Turning scattered community reports into coordinated, prioritised climate action — built for Uganda, powered by ASI-1.
Built for the Ideathon 2026 by Tech Z.
KomuniCare is a mobile app that works like an AI-powered community climate resilience assistant for Uganda's urban and peri-urban communities. Residents report local climate issues — flooding, drought, crop failure, disease outbreaks — and ASI-1 analyses patterns, scores household vulnerability, and coordinates volunteer response teams with prioritised action plans.
Climate change in Uganda is not a future threat — it is happening now. Neighbourhoods like Bwaise, Kinawataka, and Nakivubo in Kampala flood regularly. Droughts destroy harvests. Disease outbreaks follow heavy rains.
The problem is not a lack of data. The problem is coordination:
- Who knows which household has an elderly person who cannot evacuate?
- Who organises the volunteers?
- Who decides what gets done first?
Today, the answer is nobody. Response is reactive, fragmented, and slow.
| Existing Approach | Limitation |
|---|---|
| Government disaster response | Slow, centralised, reaches communities too late |
| NGO emergency relief | Reactive, not community-led |
| WhatsApp community groups | Unstructured, no prioritisation, no coordination |
| Early warning SMS systems | One-way alerts only, no response coordination |
KomuniCare operates in three layers:
Residents submit issues via mobile using photos, voice notes, or text in English or Luganda. No technical knowledge required.
Every report is processed by ASI-1 across three dimensions:
User submits report (photo + text/voice in Luganda)
↓
ASI-1 Vision: classify issue type + severity score
↓
ASI-1 NLP: extract location, affected parties, urgency signals
↓
ASI-1 Pattern Engine: cross-reference weather + historical reports
↓
ASI-1 generates: vulnerability score + prioritised action plan
↓
Action plan delivered to volunteer in plain Luganda or English
Volunteers receive prioritised task assignments, claim tasks, update status, and mark them complete. A live neighbourhood dashboard tracks resolution across the whole community.
KomuniCare integrates ASI-1 across three distinct capability areas:
const response = await fetch("https://api.asi1.ai/v1/messages", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
model: "asi1-mini",
max_tokens: 500,
messages: [{
role: "user",
content: [
{
type: "image",
source: { type: "base64", media_type: "image/jpeg", data: imageBase64 }
},
{
type: "text",
text: "Classify this community-reported climate issue. Return JSON with: issue_type, severity (1-5), affected_infrastructure, immediate_risks, recommended_actions."
}
]
}]
})
});const actionPlan = await fetch("https://api.asi1.ai/v1/messages", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
model: "asi1-mini",
max_tokens: 800,
messages: [{
role: "user",
content: `You are a community resilience coordinator for Kampala, Uganda.
Report received (may be in Luganda or English): "${reportText}"
Issue classification: ${issueType}, Severity: ${severity}/5
Affected households: ${affectedCount}
Weather forecast: ${weatherForecast}
Generate a prioritised action plan in ${userLanguage}. Include:
1. Immediate actions (next 2 hours)
2. Vulnerable households to prioritise
3. Resources needed
4. Volunteer assignments
Keep language simple and practical.`
}]
})
});const vulnerabilityScore = await fetch("https://api.asi1.ai/v1/messages", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
model: "asi1-mini",
max_tokens: 600,
messages: [{
role: "user",
content: `Analyse these community reports from the past 48 hours and identify:
1. Emerging hotspots not yet reported
2. Households with highest vulnerability score
3. Resource gaps in current volunteer coverage
4. Predicted escalation risk in next 6 hours
Reports: ${JSON.stringify(recentReports)}
Weather forecast: ${weatherData}
Historical flood data: ${historicalData}`
}]
})
});- React Native app scaffolding
- ASI-1 API integration (vision + NLP)
- Report submission flow (photo + text + voice)
- Firebase backend setup
- Luganda language support and prompt optimisation
- Vulnerability scoring engine
- Pattern recognition across reports
- Open-Meteo weather integration
- Volunteer task assignment system
- Real-time neighbourhood dashboard
- Offline-first caching for low-connectivity areas
- Push notifications
- Community onboarding in Bwaise, Kampala
- LC1 leader training
- Feedback collection and iteration
- Swahili and Acholi language support
- KCCA government integration
- Open API for NGO partners
- Rural drought monitoring expansion
┌─────────────────────────────────────────┐
│ React Native Mobile App │
│ (iOS + Android, English + Luganda UI) │
└──────────────┬──────────────────────────┘
│
┌───────▼────────┐
│ Node.js API │
│ (Firebase) │
└───────┬─────────┘
│
┌──────────┼──────────┐
│ │ │
▼ ▼ ▼
ASI-1 Open-Meteo Leaflet.js
Vision + Weather Community
NLP + API Risk Map
Patterns
| Layer | Technology |
|---|---|
| Mobile frontend | React Native |
| AI engine | ASI-1 API (vision, NLP, patterns) |
| Backend | Node.js + Firebase Firestore |
| Weather data | Open-Meteo API |
| Mapping | Leaflet.js |
| Offline support | AsyncStorage + sync queue |
| Languages | English, Luganda (Swahili planned) |
| Feature | ASI-1 Role |
|---|---|
| Photo-based issue reporting | Vision classification + severity scoring |
| Luganda language support | Multilingual NLP understanding + generation |
| Vulnerability scoring | Pattern analysis across household + weather data |
| Action plan generation | Plain-language coordination instructions |
| Hotspot prediction | Cross-report pattern recognition |
| Volunteer matching | Priority-based task assignment |
Primary users:
- Urban and peri-urban residents of Kampala (4.5M people)
- Community volunteers and LC1 leaders
- Local NGO coordinators
Secondary users:
- KCCA disaster response teams
- Ministry of Disaster Preparedness
- East African NGOs (expansion)
Market size: 45M people in Uganda; 200M+ in East Africa face climate-related displacement risk by 2050.
- Faster emergency response for vulnerable households
- Community-led coordination reducing dependence on slow government systems
- Inclusive design — works in Luganda, works on low-end Android phones
- Reduced flood damage through faster response
- Lower cost than government emergency systems
- Volunteer coordination reduces duplication of effort
- Better data on climate impact patterns to inform adaptation planning
- Integration with nature-based solutions (e.g. wetland restoration alerts)
| Challenge | Mitigation | ASI-1 Role |
|---|---|---|
| Luganda NLP accuracy | Iterative prompt engineering + community testing | Core NLP engine |
| Low connectivity during crises | Offline-first caching, sync on reconnect | N/A |
| Privacy of vulnerable households | No PII stored; ASI-1 infers from patterns only | Pattern analysis without raw data |
| Community trust | Built around existing LC1 + church structures | N/A |
| Volunteer burnout | ASI-1 optimises task distribution to spread load | Task assignment engine |
- Predictive alerts before issues are even reported
- Integration with satellite imagery for large-scale damage assessment
- Carbon credit tracking for nature-based solutions implemented by communities
- Pan-East Africa deployment (Kenya, Tanzania, Rwanda)
Raymond Magezi Ssebyala Full-stack developer, Kampala, Uganda GitHub: @Ray56monds
- ASI-1 API Documentation
- Open-Meteo Weather API
- Uganda Red Cross Climate Resilience Programme
- KCCA Flood Risk Assessment 2023
- Kampala Climate Action Plan 2020-2030
- README with all 13 sections complete
- GitHub repository set up
- Problem statement clearly defined
- ASI-1 integration plan with API code examples
- Implementation roadmap with 5 phases and milestones
- Technical architecture diagram
- Target users and market size defined
- Impact assessment (social, economic, environmental)
- Challenges and mitigation strategies
- Future scope outlined
- Team information included
- Demo mockups / wireframes (in progress)