Swift Student Challenge 2026

Distinguished Winner

Swift Student Challenge 2026

Distinguished Winner

Swift Student Challenge 2026

Distinguished Winner

Asuo

Navigating Floods. Saving Lives.

Project Overview

What is Asuo? Asuo is an offline flood safety navigation app that delivers real-time flood warnings and guides people to safety. Built for Accra, Ghana, and designed to scale to the 1.6 billion people living in flood-prone communities worldwide.

User problem: Flooding in cities like Accra causes lives to be lost because people have no reliable way to navigate danger zones or find safety quickly, especially when connectivity is unavailable.

My role: Product and interaction design, research, concept, prototyping.

What I designed: The navigation system, alert dashboard, flood map interface, offline functionality, and SOS emergency feature.

Outcome or validation: Prototype built and refined through user feedback and research insights.

My role: Product and interaction design, research, concept, prototyping.

What I designed: The navigation system, alert dashboard, flood map interface, offline functionality, and SOS emergency feature.

Outcome or validation: Prototype built and refined through user feedback and research insights.

My role: Product and interaction design, research, concept, prototyping.

What I designed: The navigation system, alert dashboard, flood map interface, offline functionality, and SOS emergency feature.

Outcome or validation: Prototype built and refined through user feedback and research insights.

Why Asuo?

I grew up in Accra, where rainy seasons often turned streets into dangerous flood zones. On June 3, 2015, flooding triggered a gas station explosion near Circle and claimed 154 lives. That tragedy shaped Asuo.

Asuo, meaning “flowing water” in Akan/Twi, is an offline flood navigation app that uses preloaded flood data and weather forecasts to guide people to safer walking routes, nearby shelters, and emergency SOS support.

Available on TestFlight

Apple's beta testing platform, install and try the app.

Scan to try Asuo

Sketches and ideation

Designing for crisis means designing for someone who has no time to think. High contrast alerts, clear zone labels, and a map that speaks before you read it. Every decision was intentional.

Low Fidelity Wireframes

Before refining the visual design, I used lo fi wireframes to focus on structure and usability. This stage helped me test layout, navigation, and content priority, making sure the most important actions were easy to find and understand in a moment of crisis.

User Interaction Design

System Architecture

Building an offline flood navigation system means every decision has to work without internet. This is the architecture I designed to make that possible.

Flood Risk Scoring Formula

Score = (Rain x 0.4) + (Drainage x 0.3) + (Elevation x 0.2) + (River x 0.1)

Danger ≥ 3.5 · Caution ≥ 2.0 · Safe < 2.0

External Data Sources

Weather Prediction API

Ghana Meteorological Agency. Real-time rainfall data, flood warnings, and weather forecasts.

Water Level Sensors

IoT sensors on Odaw River and drainage outlets. Real-time water depth and flow rate per zone.

Historical Flood Records

Past flood events, affected areas, water levels, and damage data used to calibrate risk models.

Geographic Data

Topographic and elevation data. Terrain, drainage infrastructure, and land use for each zone.

OpenStreetMap

Map tiles at multiple zoom levels, road network geometry, and geographic features. Cached locally for offline use.

Shelter Database

Emergency shelters, hospitals, and safe locations. Name, GPS coordinates, capacity, and current status.

Zone Characteristics

Per-zone data: population, drainage score, elevation score, river proximity, and drainage infrastructure status.

View full architecture

Backend Server

Asuo Backend

Ingests data, calculates risk, builds grid, finds safe routes

Data Ingestion

Receives weather and sensor data. Normalizes into rain intensity levels and flood phases.

→

Flood Risk Engine

Runs weighted formula per zone. Outputs risk level and estimated water depth.

→

Grid Builder

Builds 40x30 pathfinding grid. Danger = impassable. Caution = high cost. Safe = low cost.

→

A* Pathfinding

Finds safest route avoiding danger zones. Returns waypoints and estimated travel time.

Push Notifications

Alerts on phase changes: approaching, active, receding, all clear

WebSocket

Real-time updates: zone risk changes, route reroutes, status messages

Status Generator

Produces human-readable messages from live sensor data

Communication Layer

Weather updatesZone risk levelsShelter availabilitySafe route dataReal-time alerts

Sent to the app when online, cached for offline use

iOS App (On Device)

Asuo iOS App Works Offline

Three-tab interface powered by SwiftUI and @Observable engine

Alert Dashboard

Phase banner (clear to safe)Rain intensity meterWeather status + countdownZone flood cardsStatus message cardSOS slide-to-call

Flood Map

Zoomable, pannable mapColor-coded flood zonesOdaw River overlayShelter + hospital markersWater depth badgesZone detail sheet

Safe Route

Destination selectionWalking / driving toggleRoute preview on mapTurn-by-turn navigationCamera follows userArrival confirmation

Local Cache

Map tiles, zone data, shelters, routes. Powers offline mode.

On-Device Engine

Navigation tracking, heading, position interpolation, shelter proximity.

GPS

Real-time user position via CoreLocation. Feeds navigation.

Accessibility

Haptics, speech synthesis, VoiceOver, reduce motion support.

Device Hardware Used

GPS Sensor

Haptic Engine

Speaker

Phone Dialer

Network

Collapse

Flood Risk Scoring Formula

Score = (Rain x 0.4) + (Drainage x 0.3) + (Elevation x 0.2) + (River x 0.1)

Danger ≥ 3.5 · Caution ≥ 2.0 · Safe < 2.0

External Data Sources

Weather Prediction API

Ghana Meteorological Agency. Real-time rainfall data, flood warnings, and weather forecasts.

Water Level Sensors

IoT sensors on Odaw River and drainage outlets. Real-time water depth and flow rate per zone.

Historical Flood Records

Past flood events, affected areas, water levels, and damage data used to calibrate risk models.

Geographic Data

Topographic and elevation data. Terrain, drainage infrastructure, and land use for each zone.

OpenStreetMap

Map tiles at multiple zoom levels, road network geometry, and geographic features. Cached locally for offline use.

Shelter Database

Emergency shelters, hospitals, and safe locations. Name, GPS coordinates, capacity, and current status.

Zone Characteristics

Per-zone data: population, drainage score, elevation score, river proximity, and drainage infrastructure status.

View full architecture

Backend Server

Asuo Backend

Ingests data, calculates risk, builds grid, finds safe routes

Data Ingestion

Receives weather and sensor data. Normalizes into rain intensity levels and flood phases.

→

Flood Risk Engine

Runs weighted formula per zone. Outputs risk level and estimated water depth.

→

Grid Builder

Builds 40x30 pathfinding grid. Danger = impassable. Caution = high cost. Safe = low cost.

→

A* Pathfinding

Finds safest route avoiding danger zones. Returns waypoints and estimated travel time.

Push Notifications

Alerts on phase changes: approaching, active, receding, all clear

WebSocket

Real-time updates: zone risk changes, route reroutes, status messages

Status Generator

Produces human-readable messages from live sensor data

Communication Layer

Weather updatesZone risk levelsShelter availabilitySafe route dataReal-time alerts

Sent to the app when online, cached for offline use

iOS App (On Device)

Asuo iOS App Works Offline

Three-tab interface powered by SwiftUI and @Observable engine

Alert Dashboard

Phase banner (clear to safe)Rain intensity meterWeather status + countdownZone flood cardsStatus message cardSOS slide-to-call

Flood Map

Zoomable, pannable mapColor-coded flood zonesOdaw River overlayShelter + hospital markersWater depth badgesZone detail sheet

Safe Route

Destination selectionWalking / driving toggleRoute preview on mapTurn-by-turn navigationCamera follows userArrival confirmation

Local Cache

Map tiles, zone data, shelters, routes. Powers offline mode.

On-Device Engine

Navigation tracking, heading, position interpolation, shelter proximity.

GPS

Real-time user position via CoreLocation. Feeds navigation.

Accessibility

Haptics, speech synthesis, VoiceOver, reduce motion support.

Device Hardware Used

GPS Sensor

Haptic Engine

Speaker

Phone Dialer

Network

Collapse

Flood Risk Scoring Formula

Score =
(Rain x 0.4)
+ (Drainage x 0.3)
+ (Elevation x 0.2)
+ (River x 0.1)

Danger ≥ 3.5 · Caution ≥ 2.0 · Safe < 2.0

External Data Sources

Weather Prediction API

Ghana Meteorological Agency. Real-time rainfall data, flood warnings, and weather forecasts.

Water Level Sensors

IoT sensors on Odaw River and drainage outlets. Real-time water depth and flow rate per zone.

Historical Flood Records

Past flood events, affected areas, water levels, and damage data used to calibrate risk models.

Geographic Data

Topographic and elevation data. Terrain, drainage infrastructure, and land use for each zone.

OpenStreetMap

Map tiles at multiple zoom levels, road network geometry, and geographic features. Cached locally for offline use.

Shelter Database

Emergency shelters, hospitals, and safe locations. Name, GPS coordinates, capacity, and current status.

Zone Characteristics

Per-zone data: population, drainage score, elevation score, river proximity, and drainage infrastructure status.

View full architecture

Backend Server

Asuo Backend

Ingests data, calculates risk, builds grid, finds safe routes

Data Ingestion

Receives weather and sensor data. Normalizes into rain intensity levels and flood phases.

Flood Risk Engine

Runs weighted formula per zone. Outputs risk level and estimated water depth.

Grid Builder

Builds 40x30 pathfinding grid. Danger = impassable. Caution = high cost. Safe = low cost.

A* Pathfinding

Finds safest route avoiding danger zones. Returns waypoints and estimated travel time.

Push Notifications

Alerts on phase changes: approaching, active, receding, all clear

WebSocket

Real-time updates: zone risk changes, route reroutes, status messages

Status Generator

Produces human-readable messages from live sensor data

Communication Layer

Weather updatesZone risk levelsShelter availabilitySafe route dataReal-time alerts

Sent to the app when online, cached for offline use

iOS App (On Device)

Asuo iOS App Works Offline

Three-tab interface powered by SwiftUI and @Observable engine

Alert Dashboard

Phase banner (clear to safe)Rain intensity meterWeather status + countdownZone flood cardsStatus message cardSOS slide-to-call

Flood Map

Zoomable, pannable mapColor-coded flood zonesOdaw River overlayShelter + hospital markersWater depth badgesZone detail sheet

Safe Route

Destination selectionWalking / driving toggleRoute preview on mapTurn-by-turn navigationCamera follows userArrival confirmation

Local Cache

Map tiles, zone data, shelters, routes. Powers offline mode.

On-Device Engine

Navigation tracking, heading, position interpolation, shelter proximity.

GPS

Real-time user position via CoreLocation. Feeds navigation.

Accessibility

Haptics, speech synthesis, VoiceOver, reduce motion support.

Device Hardware Used

GPS Sensor

Haptic Engine

Speaker

Phone Dialer

Network

Collapse

Next Steps

Conduct usability testing with real users in flood-prone communities in Accra to validate the experience
Integrate live weather and flood data to move the app from simulation to real-time prediction
Partner with local authorities in Ghana to expand flood zone data coverage and emergency response integration

Conduct usability testing with real users in flood-prone communities in Accra to validate the experience
Integrate live weather and flood data to move the app from simulation to real-time prediction
Partner with local authorities in Ghana to expand flood zone data coverage and emergency response integration

Conduct usability testing with real users in flood-prone communities in Accra to validate the experience
Integrate live weather and flood data to move the app from simulation to real-time prediction
Partner with local authorities in Ghana to expand flood zone data coverage and emergency response integration

Tools

Photoshop

Figma

Google Gemini

Claude Code

Xcode

SwiftUI

Illustrattor