What is Smart India Hackathon (SIH) 2026?

Smart India Hackathon (SIH) is the world’s biggest open innovation hackathon organized by the Ministry of Education, AICTE, and MIC, where student teams build hardware and software solutions for problem statements submitted by Government Ministries, Departments, and State Agencies.

How many problem statements are released in SIH 2026?

SIH 2026 features 226 official problem statements, comprising 172 Software category statements and 54 Hardware category statements across themes like Smart Automation, Agriculture, Disaster Management, MedTech, Clean Water, and Cybersecurity.

How does the SIH ONE AI Team Matchmaker work?

The SIH ONE Matchmaker takes your 6-member team’s frontend/backend/AI skills, hardware experience, domain preferences, and exclusions, then runs a multi-factor weighted scoring algorithm to rank the top 25 highest-fit problem statements.

Why is Synthetic Aperture Radar (SAR) indispensable for Antarctic navigation compared to optical cameras?

SAR active microwave radar penetrates thick polar clouds, blizzards, and complete 24-hour polar winter darkness, providing continuous surface roughness and ice thickness information.

How do you model iceberg drift when 90% of the iceberg mass is hidden beneath the ocean surface?

Our hydrodynamic model integrates the balance of forces: atmospheric wind drag on the visible sail (10%), deep ocean current drag on the underwater keel (90%), Coriolis force, and sea surface tilt.

How does the route optimization engine minimize fuel consumption through sea-ice?

The A* pathfinder assigns cost weights proportional to sea-ice concentration and thickness resistance, routing the vessel through natural leads (polynyas and fractures) to avoid heavy ice-ramming fuel burn.

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PS 26059SOFTWARESmart EducationModerate Scope

AI-Enabled Antarctic Sea-Ice, Iceberg Trajectory, and Navigation Decision Support System

Ministry of Earth Sciences (MoES)• National Centre for Polar andOcean Research (NCPOR)

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30-Second Plain English Summary

Indian Antarctic expeditions (vessels travelling from Cape Town to Bharati/Maitri stations) face catastrophic iceberg collisions, thick pack-ice besetting, and severe polar storms with delayed satellite ice charts. Build an AI-enabled Antarctic sea-ice and iceberg trajectory forecasting decision support platform combining multi-mission SAR satellite imagery (Sentinel-1 / RISAT), optical MODIS feeds, and ocean-wind drift physics to calculate optimal fuel-efficient and safe polar navigation corridors.

5-Dimension Strategic ScorecardOverall Score: 4 / 5.0

Innovation

4.4 / 5

36h Feasibility

4.3 / 5

Uniqueness

3.8 / 5

Jury Appeal

3.5 / 5

Tech Depth

3.8 / 5

Recommended System Architecture Pipeline

Sentinel-1 SAR Radar + ECMWF Polar Winds -> SAR Sea-Ice Segmentation AI -> Iceberg Drift Physics Model -> A* Polar Ice Routing Engine -> Ship Bridge Navigation Console

Recommended Tech StackClick to search similar

Official Government Problem Description

Develop an AI/ML-enabled decision support platform capable of forecasting Antarctic sea-ice concentration, predicting iceberg trajectories, and identifying safe and fuel-efficient navigation routes for research vessels using satellite,oceanographic and meteorological datasets.

AI & PPT Citation Format

Smart India Hackathon 2026 Problem Statement PS-26059: "AI-Enabled Antarctic Sea-Ice, Iceberg Trajectory, and Navigation Decision Support System", Ministry: Ministry of Earth Sciences (MoES). Strategy & Architecture via SIH ONE (https://sihone.pages.dev/ps/26059)

AI-Enabled Antarctic Sea-Ice, Iceberg Trajectory, and Navigation Decision Support System

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