Welcome

◐ HOW IT WORKS

Location → Vulnerability → Priority → Action

AQUORA is a software-only AI/GIS decision-support platform. It combines hazard conditions, household vulnerability and real-time needs to rank affected families — so responders reach the right people, with the right resources, first.

1. 01

   Register

   Anonymous ID (H-01…) + GPS location. No names on the map.

2. 02

   Profile

   Elderly, infants, mobility, medical needs recorded once.

3. 03

   Report

   Live needs: evacuation, medicine, water, food, shelter, hygiene, SOS.

4. 04

   Fuse

   Household overlaid on Red / Orange / Yellow / Green hazard layer.

5. 05

   Prioritize

   P1 Immediate / P2 Urgent / P3 Standard — every rank carries its WHY.

6. 06

   Decide

   Human Priority Map + P1-first rescue list + shelter match + resource gap.

7. 07

   Act & update

   Dispatch → Dispatched → Resolved. List recalculates; P3→P2→P1 escalates.

▲ HAZARD & RED ZONES

Where is the water?

Inputs: flood extent, rainfall, water level, terrain/DEM, roads & bridges, official alerts. Output is a living zone map that gates everything downstream.

Classification logic — how a zone is decided

• RED — water above danger level and still rising, or an official evacuation order. Overrides everything else.
• ORANGE — water above warning level, or heavy inflow coming from upstream. Prepare to move.
• YELLOW — heavy rainfall forecast or upstream rise while local levels are still normal. Watch.
• GREEN — every reading below threshold. Staging ground, not a target.

Zones recompute as readings change — a YELLOW can turn RED overnight, and every household under it is automatically re-ranked.

● VULNERABILITY & PRIORITY

Who goes first, and why

The core of AQUORA. Rule-based and explainable — no black-box AI deciding lives.

How each part is scored (0–10)

† Weights and bands are illustrative — set with domain experts before any deployment. As stock runs out or water rises, scores climb on their own: P3 becomes P2 becomes P1.

■ SAFE SITE SELECTION

Where do people go?

• Outside the Red zone, roads intact (a cut road = instant reject)
• Within 5 km / 1 hr walk, with a motorable + alternate route
• Accessible for elderly & wheelchairs, with WASH + medical nearby

Output: candidate Site A / B / C. DS3 finds them — it does not promise they can hold everyone. That's DS4's job.

▣ CAPACITY + OFFLINE

Can the site actually hold them?

Everything is counted in persons-equivalent. The weakest resource decides.

Status: GREEN <70% · YELLOW 70–90 · ORANGE 90–100 · RED full. Example from the demo: 800 need relocation, Site B holds 750 — flagged honestly as “gap 50, split across a second site.”

Duration math — how long stock lasts

Ranking shelters, step by step

1. Gate check. Inside Red, or its road is cut? Rejected — no math needed.
2. Compute Effective for every surviving site (weakest resource decides).
3. Sort highest first. Biggest Effective capacity tops the list.
4. Fill top-down. Whatever doesn't fit is the gap — printed plainly with a split suggestion, never hidden.

Offline-first, briefly

QUEUE local → pending → syncing → synced. Only sub-1KB anonymized packets travel (road / shelter / evac / hazard updates) — store → carry → forward → auto-sync with dedup when signal returns. Names and medical details never leave the device.

◇ TECH STACK

What we use

Data (as we integrate officially): flood/GIS layers, weather, DEM, roads, shelters, inventory, alerts.

⬔ PRIVACY & PRINCIPLES

Lines we don't cross

• Anonymous H-IDs only. Minimal data, consent-first, role-based access, no public PII.
• Explainable ranks with printed reasons. No black-box life/death AI.
• Software only — no sensors, drones, or hardware claims.
• Complements official NDRF/SDRF systems. Never claims to replace them.

○ OUR SIH TEAM

Six people, one institute

ASHOKA INSTITUTE OF TECHNOLOGY AND MANAGEMENT

Anjali Maurya

LEADER

CSE · DATA SCIENCE — 2ND YEAR

Archana Pandey

CSE · DATA SCIENCE — 2ND YEAR

Vishal Chaubey

CSE · AIML — 2ND YEAR

Arya Tripathi

MBA — 2ND YEAR

AJ

Archit Jaiswal

CSE · DATA SCIENCE — 2ND YEAR

06 — ?

DECIDING SOON

Photos: drop files at public/team/anjali.jpg, archana.jpg, vishal.jpg — cards swap in automatically.