Problem Statements Explorer

The North Eastern Region of India frequently suffers from landslides that cut off villages and cause damage. This problem asks for an AI system that uses various data sources like weather and satellite images to predict where and when landslides might happen. The system should then warn people and authorities in real-time to help save lives and property.

The North Eastern Region (NER) struggles with getting essential goods around due to tough roads and bad weather. We need to build a smart system that uses AI and maps to track transport, predict problems like landslides, and suggest better routes in real-time to ensure supplies reach everyone efficiently. This platform will help government officials and field workers manage logistics and respond to emergencies better.

An easy-to-use mobile and tablet app designed for elderly dementia patients in Northeast India that uses fun, culturally familiar voice-controlled games to keep their minds active. It helps them remember daily tasks like taking medicines while letting their families and doctors track their mental health progress, even without an internet connection.

Many people in North Eastern India suffer from joint pain (Osteoarthritis) but struggle to get early diagnosis due to limited healthcare access. This problem asks for a smart, portable system that uses AI to help local health workers detect early signs of joint problems, even in remote areas, and provide preventive advice.

Farmers in India's North East lose a lot of fresh vegetables because they lack proper cold storage. We need to build a small, solar-powered smart cold storage unit that keeps vegetables fresh longer, even in remote areas with no electricity, helping farmers earn more and reduce waste.

SAIL currently guesses when to rent ships for importing bulk cargo, leading to higher costs and delays. This problem asks us to build a smart system that predicts future shipping prices and recommends the best time and type of ship to rent, considering port limitations, to save money and improve efficiency.

Mine vehicles struggle to operate safely and efficiently in dense fog, causing delays and accidents. We need a smart system to help drivers see better, avoid crashes, and keep operations running smoothly even when visibility is very low.

Conveyor belts in iron ore mines often break down due to joint ruptures and damage, causing costly delays and safety risks. We need to build a smart system that uses sensors and cameras to detect early signs of damage and predict failures before they happen, moving away from manual checks.

MOIL, India's top manganese producer, struggles to find new reserves and predict production issues. This problem asks teams to build an AI tool that uses satellite data and company records to accurately locate manganese, foresee production shortfalls, and suggest solutions to keep ore flowing.

Rural Indian land records are outdated and inaccurate, leading to many disputes and hindering development. We need to build a modern, tech-driven system to accurately map agricultural land, update ownership records digitally, and make land administration transparent and efficient.

Traditional land records only show flat 2D maps, making it impossible to legally define who owns which floor in a high-rise building or who owns underground spaces. This system builds a smart 3D digital map of properties (above and below ground) and assigns a unique digital ID (3D ULPIN) to every single flat, basement, or utility space. This ensures clear ownership, prevents property disputes, and helps cities plan infrastructure better.

Currently, mapping land boundaries and buildings in crowded cities is done manually by drawing lines on drone photos, which takes months. We are building an AI-powered web platform that automatically traces land boundaries, buildings, and roads from drone images in minutes, and lets surveyors easily fix any errors on an interactive map.

Different government departments hold separate, conflicting map layers and tax records for the same urban land parcels. This platform automatically ingests drone maps, legacy land surveys, and utility lines, aligns their boundaries, fixes geometric errors, and unifies them into a single accurate master land map.

India's land records are currently scattered across different state departments with incompatible systems, causing land disputes and slow public services. Land Stack solves this by creating a unified GIS map platform where every land parcel gets a unique digital ID (ULPIN) linked to its ownership, tax, zoning, and utility records. This acts as a single source of truth for both government officials and citizens.

Currently, field workers take photos of rural water and land conservation projects, but these photos are only stored as plain evidence without deeper analysis. This project builds a smart mapping tool that connects ground photos with satellite maps to track environmental changes like increased water levels, crop growth, and soil health over time. It transforms simple field photos into a live interactive map for monitoring rural development projects.

This project aims to build a single digital platform for all of India to manage land acquisition for infrastructure projects like highways and railways. It automates paperwork, tracks land coordinates on a map, monitors compensation payments to landowners, and ensures displaced families receive proper resettlement support in real time.

Major highway, railway, and urban building projects in India get delayed for years because acquiring land takes too long due to legal fights, late compensation, and lost paperwork. This project asks for a smart computer system that looks at project details, predicts which land acquisitions will get stuck before it actually happens, explains why, and shows warning signals on an interactive map so government officers can fix the issues early.

This project aims to build an AI platform that automatically converts old, handwritten, and scanned paper land records in multiple Indian languages into organized digital data. It checks the extracted information for errors, highlights uncertain entries for human review, and links the data directly with official government land databases and maps.

This problem asks for a unified digital platform where researchers, policy makers, and government officials can access land data, simulate policy changes, analyze GIS maps, and collaborate on evidence-based land governance across India.

Rural Khadi spinning artisans, mostly women, suffer from physical fatigue, joint pain, and slow output due to heavy and non-ergonomic traditional hand-spinning wheels (Charkhas). This problem asks for a redesigned, lightweight, highly efficient, and ergonomic hand-operated spinning machine that significantly increases yarn output and quality without using grid electricity.