Ideathon 2026 โ€” Social Good + Climate

๐ŸŒ KomuniCare

AI-powered community climate resilience โ€” turning scattered reports into coordinated action for Uganda's most vulnerable neighbourhoods.

View on GitHub Devpost Submission

Coordination is the missing link

Kampala floods regularly. Neighbourhoods like Bwaise, Kinawataka, and Nakivubo are home to hundreds of thousands of people โ€” and some of the city's most economically vulnerable families. When heavy rain hits, homes flood within minutes.

The weather data to predict these events already exists. Government agencies exist. NGOs exist. The problem is that when a flood hits at 2am, nobody knows which household has an elderly person who cannot evacuate alone. Nobody coordinates the volunteers. Nobody decides what gets done first.

KomuniCare uses ASI-1 to solve the coordination problem โ€” turning scattered community reports into prioritised, actionable response plans in real time.

Three layers of community resilience

1

Report

Residents submit issues via mobile โ€” flooding, drought, disease โ€” using photos, voice or text in English or Luganda.

2

Analyse

ASI-1 classifies the issue, scores household vulnerability, and cross-references live weather data to predict escalation.

3

Coordinate

ASI-1 generates a prioritised action plan. Volunteers receive assignments, claim tasks, and track resolution in real time.

4

Track

A live neighbourhood dashboard shows every open issue, volunteer coverage, and resolution status across the community.

Three deep AI capabilities

KomuniCare doesn't just use ASI-1 as a chatbot โ€” it integrates three distinct AI capabilities into a single community workflow.

๐Ÿ‘๏ธ Vision analysis

Classifies issue type and severity from submitted photos โ€” flood depth, structural damage, waste type

๐Ÿ—ฃ๏ธ Multilingual NLP

Understands reports in Luganda and English natively, generates plain-language action plans back in the user's language

๐Ÿ“Š Pattern recognition

Spots emerging hotspots across reports before they become crises, scores household vulnerability from community data

Built for those left behind

4.5M
Kampala residents
200M+
East Africans at climate risk by 2050
60%
Ugandans on basic phones
2
Languages supported at launch

From report to action plan

User submits report (photo + Luganda voice note)
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ASI-1 Vision: classify issue type + severity score (1โ€“5)
โ†“
ASI-1 NLP: extract location, affected parties, urgency signals
โ†“
ASI-1 Patterns: cross-reference weather + historical reports
โ†“
ASI-1 Output: vulnerability score + prioritised action plan
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Volunteer receives plain-language tasks in Luganda or English