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★ 40.0 / 100 • Rank #55 Originality: Common Concept Judge: Discard AI Unnecessary Easy Independent Community Builds 30-Hour Build Plan

GoBagReady: Family go-bag planner from public hazard maps

#Offline & Edge #Disaster Preparedness #Open Data #Checklist AI
Executive Elevator Pitch

"GoBagList turns your purok's public flood/landslide/quake zone into a one-page family go-bag and papers checklist in Tagalog — what to pack, where copies go, who carries whom. No account, no location upload; type your purok once and everything stays local."

Suggested Stack: Astro static site + on-device checklist logic, public HazardHunter/NOAH zones, printable one-pager.
Strict Judge Evaluation — 0–100 (Innovation 25 / Fit 25 / AI 20 / Feasibility 15 / Impact 15) Methodology & rankings →
Innovation & Creativity
20
Problem–Solution Fit
50
AI Application & Value
15
Feasibility & Potential
85
Impact & Scalability
45

Weighted total ★ 40.0/100 — ranked #55 of 56. Concept-stage assessment only: no prototype has been built or tested. Scores are comparative, not official PLDT marks.

Problem Statement

Every typhoon post-mortem says “prepare a go-bag,” but families don’t know what applies to them: flood-prone needs documents in dry bags; landslide-prone needs night-evacuation plan; elderly-heavy households need meds list. Generic infographics get ignored because they aren’t specific to the household.

Proposed Solution

Pick province → city → purok type + household profile (seniors, infants, meds, pets). GoBagList cross-reads public hazard susceptibility and outputs a prioritized one-page list: bag contents, document copies, meeting point, and “who carries whom.” Printable and screenshot-friendly; works offline after first load. Nothing uploaded.

Target Market

  • Primary users: Families in hazard-prone puroks, boarding-house tenants, new parents.
  • Deployers: Barangay DRRM volunteers during family preparedness drives, schools, parishes.

How AI Is Used

  • Checklist composer: Small LM assembles household-specific lists from hazard zone + profile without over-packing.
  • Plain-language rewriting: Turns technical zone labels into “Bahaabutin tuwing malakas na ulan” guidance.
  • Why AI: Static lists overwhelm; composed lists match the household.

Independent Deployment Angle

  • Static site anyone can mirror; no backend, no telco, no venue, no headset.
  • Barangay prints 100 copies from a PDF; no load needed to use.
  • Youth volunteers localize for their purok in an afternoon.

Demo Scenario (3 minutes for judges)

  1. Select a riverside purok + household: lola with maintenance meds + 1 infant.
  2. One-page list appears: meds for 7 days, dry-bag docs, infant needs, meeting point.
  3. Switch to upland landslide profile; list changes to night-evacuation emphasis.
  4. Print the one-pager; show offline reload with WiFi off.
  5. Close: “Isang pahina bawat pamilya.”

30-Hour Build Plan

Hours Task Role
0–3 Gather public zone guides, define household profiles All
3–9 Checklist composer prompts + zone mapping AI lead
3–10 Static site + offline cache + print CSS Frontend
10–20 Purok picker, Tagalog rewrite pass Backend + Frontend
20–26 Test with 5 household types, readability check All
26–30 Pitch, disclosure PM / Pitch

Suggested stack: Astro static site + on-device checklist logic, printable one-pager. Public data / APIs: HazardHunterPH/GeoRiskPH guides, Project NOAH materials, NDRRMC preparedness lists.

Risks & Privacy Notes

  • Safety over-precision: Zone guidance is advisory with source links; always defers to barangay evacuation orders.
  • Privacy: No location or household data collected or sent anywhere. Demo households are fictional.
  • IP: Only public guidance paraphrased with citations; no copied infographics.

AI Use Disclosure (draft)

Uses a small LM to compose and rewrite checklists from public hazard guidance. AI coding assistants helped with static-site code. All lists were reviewed against NDRRMC guidance by the team.

Rubric Scoring

Criterion Weight Score (1–5) Why
Innovation & creativity 25% 3 Checklists exist; household-specific composition is the edge
Problem–solution fit 25% 5 Fits low-attention preparedness gap
AI application & value 20% 3 Light but well-applied
Feasibility 15% 5 Static + LM very doable
Impact & scalability 15% 4 Printable scale via barangays
Weighted total 4.00

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