🧩 IDRM: Integrated Disaster Response Management Platform - MVP Product Requirements Document

A comprehensive MVP Product Requirements Document.

Posted Dec 22, 2024 Updated Dec 22, 2025

33 min read

IDRM: MVP PRD - Product Requirements Document

Executive Summary

The Integrated Disaster Response Management Platform (IDRM) MVP is a unified, map-driven, privacy-first digital platform designed to enable timely, coordinated, transparent disaster response in India. This document outlines the technical architecture, technology stack, and implementation roadmap for the Minimum Viable Product deployment on a standalone Ubuntu machine.

1. Product Overview

1.1 Product Vision

IDRM serves as a national-scale digital nervous system for disaster response, connecting information flow, logistics, people, and accountability mechanisms into one coordinated platform. The system operates analogously to the human body with a neural network for information and a circulatory system for resources.

1.2 Core Problem Statement

Disaster response in India suffers from:

Fragmented information across multiple stakeholders
Delayed coordination between agencies
Limited transparency in resource allocation
Absence of unified digital coordination systems
Privacy concerns for vulnerable populations
Difficulty tracking service delivery and outcomes

1.3 MVP Scope

The MVP focuses on establishing core platform capabilities:

Geographic information system with real-time mapping
Service request and provider coordination
Role-based access control with privacy protection
Basic communication and notification system
Financial transparency for donations and allocations
Audit trails and reporting

2. Technology Stack

2.1 System Architecture

graph TB
    A[Web Clients] --> B[NGINX Reverse Proxy]
    B --> C[Node.js API Gateway]
    C --> D[Python Microservices]
    C --> E[Redis Cache]
    D --> F[PostgreSQL + PostGIS]
    C --> G[GeoServer]
    G --> F
    H[Admin Dashboard] --> B

2.2 Core Technologies

Backend Technologies

Node.js Stack (API Gateway & Real-time Services)

Node.js 20 LTS - JavaScript runtime for asynchronous operations
Express.js 4.x - Web application framework for REST APIs
Socket.io 4.x - Real-time bidirectional communication
Passport.js - Authentication middleware supporting JWT
Helmet.js - Security middleware for HTTP headers
Express-validator - Input validation and sanitization
Winston - Logging framework
Morgan - HTTP request logger
Joi - Schema validation

Python Stack (Data Processing & Analytics)

Python 3.11 - Core language for data operations
FastAPI 0.104+ - Modern, fast web framework for building APIs
SQLAlchemy 2.0 - ORM for database operations
GeoAlchemy2 - Spatial extension for SQLAlchemy
Pandas - Data manipulation and analysis
Celery 5.x - Distributed task queue for async processing
Pydantic - Data validation using Python type annotations

Database & Caching

PostgreSQL 16 + PostGIS 3.4

Primary relational database
PostGIS extension for geospatial data types and operations
Supports point, line, polygon geometries with spatial indexing
R-tree indexes for efficient spatial queries

Redis 7.2

Session management and JWT token blacklisting
Real-time data caching
Message queue for pub/sub patterns
Rate limiting implementation

Geospatial Services

GeoServer 2.24

OGC-compliant map server (WMS, WFS, WCS)
Connects to PostGIS for spatial data
Supports SLD styling for map visualization
REST API for programmatic control

Leaflet 1.9

Frontend mapping library
Lightweight and mobile-friendly
Plugin ecosystem for extended functionality
WMS/WFS integration with GeoServer

Web Server & Proxy

NGINX 1.24

Reverse proxy for Node.js and Python services
Web Application Firewall (WAF) capabilities
SSL/TLS termination
Static file serving and caching
Load balancing across service instances

Development & Deployment

Docker 24.x & Docker Compose

Container orchestration
Service isolation
Development-production parity

Git

Version control system

2.3 Technology Selection Rationale

Node.js for API Gateway: Event-driven architecture handles high-concurrency connections efficiently, making it ideal for real-time disaster response coordination with thousands of simultaneous users.

Python for Data Processing: Superior libraries for geospatial analysis, data science capabilities for analytics, and extensive scientific computing ecosystem for future ML integration.

PostgreSQL + PostGIS: Industry standard for geospatial databases with ACID compliance, robust spatial functions (over 1000 geospatial operations), and superior performance for complex spatial queries compared to MongoDB.

Redis: In-memory storage provides sub-millisecond latency for session management, enabling stateless JWT authentication with blacklist capability and efficient caching layer.

GeoServer: Open-source, OGC-compliant standard for serving geospatial data, extensive format support, and seamless integration with PostGIS.

NGINX: High-performance reverse proxy with minimal resource footprint, excellent for handling concurrent connections and providing security features.

3. System Architecture

3.1 Layered Architecture

┌─────────────────────────────────────────┐
│     Presentation Layer (Web Client)     │
│    Leaflet Maps | React Components      │
└─────────────────────────────────────────┘
                  ↓ HTTPS
┌─────────────────────────────────────────┐
│    NGINX (Reverse Proxy, WAF, Cache)    │
└─────────────────────────────────────────┘
                  ↓
┌─────────────────────────────────────────┐
│       API Gateway (Node.js/Express)     │
│   Authentication | Routing | WebSocket  │
└─────────────────────────────────────────┘
        ↓                    ↓
┌───────────────┐    ┌──────────────────┐
│  Redis Cache  │    │  GeoServer WMS   │
└───────────────┘    └──────────────────┘
        ↓                    ↓
┌─────────────────────────────────────────┐
│   Business Logic Layer (Python/FastAPI) │
│  Service Management | Analytics | ReVV  │
└─────────────────────────────────────────┘
                  ↓
┌─────────────────────────────────────────┐
│     Data Layer (PostgreSQL + PostGIS)   │
│   User Data | Service Data | GeoData    │
└─────────────────────────────────────────┘

3.2 Microservices Architecture

The MVP implements a microservices pattern with the following services:

Authentication Service (Node.js)

JWT token generation and validation
OAuth 2.0 integration capability
Session management with Redis
Token blacklisting on logout

Service Management Service (Python/FastAPI)

CRUD operations for service requests
Provider matching algorithms
Status tracking and updates
Task assignment logic

Geospatial Service (Python/FastAPI)

Spatial queries and analysis
Location-based service matching
Distance calculations
Clustering algorithms

Communication Service (Node.js/Socket.io)

Real-time notifications
WebSocket connections
Broadcast mechanisms
Message queuing

Analytics Service (Python/FastAPI)

Data aggregation
Report generation
Dashboard metrics
Audit log processing

Financial Service (Python/FastAPI)

Donation tracking
Allocation management
Transparent accounting
Fund flow auditing

4. Core Features

4.1 Identity & Access Management

User Authentication

JWT-based stateless authentication
Access token (15 minutes expiry) and refresh token (7 days expiry)
Token blacklisting on logout using Redis
Password hashing with bcrypt (cost factor: 12)

Role-Based Access Control (RBAC)

User roles with hierarchical permissions:

System Administrator - Full system access, user management
Disaster Management Authority - Oversee operations, approve requests
Organization Admin - Manage organization users and services
Event Manager - On-ground coordination, task assignment
Service Provider - Respond to requests, update status
Volunteer - Field support, data collection
Citizen - Submit requests, receive information
Auditor - Read-only access, generate reports

RBAC Implementation using Casbin

Policy-based access control
Flexible permission models (ACL, RBAC, ABAC)
Database-backed policy storage in PostgreSQL

4.2 Privacy Preservation

Anonymization Levels

Level 1: Public (location precision to district)
Level 2: Protected (location precision to block)
Level 3: Private (exact coordinates, restricted access)

Privacy Controls

User-controlled visibility settings
Automatic PII masking in logs
Differential privacy for aggregated analytics
GDPR-compliant data handling

4.3 GeoMap-Based Services

Map Features

Service Request Markers:

Color-coded by service type (medical, food, shelter, rescue)
Size indicates urgency (critical, high, medium, low)
Clustering for dense areas (using Leaflet.markercluster)

Service Provider Markers:

Organization type icons
Availability status indicators
Service radius visualization

Map Interactions:

Click marker for details
Filter by service type, status, date range
Search by location/address
Draw areas of interest
Measure distances

Spatial Operations

PostGIS Capabilities:

  
-- Find services within 5km radius
SELECT * FROM service_requests 
WHERE ST_DWithin(
  location::geography,
  ST_MakePoint(longitude, latitude)::geography,
  5000
);

-- Cluster nearby requests
SELECT ST_ClusterKMeans(location, 10) OVER() as cluster_id,
       service_id, service_type, location
FROM service_requests;

-- Calculate service coverage area
SELECT service_provider_id,
       ST_ConvexHull(ST_Collect(location)) as coverage_area
FROM service_deliveries
GROUP BY service_provider_id;

GeoServer Integration

WMS layers for service visualization
WFS for editable features
SLD styling for thematic mapping
GetFeatureInfo for querying

4.4 Service Lifecycle Management

Service Request Workflow

stateDiagram-v2
    [*] --> Submitted
    Submitted --> UnderReview: Auto/Manual trigger
    UnderReview --> Approved: Verification passed
    UnderReview --> Rejected: Invalid/Duplicate
    Approved --> Assigned: Provider matched
    Assigned --> InProgress: Provider accepts
    InProgress --> Completed: Service delivered
    InProgress --> Cancelled: Unable to complete
    Completed --> Verified: Beneficiary confirms
    Rejected --> [*]
    Cancelled --> [*]
    Verified --> [*]

Service Request Schema

  
class ServiceRequest(BaseModel):
    service_id: UUID4
    requestor_id: UUID4
    service_type: ServiceType  # MEDICAL, FOOD, SHELTER, RESCUE, etc.
    priority: Priority  # CRITICAL, HIGH, MEDIUM, LOW
    location: Point  # PostGIS geometry
    address: str
    description: str
    privacy_level: PrivacyLevel
    status: ServiceStatus
    created_at: datetime
    updated_at: datetime
    assigned_to: Optional[UUID4]
    estimated_completion: Optional[datetime]
    metadata: dict  # Flexible JSON field

4.5 Review, Verification & Validation (ReVV)

Automated Validation

Duplicate detection using spatial clustering
Anomaly detection for fraudulent requests
Cross-reference with known disaster zones
Historical pattern analysis

Manual Verification

Authority review queue
Community-based validation
Photographic evidence requirements
Third-party verification integration

Audit Trail

Every action logged with timestamp and user
Immutable log storage
Change tracking for all entities
Searchable audit interface

4.6 Communication System

Real-time Notifications

WebSocket connections for instant updates
Service status changes
Assignment notifications
Alert broadcasts

Chatbot Integration (Future)

Natural language processing
Multi-language support (Hindi, English, regional languages)
WhatsApp Business API integration
SMS fallback for low connectivity

Notification Channels

In-app notifications
Email notifications
SMS (via third-party gateway)
Push notifications (mobile app future)

4.7 Financial Transparency

Donation Management

  
class Donation(BaseModel):
    donation_id: UUID4
    donor_id: Optional[UUID4]  # Anonymous allowed
    amount: Decimal
    currency: str = "INR"
    purpose: str  # General or specific cause
    disaster_event_id: Optional[UUID4]
    payment_method: PaymentMethod
    transaction_id: str
    status: DonationStatus
    created_at: datetime

Fund Allocation

Purpose-wise pooling
Transparent allocation records
Multi-level approval for disbursements
Automatic receipt generation

Financial Reporting

Real-time fund balance dashboards
Allocation vs utilization reports
Donor-specific reports
Audit-ready transaction logs

4.8 Analytics & Reporting

Dashboard Metrics

Total services requested/completed
Average response time by service type
Geographic distribution heat maps
Provider performance metrics
Financial flow visualization

Report Types

Daily operational reports
Event-specific summaries
Provider performance reports
Financial audit reports
Impact assessment reports

Data Export

CSV, JSON, PDF formats
Custom date ranges
Filtered by parameters
Scheduled automated reports

5. Database Schema

5.1 Core Tables

users

  
CREATE TABLE users (
    user_id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    email VARCHAR(255) UNIQUE NOT NULL,
    password_hash VARCHAR(255) NOT NULL,
    full_name VARCHAR(255),
    phone VARCHAR(20),
    role VARCHAR(50) NOT NULL,
    organization_id UUID REFERENCES organizations(organization_id),
    is_active BOOLEAN DEFAULT true,
    is_verified BOOLEAN DEFAULT false,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

CREATE INDEX idx_users_email ON users(email);
CREATE INDEX idx_users_role ON users(role);

organizations

  
CREATE TABLE organizations (
    organization_id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    name VARCHAR(255) NOT NULL,
    type VARCHAR(50) NOT NULL, -- NGO, GOVERNMENT, IO, PRIVATE
    registration_number VARCHAR(100),
    address TEXT,
    location GEOMETRY(Point, 4326),
    contact_email VARCHAR(255),
    contact_phone VARCHAR(20),
    is_verified BOOLEAN DEFAULT false,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

CREATE INDEX idx_organizations_location ON organizations USING GIST(location);

service_requests

  
CREATE TABLE service_requests (
    service_id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    requestor_id UUID REFERENCES users(user_id),
    service_type VARCHAR(50) NOT NULL,
    priority VARCHAR(20) NOT NULL,
    location GEOMETRY(Point, 4326) NOT NULL,
    address TEXT,
    description TEXT,
    privacy_level VARCHAR(20) DEFAULT 'PUBLIC',
    status VARCHAR(50) DEFAULT 'SUBMITTED',
    assigned_to UUID REFERENCES users(user_id),
    disaster_event_id UUID REFERENCES disaster_events(event_id),
    estimated_completion TIMESTAMP,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    metadata JSONB
);

CREATE INDEX idx_service_requests_location ON service_requests USING GIST(location);
CREATE INDEX idx_service_requests_status ON service_requests(status);
CREATE INDEX idx_service_requests_type ON service_requests(service_type);
CREATE INDEX idx_service_requests_priority ON service_requests(priority);
CREATE INDEX idx_service_requests_event ON service_requests(disaster_event_id);

disaster_events

  
CREATE TABLE disaster_events (
    event_id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    event_name VARCHAR(255) NOT NULL,
    event_type VARCHAR(50) NOT NULL, -- FLOOD, EARTHQUAKE, CYCLONE, etc.
    severity VARCHAR(20), -- LOW, MEDIUM, HIGH, CRITICAL
    affected_area GEOMETRY(Polygon, 4326),
    start_date TIMESTAMP NOT NULL,
    end_date TIMESTAMP,
    status VARCHAR(50) DEFAULT 'ACTIVE',
    description TEXT,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

CREATE INDEX idx_disaster_events_area ON disaster_events USING GIST(affected_area);
CREATE INDEX idx_disaster_events_type ON disaster_events(event_type);

service_providers

  
CREATE TABLE service_providers (
    provider_id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    user_id UUID REFERENCES users(user_id),
    organization_id UUID REFERENCES organizations(organization_id),
    service_types VARCHAR(50)[], -- Array of service types
    coverage_area GEOMETRY(Polygon, 4326),
    capacity INTEGER,
    current_load INTEGER DEFAULT 0,
    is_available BOOLEAN DEFAULT true,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

CREATE INDEX idx_service_providers_coverage ON service_providers USING GIST(coverage_area);
CREATE INDEX idx_service_providers_types ON service_providers USING GIN(service_types);

donations

  
CREATE TABLE donations (
    donation_id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    donor_id UUID REFERENCES users(user_id),
    amount DECIMAL(15,2) NOT NULL,
    currency VARCHAR(3) DEFAULT 'INR',
    purpose TEXT,
    disaster_event_id UUID REFERENCES disaster_events(event_id),
    payment_method VARCHAR(50),
    transaction_id VARCHAR(255) UNIQUE,
    status VARCHAR(50) DEFAULT 'PENDING',
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

CREATE INDEX idx_donations_event ON donations(disaster_event_id);
CREATE INDEX idx_donations_status ON donations(status);

audit_logs

  
CREATE TABLE audit_logs (
    log_id BIGSERIAL PRIMARY KEY,
    user_id UUID REFERENCES users(user_id),
    action VARCHAR(100) NOT NULL,
    entity_type VARCHAR(50),
    entity_id UUID,
    changes JSONB,
    ip_address INET,
    user_agent TEXT,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

CREATE INDEX idx_audit_logs_user ON audit_logs(user_id);
CREATE INDEX idx_audit_logs_entity ON audit_logs(entity_type, entity_id);
CREATE INDEX idx_audit_logs_created ON audit_logs(created_at);

6. API Design

6.1 RESTful API Structure

Base URL: https://api.idrm.gov.in/v1

Authentication Header: Authorization: Bearer <jwt_token>

6.2 API Endpoints

Authentication

POST   /auth/register          - Register new user
POST   /auth/login             - Login and get tokens
POST   /auth/refresh           - Refresh access token
POST   /auth/logout            - Logout and blacklist tokens
POST   /auth/verify-email      - Verify email address
POST   /auth/forgot-password   - Request password reset
POST   /auth/reset-password    - Reset password with token

Users

GET    /users/me               - Get current user profile
PUT    /users/me               - Update current user profile
GET    /users/:id              - Get user by ID (restricted)
GET    /users                  - List users (admin only)
POST   /users                  - Create user (admin only)
PUT    /users/:id              - Update user (admin only)
DELETE /users/:id              - Delete user (admin only)

Service Requests

POST   /services               - Create service request
GET    /services               - List service requests (filtered)
GET    /services/:id           - Get service request details
PUT    /services/:id           - Update service request
DELETE /services/:id           - Delete service request (restricted)
POST   /services/:id/assign    - Assign to provider
PUT    /services/:id/status    - Update status
GET    /services/nearby        - Find services near location
POST   /services/:id/verify    - Verify service completion

Organizations

POST   /organizations          - Register organization
GET    /organizations          - List organizations
GET    /organizations/:id      - Get organization details
PUT    /organizations/:id      - Update organization
POST   /organizations/:id/verify - Verify organization (admin)

Disaster Events

POST   /events                 - Create disaster event (admin)
GET    /events                 - List disaster events
GET    /events/:id             - Get event details
PUT    /events/:id             - Update event (admin)
GET    /events/:id/services    - Get services for event
GET    /events/:id/analytics   - Get event analytics

Donations

POST   /donations              - Create donation
GET    /donations              - List donations (filtered)
GET    /donations/:id          - Get donation details
GET    /donations/summary      - Get financial summary
POST   /donations/:id/allocate - Allocate funds (admin)

Analytics

GET    /analytics/dashboard    - Get dashboard metrics
GET    /analytics/services     - Service analytics
GET    /analytics/financial    - Financial analytics
GET    /analytics/geographic   - Geographic analytics
POST   /analytics/report       - Generate custom report

GeoSpatial

GET    /geo/services           - GeoJSON of service locations
GET    /geo/coverage           - Provider coverage areas
POST   /geo/search             - Spatial search
GET    /geo/cluster            - Clustered service points

6.3 Request/Response Examples

Create Service Request

Request:

  
POST /v1/services
Content-Type: application/json
Authorization: Bearer <token>

{
  "service_type": "MEDICAL",
  "priority": "HIGH",
  "location": {
    "type": "Point",
    "coordinates": [78.4867, 17.3850]
  },
  "address": "Charminar, Hyderabad, Telangana",
  "description": "Urgent medical attention needed for elderly person",
  "privacy_level": "PROTECTED",
  "disaster_event_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890"
}

Response:

  
{
  "status": "success",
  "data": {
    "service_id": "f9e8d7c6-b5a4-3210-fedc-ba9876543210",
    "status": "SUBMITTED",
    "created_at": "2024-12-22T10:30:00Z",
    "estimated_response_time": "30 minutes"
  }
}

Get Service Requests (with spatial filter)

Request:

GET /v1/services?lat=17.3850&lng=78.4867&radius=5000&status=APPROVED&service_type=MEDICAL
Authorization: Bearer <token>

Response:

  
{
  "status": "success",
  "data": {
    "services": [
      {
        "service_id": "f9e8d7c6-b5a4-3210-fedc-ba9876543210",
        "service_type": "MEDICAL",
        "priority": "HIGH",
        "status": "APPROVED",
        "distance_meters": 1250,
        "created_at": "2024-12-22T10:30:00Z"
      }
    ],
    "pagination": {
      "page": 1,
      "per_page": 20,
      "total": 45,
      "pages": 3
    }
  }
}

7. Security Implementation

7.1 Authentication Flow

sequenceDiagram
    participant C as Client
    participant N as NGINX
    participant A as Auth Service
    participant R as Redis
    participant D as Database

    C->>N: POST /auth/login
    N->>A: Forward request
    A->>D: Verify credentials
    D-->>A: User data
    A->>A: Generate JWT tokens
    A->>R: Store refresh token
    A-->>C: Access + Refresh tokens
    
    C->>N: GET /services (with token)
    N->>A: Verify token
    A->>R: Check blacklist
    R-->>A: Not blacklisted
    A-->>N: Token valid
    N->>C: Authorized access

7.2 Security Measures

JWT Token Security

Short-lived access tokens (15 minutes)
Longer refresh tokens (7 days)
Token rotation on refresh
Blacklisting on logout using Redis
Token includes user ID, role, and expiry

Password Security

Bcrypt hashing (cost factor 12)
Minimum 8 characters requirement
Password strength validation
Rate limiting on login attempts (5 attempts per 15 minutes)

Input Validation

Schema validation using Joi (Node.js) and Pydantic (Python)
SQL injection prevention via parameterized queries
XSS protection through output encoding
CSRF tokens for state-changing operations

Network Security

HTTPS enforced (TLS 1.3)
HSTS headers
Certificate pinning
Secure cookie flags (HttpOnly, Secure, SameSite)

Rate Limiting

API rate limits: 100 requests/minute per user
Login attempts: 5 per 15 minutes
Registration: 3 per hour per IP
Implemented via Redis counters

CORS Configuration

  
{
  origin: process.env.ALLOWED_ORIGINS.split(','),
  credentials: true,
  methods: ['GET', 'POST', 'PUT', 'DELETE'],
  allowedHeaders: ['Content-Type', 'Authorization']
}

8. Deployment Architecture

8.1 Server Specifications

Hardware Requirements

CPU: 8 cores (minimum)
RAM: 32 GB (minimum)
Storage: 500 GB SSD
Network: 1 Gbps connection

Operating System

Ubuntu 24.04 LTS (Noble Numbat)
Kernel 6.8+

8.2 Docker Compose Configuration

docker-compose.yml

  
version: '3.8'

services:
  # NGINX Reverse Proxy
  nginx:
    image: nginx:1.24-alpine
    container_name: idrm-nginx
    ports:
      - "80:80"
      - "443:443"
    volumes:
      - ./nginx/nginx.conf:/etc/nginx/nginx.conf:ro
      - ./nginx/ssl:/etc/nginx/ssl:ro
      - ./static:/usr/share/nginx/html:ro
    depends_on:
      - api-gateway
      - geoserver
    networks:
      - idrm-network
    restart: unless-stopped

  # PostgreSQL with PostGIS
  postgres:
    image: postgis/postgis:16-3.4
    container_name: idrm-postgres
    environment:
      POSTGRES_DB: idrm_db
      POSTGRES_USER: idrm_user
      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
      PGDATA: /var/lib/postgresql/data/pgdata
    volumes:
      - postgres-data:/var/lib/postgresql/data
      - ./init-scripts:/docker-entrypoint-initdb.d
    ports:
      - "5432:5432"
    networks:
      - idrm-network
    restart: unless-stopped
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U idrm_user -d idrm_db"]
      interval: 30s
      timeout: 10s
      retries: 5

  # Redis Cache
  redis:
    image: redis:7.2-alpine
    container_name: idrm-redis
    command: redis-server --requirepass ${REDIS_PASSWORD} --appendonly yes
    volumes:
      - redis-data:/data
    ports:
      - "6379:6379"
    networks:
      - idrm-network
    restart: unless-stopped
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 30s
      timeout: 10s
      retries: 5

  # Node.js API Gateway
  api-gateway:
    build:
      context: ./services/api-gateway
      dockerfile: Dockerfile
    container_name: idrm-api-gateway
    environment:
      NODE_ENV: production
      PORT: 3000
      DATABASE_URL: postgresql://idrm_user:${POSTGRES_PASSWORD}@postgres:5432/idrm_db
      REDIS_URL: redis://:${REDIS_PASSWORD}@redis:6379
      JWT_SECRET: ${JWT_SECRET}
      JWT_REFRESH_SECRET: ${JWT_REFRESH_SECRET}
    ports:
      - "3000:3000"
    depends_on:
      - postgres
      - redis
    networks:
      - idrm-network
    restart: unless-stopped
    volumes:
      - ./logs:/app/logs

  # Python Service Management
  service-manager:
    build:
      context: ./services/service-manager
      dockerfile: Dockerfile
    container_name: idrm-service-manager
    environment:
      DATABASE_URL: postgresql://idrm_user:${POSTGRES_PASSWORD}@postgres:5432/idrm_db
      REDIS_URL: redis://:${REDIS_PASSWORD}@redis:6379
    ports:
      - "8001:8000"
    depends_on:
      - postgres
      - redis
    networks:
      - idrm-network
    restart: unless-stopped

  # Python Analytics Service
  analytics:
    build:
      context: ./services/analytics
      dockerfile: Dockerfile
    container_name: idrm-analytics
    environment:
      DATABASE_URL: postgresql://idrm_user:${POSTGRES_PASSWORD}@postgres:5432/idrm_db
      REDIS_URL: redis://:${REDIS_PASSWORD}@redis:6379
    ports:
      - "8002:8000"
    depends_on:
      - postgres
      - redis
    networks:
      - idrm-network
    restart: unless-stopped

  # GeoServer
  geoserver:
    image: kartoza/geoserver:2.24.0
    container_name: idrm-geoserver
    environment:
      GEOSERVER_ADMIN_USER: ${GEOSERVER_USER}
      GEOSERVER_ADMIN_PASSWORD: ${GEOSERVER_PASSWORD}
      GEOSERVER_DATA_DIR: /opt/geoserver/data_dir
      POSTGRES_HOST: postgres
      POSTGRES_PORT: 5432
      POSTGRES_DB: idrm_db
      POSTGRES_USER: idrm_user
      POSTGRES_PASS: ${POSTGRES_PASSWORD}
    volumes:
      - geoserver-data:/opt/geoserver/data_dir
    ports:
      - "8080:8080"
    depends_on:
      - postgres
    networks:
      - idrm-network
    restart: unless-stopped

volumes:
  postgres-data:
  redis-data:
  geoserver-data:

networks:
  idrm-network:
    driver: bridge

8.3 NGINX Configuration

nginx.conf

  
user nginx;
worker_processes auto;
error_log /var/log/nginx/error.log warn;
pid /var/run/nginx.pid;

events {
    worker_connections 4096;
    use epoll;
}

http {
    include /etc/nginx/mime.types;
    default_type application/octet-stream;

    # Logging
    log_format main '$remote_addr - $remote_user [$time_local] "$request" '
                    '$status $body_bytes_sent "$http_referer" '
                    '"$http_user_agent" "$http_x_forwarded_for"';
    access_log /var/log/nginx/access.log main;

    # Performance
    sendfile on;
    tcp_nopush on;
    tcp_nodelay on;
    keepalive_timeout 65;
    types_hash_max_size 2048;
    client_max_body_size 20M;

    # Compression
    gzip on;
    gzip_vary on;
    gzip_proxied any;
    gzip_comp_level 6;
    gzip_types text/plain text/css text/xml text/javascript 
               application/json application/javascript application/xml+rss;

    # Security Headers
    add_header X-Frame-Options "SAMEORIGIN" always;
    add_header X-Content-Type-Options "nosniff" always;
    add_header X-XSS-Protection "1; mode=block" always;
    add_header Referrer-Policy "no-referrer-when-downgrade" always;

    # Rate Limiting
    limit_req_zone $binary_remote_addr zone=api_limit:10m rate=100r/m;
    limit_req_zone $binary_remote_addr zone=auth_limit:10m rate=5r/m;

    # Upstream services
    upstream api_gateway {
        least_conn;
        server api-gateway:3000;
    }

    upstream geoserver_backend {
        server geoserver:8080;
    }

    # HTTP to HTTPS redirect
    server {
        listen 80;
        server_name idrm.gov.in;
        return 301 https://$server_name$request_uri;
    }

    # HTTPS Server
    server {
        listen 443 ssl http2;
        server_name idrm.gov.in;

        # SSL Configuration
        ssl_certificate /etc/nginx/ssl/cert.pem;
        ssl_certificate_key /etc/nginx/ssl/key.pem;
        ssl_protocols TLSv1.2 TLSv1.3;
        ssl_ciphers HIGH:!aNULL:!MD5;
        ssl_prefer_server_ciphers on;

        # API Gateway
        location /api/ {
            limit_req zone=api_limit burst=20 nodelay;
            
            proxy_pass http://api_gateway;
            proxy_http_version 1.1;
            proxy_set_header Upgrade $http_upgrade;
            proxy_set_header Connection 'upgrade';
            proxy_set_header Host $host;
            proxy_set_header X-Real-IP $remote_addr;
            proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
            proxy_set_header X-Forwarded-Proto $scheme;
            proxy_cache_bypass $http_upgrade;
            
            # CORS
            add_header Access-Control-Allow-Origin $http_origin always;
            add_header Access-Control-Allow-Methods 'GET, POST, PUT, DELETE, OPTIONS' always;
            add_header Access-Control-Allow-Headers 'Content-Type, Authorization' always;
            add_header Access-Control-Allow-Credentials 'true' always;
            
            if ($request_method = 'OPTIONS') {
                return 204;
            }
        }

        # Authentication endpoints with stricter rate limiting
        location /api/auth/ {
            limit_req zone=auth_limit burst=5 nodelay;
            
            proxy_pass http://api_gateway;
            proxy_http_version 1.1;
            proxy_set_header Host $host;
            proxy_set_header X-Real-IP $remote_addr;
            proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
            proxy_set_header X-Forwarded-Proto $scheme;
        }

        # GeoServer WMS/WFS
        location /geoserver/ {
            proxy_pass http://geoserver_backend/geoserver/;
            proxy_set_header Host $host;
            proxy_set_header X-Real-IP $remote_addr;
            proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
            
            # Caching for WMS tiles
            proxy_cache_valid 200 1h;
            proxy_cache_bypass $http_pragma $http_authorization;
        }

        # Static files
        location /static/ {
            alias /usr/share/nginx/html/;
            expires 1y;
            add_header Cache-Control "public, immutable";
        }

        # Frontend application
        location / {
            root /usr/share/nginx/html;
            try_files $uri $uri/ /index.html;
        }
    }
}

9. Development Guidelines

9.1 Code Structure

Node.js API Gateway Structure

services/api-gateway/
├── src/
│   ├── config/
│   │   ├── database.js
│   │   ├── redis.js
│   │   └── passport.js
│   ├── middleware/
│   │   ├── auth.js
│   │   ├── rbac.js
│   │   ├── validate.js
│   │   └── errorHandler.js
│   ├── routes/
│   │   ├── auth.routes.js
│   │   ├── user.routes.js
│   │   ├── service.routes.js
│   │   └── index.js
│   ├── controllers/
│   │   ├── auth.controller.js
│   │   ├── user.controller.js
│   │   └── service.controller.js
│   ├── models/
│   │   ├── User.js
│   │   └── Session.js
│   ├── utils/
│   │   ├── logger.js
│   │   ├── jwt.js
│   │   └── validators.js
│   └── app.js
├── tests/
├── package.json
├── Dockerfile
└── .env.example

Python Service Structure

services/service-manager/
├── app/
│   ├── api/
│   │   ├── v1/
│   │   │   ├── endpoints/
│   │   │   │   ├── services.py
│   │   │   │   └── providers.py
│   │   │   └── api.py
│   │   └── dependencies.py
│   ├── core/
│   │   ├── config.py
│   │   ├── security.py
│   │   └── logging.py
│   ├── db/
│   │   ├── session.py
│   │   ├── base.py
│   │   └── init_db.py
│   ├── models/
│   │   ├── service.py
│   │   └── provider.py
│   ├── schemas/
│   │   ├── service.py
│   │   └── provider.py
│   ├── services/
│   │   ├── service_manager.py
│   │   └── geospatial.py
│   └── main.py
├── tests/
├── requirements.txt
├── Dockerfile
└── .env.example

9.2 Coding Standards

JavaScript/Node.js

Use ESLint with Airbnb style guide
Use async/await over callbacks
Implement error handling in all async functions
Use ES6+ features (arrow functions, destructuring, template literals)
Add JSDoc comments for functions

Python

Follow PEP 8 style guide
Use type hints for all function signatures
Implement docstrings (Google style)
Use Black for code formatting
Use pylint for linting

9.3 Testing Strategy

Unit Tests

Node.js: Jest framework
Python: pytest framework
Minimum 70% code coverage
Test all business logic functions
Mock external dependencies

Integration Tests

API endpoint testing
Database integration testing
Redis integration testing
End-to-end workflows

Load Testing

Apache JMeter or Locust
Test scenarios:
- 1000 concurrent users
- 10000 service requests per hour
- Geographic query performance

10. Monitoring & Observability

10.1 Logging

Winston Configuration (Node.js)

  
const winston = require('winston');

const logger = winston.createLogger({
  level: 'info',
  format: winston.format.combine(
    winston.format.timestamp(),
    winston.format.errors({ stack: true }),
    winston.format.json()
  ),
  defaultMeta: { service: 'api-gateway' },
  transports: [
    new winston.transports.File({ 
      filename: 'logs/error.log', 
      level: 'error' 
    }),
    new winston.transports.File({ 
      filename: 'logs/combined.log' 
    })
  ]
});

Python Logging Configuration

  
import logging
from logging.handlers import RotatingFileHandler

logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)

handler = RotatingFileHandler(
    'logs/service.log',
    maxBytes=10485760,  # 10MB
    backupCount=5
)

formatter = logging.Formatter(
    '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
handler.setFormatter(formatter)
logger.addHandler(handler)

10.2 Metrics Collection

Application Metrics

Request count by endpoint
Response time percentiles (p50, p95, p99)
Error rates
Active connections
Database query performance

System Metrics

CPU usage
Memory consumption
Disk I/O
Network throughput
Container resource utilization

Business Metrics

Service requests created per hour
Average resolution time
Provider response rate
User registrations
Donation amounts

10.3 Health Checks

API Health Endpoint

  
app.get('/health', async (req, res) => {
  const health = {
    status: 'UP',
    timestamp: new Date().toISOString(),
    services: {
      database: await checkDatabase(),
      redis: await checkRedis(),
      geoserver: await checkGeoServer()
    }
  };
  
  const statusCode = Object.values(health.services)
    .every(s => s === 'UP') ? 200 : 503;
    
  res.status(statusCode).json(health);
});

11. Disaster Types Coverage

11.1 Supported Disaster Types

Natural Disasters

Floods & Urban Flooding
Cyclones & Storms
Earthquakes & Aftershocks
Landslides & Mudslides
Droughts & Water Scarcity
Heatwaves & Cold Waves
Tsunamis
Wildfires
Avalanches (mountainous regions)

Man-Made Disasters

Industrial Accidents
Chemical Spills
Building Collapses
Fire Incidents
Transportation Accidents

11.2 Disaster-Specific Configurations

Each disaster type has:

Predefined service categories
Priority algorithms
Resource allocation patterns
Communication templates
Alert thresholds

12. MVP Feature Prioritization

12.1 Phase 1 (MVP Launch - Month 1-3)

Core Features

User registration and authentication
Basic RBAC (5 primary roles)
Service request submission
Geographic visualization (basic map with markers)
Service provider registration
Manual service assignment
Status tracking
Basic notifications (email)
Audit logging

Technical Infrastructure

PostgreSQL + PostGIS setup
Redis caching
NGINX reverse proxy
Basic API endpoints
GeoServer with WMS

12.2 Phase 2 (Enhancement - Month 4-6)

Additional Features

Automated service-provider matching
Advanced spatial queries
Real-time notifications (WebSocket)
Donation management
Enhanced privacy controls
Mobile-responsive UI
Advanced analytics dashboard
Export functionality

12.3 Phase 3 (Scale - Month 7-12)

Advanced Features

Chatbot integration
Multi-language support
Predictive analytics
Automated verification
Mobile applications
SMS integration
Advanced reporting
Integration with external systems

13. Data Migration & Initialization

13.1 Initial Data Setup

Administrative Boundaries

Import India state boundaries
Import district boundaries
Import block/taluk boundaries
Source: Government open data portals

Base Layers

OpenStreetMap data import
Critical infrastructure locations
Hospital and medical facility locations
Shelter locations

Seed Data

System administrator account
Default disaster types
Service type taxonomy
Default RBAC policies

13.2 Data Import Scripts

Import Administrative Boundaries

  
import geopandas as gpd
from sqlalchemy import create_engine

# Read shapefile
gdf = gpd.read_file('data/india_districts.shp')

# Convert to EPSG:4326
gdf = gdf.to_crs('EPSG:4326')

# Import to PostGIS
engine = create_engine(DATABASE_URL)
gdf.to_postgis('administrative_boundaries', 
               engine, 
               if_exists='replace',
               index=False)

14. Performance Optimization

14.1 Database Optimization

Indexing Strategy

B-tree indexes for equality searches
GiST indexes for spatial queries
GIN indexes for JSONB and array columns
Partial indexes for filtered queries

Query Optimization

  
-- Use EXPLAIN ANALYZE for query planning
EXPLAIN ANALYZE
SELECT * FROM service_requests
WHERE ST_DWithin(
  location::geography,
  ST_MakePoint(78.4867, 17.3850)::geography,
  5000
);

-- Create materialized views for analytics
CREATE MATERIALIZED VIEW service_stats AS
SELECT 
  service_type,
  status,
  COUNT(*) as count,
  DATE(created_at) as date
FROM service_requests
GROUP BY service_type, status, DATE(created_at);

CREATE INDEX idx_service_stats_date ON service_stats(date);

14.2 Caching Strategy

Redis Caching Layers

Session Cache - TTL: Until logout
User Profile Cache - TTL: 1 hour
Service List Cache - TTL: 5 minutes
Analytics Cache - TTL: 15 minutes
GeoServer Tile Cache - TTL: 24 hours

Cache Invalidation

Write-through for user updates
Time-based expiration for analytics
Event-based invalidation for service changes

14.3 API Performance

Response Time Targets

Authentication: < 200ms
Simple queries: < 300ms
Spatial queries: < 500ms
Complex analytics: < 2s
Map tile serving: < 100ms

Optimization Techniques

Database connection pooling
Query result pagination
Lazy loading for related entities
Response compression (gzip)
CDN for static assets

15. Backup & Disaster Recovery

15.1 Backup Strategy

PostgreSQL Backups

Daily full backups (retained 30 days)
Hourly incremental backups (retained 7 days)
Continuous WAL archiving
Backup verification weekly

Backup Script

  
#!/bin/bash
# Daily backup script

BACKUP_DIR="/backups/postgres"
DATE=$(date +%Y%m%d_%H%M%S)
BACKUP_FILE="$BACKUP_DIR/idrm_backup_$DATE.sql.gz"

# Perform backup
docker exec idrm-postgres pg_dump -U idrm_user idrm_db | gzip > $BACKUP_FILE

# Upload to cloud storage (optional)
# aws s3 cp $BACKUP_FILE s3://idrm-backups/

# Cleanup old backups (keep 30 days)
find $BACKUP_DIR -name "*.sql.gz" -mtime +30 -delete

15.2 Disaster Recovery Plan

Recovery Time Objective (RTO): 4 hours Recovery Point Objective (RPO): 1 hour

Recovery Procedures

Restore PostgreSQL from latest backup
Restore Redis data from persistence files
Restart all services via Docker Compose
Verify data integrity
Resume operations

16. Compliance & Legal

16.1 Data Protection

GDPR-like Compliance

Right to access personal data
Right to data portability
Right to erasure
Data minimization
Consent management

Data Retention

Active user data: Indefinite
Service requests: 7 years
Audit logs: 10 years
Donation records: 10 years
Inactive user data: 2 years (then anonymized)

16.2 Accessibility

WCAG 2.1 Level AA Compliance

Keyboard navigation support
Screen reader compatibility
Sufficient color contrast
Text alternatives for images
Responsive design

17. Future Enhancements

17.1 Machine Learning Integration

Predictive Capabilities

Disaster impact prediction
Resource demand forecasting
Optimal provider routing
Anomaly detection for fraud
Sentiment analysis from communications

17.2 Advanced Features

AI-Powered Chatbot

Natural language understanding
Multi-language support
Automated service request creation
Status inquiry handling
FAQ automation

Drone Integration

Real-time aerial imagery
Damage assessment automation
Supply delivery tracking
Search and rescue coordination

IoT Sensors

Environmental monitoring
Early warning systems
Infrastructure health monitoring
Crowd density tracking

17.3 Platform Expansion

Mobile Applications

Native iOS application
Native Android application
Offline functionality
Push notifications
Location tracking

Third-Party Integrations

Weather APIs
Social media monitoring
Government databases
International aid organizations
Emergency services (Police, Fire, Ambulance)

18. Success Metrics

18.1 Key Performance Indicators

Operational Metrics

Average time from request to assignment: < 30 minutes
Service completion rate: > 85%
Provider response rate: > 90%
System uptime: > 99.5%

User Adoption Metrics

Active users per month: Target 10,000 (Month 6)
Organizations registered: Target 500 (Month 6)
Service requests processed: Target 50,000 (Month 6)

Financial Metrics

Donation transparency score: 100%
Average fund allocation time: < 24 hours
Administrative overhead: < 5%

Impact Metrics

Lives saved (estimated): Tracked via service outcomes
Response time improvement: Benchmark vs traditional methods
Resource utilization efficiency: Tracked via analytics

19. Risk Management

19.1 Technical Risks

Risk	Probability	Impact	Mitigation
Data breach	Medium	High	Encryption, regular security audits, penetration testing
System downtime	Low	High	High availability setup, automated failover, backups
Performance degradation	Medium	Medium	Load testing, auto-scaling, caching optimization
Data loss	Low	High	Regular backups, replication, WAL archiving

19.2 Operational Risks

Risk	Probability	Impact	Mitigation
Misuse/Fraud	Medium	Medium	Verification system, audit trails, user reporting
Low adoption	Medium	High	User training, stakeholder engagement, marketing
Inaccurate data	Medium	High	Validation workflows, community verification
Privacy violations	Low	High	Privacy controls, data anonymization, compliance audits

20. Implementation Roadmap

20.1 Development Timeline

Month 1-2: Foundation

Week 1-2: Infrastructure setup, Docker environment
Week 3-4: Database schema, basic API development
Week 5-6: Authentication system, RBAC implementation
Week 7-8: Service request CRUD operations

Month 3-4: Core Features

Week 9-10: GeoServer integration, map visualization
Week 11-12: Service-provider matching logic
Week 13-14: Notification system, communication module
Week 15-16: Testing, bug fixes

Month 5-6: Enhancement & Launch

Week 17-18: Analytics dashboard, reporting
Week 19-20: Donation management, financial tracking
Week 21-22: User acceptance testing, documentation
Week 23-24: Training, MVP launch

20.2 Deployment Checklist

Pre-deployment

All tests passing (unit, integration)
Security audit completed
Performance testing completed
Documentation finalized
User training materials prepared
Backup and recovery procedures tested

Deployment

SSL certificates installed
Environment variables configured
Database migrations executed
Initial data seeded
GeoServer layers published
Monitoring tools configured

Post-deployment

Health checks verified
Monitoring alerts configured
User feedback mechanism active
Support team trained
Rollback plan documented
Performance metrics baseline established

21. Support & Maintenance

21.1 Support Tiers

Tier 1: User Support

FAQ documentation
Video tutorials
Email support
Community forum

Tier 2: Technical Support

Bug triage and fixing
Performance monitoring
System health checks
Regular updates

Tier 3: Development Support

Feature enhancements
Integration support
Custom development
Architecture consulting

21.2 Maintenance Schedule

Daily

Monitor system health
Check error logs
Review security alerts

Weekly

Database maintenance (VACUUM, ANALYZE)
Log rotation and cleanup
Performance metrics review
Security patch assessment

Monthly

Full system backup verification
Security audit
Dependency updates
Capacity planning review

Quarterly

Disaster recovery drill
Performance optimization
User feedback analysis
Feature roadmap review

22. Training & Documentation

22.1 User Documentation

End User Guide

Registration and login
Creating service requests
Tracking service status
Making donations
Privacy settings

Provider Guide

Organization registration
Accepting service requests
Updating service status
Reporting issues

Administrator Guide

User management
Role assignment
Disaster event creation
System configuration
Analytics and reporting

22.2 Technical Documentation

Architecture Documentation

System design diagrams
Database schema documentation
API documentation (OpenAPI/Swagger)
Deployment guides
Troubleshooting guides

Developer Documentation

Code contribution guidelines
API integration guides
Testing procedures
Release process

23. Conclusion

The IDRM MVP represents a comprehensive, technically sound approach to modernizing disaster response in India. By leveraging open-source technologies and following industry best practices, the platform establishes a foundation for scalable, secure, and effective disaster management coordination.

The combination of Node.js for real-time operations, Python for data processing, PostgreSQL with PostGIS for geospatial capabilities, and GeoServer for map serving creates a robust technical stack capable of handling the demands of nationwide disaster response.

Success depends on careful implementation, continuous monitoring, user feedback incorporation, and iterative improvement. The roadmap provides a clear path from MVP to a fully-featured platform that can genuinely save lives and improve disaster response outcomes across India.