OceanGrid AI: Marine Resource Intelligence Platform
Budget: ₹75,000 – ₹150,000 INR
Project Brief: Full Stack Development of "OceanGrid AI"
Project Title:
Development of “OceanGrid AI” – A Web & Mobile Platform for Marine Resource Intelligence
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Objective:
To build OceanGrid AI, an integrated geospatial + AI-powered platform that maps, analyzes, and visualizes marine mineral/oil/gas resource potential in Indian Ocean territories (starting with India’s EEZ), and ultimately enables commercial, environmental, and strategic exploitation of these resources using AI insights.
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Project Scope:
You will develop the first functional MVP (Minimum Viable Product) of OceanGrid AI including:
1. User Dashboard (Web & Mobile):
Geospatial map of Indian Ocean with interactive layers.
Mineral deposit visualizations (uploadable via datasets or simulated data).
Satellite image viewer + bathymetric overlays.
Resource heatmap (oil, manganese, hydrocarbons, REEs).
AI-predicted zones of high potential (color-coded).
2. AI Module (Back-end):
Basic ML algorithm to simulate resource prediction zones based on known data.
Future scope: Plug into ocean sensor APIs, satellite feeds.
3. Data Layer Integrations:
Marine topography (use public NOAA, ISRO, or GEBCO datasets).
Indian EEZ boundaries.
Overlay: shipping lanes, seafloor types, tectonic boundaries.
4. Admin Panel:
Upload/import new datasets (CSV, GeoTIFF, JSON).
Moderate user access.
Manage prediction model parameters (via UI sliders).
5. User Features:
Search, filter by mineral/oil type, coordinates, EEZ zones.
Download reports.
Login with OTP/email (no Google auth needed for MVP).
Save/view bookmarks of zones.
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Tech Stack (Suggested):
Frontend: React.js (web), React Native or Flutter (mobile)
Backend: Python (FastAPI or Django)
Map Layer: Leaflet.js, Mapbox, or Cesium.js
Database: PostgreSQL + PostGIS
AI/ML: scikit-learn or TensorFlow (basic models for MVP)
Hosting: AWS or DigitalOcean
Version Control: GitHub or GitLab
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Security & IP Protection:
You must agree to the following before work starts:
1. NDA (Non-Disclosure Agreement) – Mandatory before project details are shared.
2. IP Assignment Agreement – All code, models, and designs created belong 100% to the client (me).
3. No reuse or resale of code, datasets, UI, or backend components.
4. No outsourcing without prior written approval.
5. Use of private Git repo (access controlled).
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Budget:
Initial MVP: ₹60,000 to ₹1,50,000 (INR) / $750 to $2000 (USD)
(Depending on skill, speed, and quality)
Bonus for early delivery and future equity options if performance exceeds expectations.
---
Timeline:
Week 1: UX wireframes + project planning
Week 2–3: Frontend + map integrations
Week 3–4: Backend + ML model + basic AI predictions
Week 5: Testing + UI polish
Week 6: Final handoff + deployment
---
Ideal Developer/Team:
Experience in geospatial applications, Mapbox, PostGIS.
Strong in full-stack web/mobile dev (React + Python).
Bonus: Past work in climate/ocean/defense data or AI
Project Title:
Development of “OceanGrid AI” – A Web & Mobile Platform for Marine Resource Intelligence
---
Objective:
To build OceanGrid AI, an integrated geospatial + AI-powered platform that maps, analyzes, and visualizes marine mineral/oil/gas resource potential in Indian Ocean territories (starting with India’s EEZ), and ultimately enables commercial, environmental, and strategic exploitation of these resources using AI insights.
---
Project Scope:
You will develop the first functional MVP (Minimum Viable Product) of OceanGrid AI including:
1. User Dashboard (Web & Mobile):
Geospatial map of Indian Ocean with interactive layers.
Mineral deposit visualizations (uploadable via datasets or simulated data).
Satellite image viewer + bathymetric overlays.
Resource heatmap (oil, manganese, hydrocarbons, REEs).
AI-predicted zones of high potential (color-coded).
2. AI Module (Back-end):
Basic ML algorithm to simulate resource prediction zones based on known data.
Future scope: Plug into ocean sensor APIs, satellite feeds.
3. Data Layer Integrations:
Marine topography (use public NOAA, ISRO, or GEBCO datasets).
Indian EEZ boundaries.
Overlay: shipping lanes, seafloor types, tectonic boundaries.
4. Admin Panel:
Upload/import new datasets (CSV, GeoTIFF, JSON).
Moderate user access.
Manage prediction model parameters (via UI sliders).
5. User Features:
Search, filter by mineral/oil type, coordinates, EEZ zones.
Download reports.
Login with OTP/email (no Google auth needed for MVP).
Save/view bookmarks of zones.
---
Tech Stack (Suggested):
Frontend: React.js (web), React Native or Flutter (mobile)
Backend: Python (FastAPI or Django)
Map Layer: Leaflet.js, Mapbox, or Cesium.js
Database: PostgreSQL + PostGIS
AI/ML: scikit-learn or TensorFlow (basic models for MVP)
Hosting: AWS or DigitalOcean
Version Control: GitHub or GitLab
---
Security & IP Protection:
You must agree to the following before work starts:
1. NDA (Non-Disclosure Agreement) – Mandatory before project details are shared.
2. IP Assignment Agreement – All code, models, and designs created belong 100% to the client (me).
3. No reuse or resale of code, datasets, UI, or backend components.
4. No outsourcing without prior written approval.
5. Use of private Git repo (access controlled).
---
Budget:
Initial MVP: ₹60,000 to ₹1,50,000 (INR) / $750 to $2000 (USD)
(Depending on skill, speed, and quality)
Bonus for early delivery and future equity options if performance exceeds expectations.
---
Timeline:
Week 1: UX wireframes + project planning
Week 2–3: Frontend + map integrations
Week 3–4: Backend + ML model + basic AI predictions
Week 5: Testing + UI polish
Week 6: Final handoff + deployment
---
Ideal Developer/Team:
Experience in geospatial applications, Mapbox, PostGIS.
Strong in full-stack web/mobile dev (React + Python).
Bonus: Past work in climate/ocean/defense data or AI
Related categories:
Python
Geospatial
PostgreSQL
React.js
Full Stack Development
React Native
Flutter
GitHub
FastAPI
AI Development