigned, UI transitions

Prompt

“Design a ‘find driver’ algorithm using Supabase:

  • pick nearest available driver (simple)

  • lock driver to avoid double assignment

  • update ride status atomically
    Show SQL or RPC strategy.”

15) Add anonymous sign-in (1:26:18)

Flutter (typical with supabase_flutter)

  • Initialize Supabase

  • Call anonymous sign-in

  • Store session

Prompt

“Show the Flutter code using supabase_flutter to:

  • initialize Supabase in main()

  • sign in anonymously at app start if no session

  • handle session persistence + sign-out”

16) Move the car icon & rotate by heading (1:27:40)

  • Driver location updates (real-time)

  • Marker moves smoothly

  • Marker rotation uses bearing between last point → next point

Prompt

“Write Dart code to compute bearing between two LatLng points and rotate a map marker accordingly. Also show how to animate marker movement smoothly.”

17) Show car info in bottom sheet (1:33:47)

  • Driver name, vehicle, plate, ETA, status

Prompt

“Create a bottom sheet UI component for driver info:

  • avatar, name, rating

  • car model + plate

  • ETA + status chips”

18) Update app status from ride listener (1:36:30)

  • Subscribe to ride row changes

  • On status change, transition app state

Prompt

“Implement a Supabase realtime listener in Flutter that watches a single rides row and updates local app state safely (cancel subscription on dispose, handle reconnect).”

19) Run through the flow manually (1:42:46)

Checklist:

  • location permission works

  • destination set

  • route drawn

  • fare shown

  • ride created in DB

  • ride updates reflected in UI

20) Simulate a driver with a script (1:45:23)

This is usually a small script that:

  • picks a ride

  • periodically updates driver location

  • updates ride status as it progresses

Example idea (pseudo)

  • Node/Python script:

    • fetch active ride

    • update drivers.current_location

    • set rides.status as it “moves”

Prompt

“Write a simple driver simulator script (Node or Python) that:

  • authenticates to Supabase with a service role key locally

  • selects the latest ride in requested status

  • updates driver location every 2 seconds along a polyline

  • updates ride status: assigned → en_route → arrived → in_progress → complete”

Quick Troubleshooting

  • Map is blank → API key missing/restricted wrong, billing not enabled, wrong manifest/appdelegate setup

  • Polyline not drawing → decoding bug or empty route response

  • Edge Function failing → missing CORS headers, wrong env secret, Routes API not enabled

  • Realtime not firing → table replication disabled, filters wrong, RLS blocking selects

If you paste your pubspec.yaml and your Edge Function code, I can:

  1. rewrite them to match the tutorial exactly, and

  2. fill in the precise commands/config for Android + iOS.

Do you want this formatted as a blog-style tutorial, or kept as a “checklist companion” like above?

Final Thoughts

While the tutorial walks through an Uber-style experience, the real value lies in the architecture: Flutter for rapid UI development, Supabase for secure backend logic, Edge Functions for API safety, and realtime databases for live interactions.

Once you understand this methodology, you can apply it to far more than ride-hailing apps.

Vide Coding, SupabaseFrancesca Tabor