prof-freakenstein/SIH2025 huggingface dataset:
Automated Specimen Preparation System for testing of Cable samples as per IS 10810 and IS 7098
Organization: Ministry of Consumer Affairs Food & Public Distribution (MoCA F&PD)
Category: Hardware | Theme: Miscellaneous

Background

Accurate and consistent preparation of cable specimens is vital for reliable testing according to Indian Standards like IS 10810 (Parts 2, 7, 33) and IS 7098 (Parts 1 & 2). These tests, including conductor resistance, insulation/sheath thickness, and flame retardance, are crucial for ensuring cable safety and quality.

Existing Problem

Currently, cable sample preparation involves significant manual intervention. The cable sample is manually cut by the operator and then straightened manually. Subsequently, these straightened PVC/XLPE/HDPE cable samples are cut into slices using electrically/pneumatically operated machines. Further, the samples are shaped as dumbbells by a dumbbell cutting machine. These manual and semi-automated steps are time-consuming, prone to human error, and introduce inconsistencies that compromise the accuracy and repeatability of critical test results.

Detailed Description

This project develops an automated machine designed to precisely cut insulation and outer sheaths from cables, preparing specimens that strictly adhere to the aforementioned IS standards. Key features include an Automated Cable Feeding and Clamping System utilizing motor-driven rollers and adjustable clamps for secure, straightened cable handling. The Cutting and Stripping Module employs precision blades with programmable depths for clean, circumferential cuts and linear stripping, fulfilling specific length requirements for various tests. An integrated diameter sensor will auto-adjust settings. A Control System (PLC/HMI) manages operations, allows test method selection, monitors status, and provides closed-loop feedback. Automated specimen ejection and waste management further streamline workflow. Robust safety features like enclosed areas and interlocks will protect operators.

Expected Solution

The automated machine will eliminate human error, guaranteeing consistent and repeatable specimen quality while significantly reducing preparation time and costs. By ensuring strict adherence to IS standards, the solution will yield more reliable test results and simplify product certification. This advancement will markedly improve accuracy, efficiency, and safety in cable testing, supporting high-quality control in the cable manufacturing industry.
Enhancing Student Awareness on difference between Aadhaar linked and Direct Beneficiary Transfer(DBT) enabled Aadhaar seeded bank account
Organization: Ministry of Social Justice & Empowerment (MoSJE)
Category: Software | Theme: Miscellaneous

Background

SCD-V Division, DoSJE implements Centrally sponsored schemes 'Pre-Matric scholarships schemes for SCs & Others' and 'Post-Matric scholarships schemes for SC students'. The entire scholarship amount - both from the State and Central Government is paid directly into the account of the students ONLY through Direct Beneficiary Transfer (DBT) enabled Aadhaar seeded bank account. However, many students are unaware of the distinction between Aadhaar linked and Direct Beneficiary Transfer (DBT) enabled Aadhaar seeded bank account. As a result, a significant number of students do not have Aadhaar-seeded bank account, leading to delays in scholarships disbursement and posing challenges for them.

Description

The above problem statement envisages that many students are unaware of the distinction between Aadhaar linked and Direct Beneficiary Transfer (DBT) enabled Aadhaar seeded bank account. As a result, a significant number of students do not have Aadhaar-seeded bank account, leading to delays in scholarships disbursement and posing challenges for them. Government of India is continuously providing support to promote digital inclusion, however there is need of extensive awareness on the importance and procedures of Aadhaar seeding with Bank Accounts.

Expected Solution

The students need to be made more aware about the difference between Aadhaar linked and Direct Beneficiary Transfer (DBT) enabled Aadhaar seeded bank account for availing pre & post-Matric scholarships scheme for SCs. Extensive awareness programmes should be conducted through Gram Panchayats Notice Boards, school committees, and discussions in the parent-teacher association meetings and other public awareness measures.
Digitize and Showcase Monasteries of Sikkim for Tourism and Cultural Preservation
Organization: Government of Sikkim
Category: Software | Theme: Travel & Tourism

Background

The agricultural region of Jorethang in South Sikkim experiences harsh, rainless summers and frequent water scarcity, making traditional irrigation unreliable and inefficient. Farmers struggle to provide adequate water to crops, often leading to reduced yields and wasted resources. With climate change intensifying these issues, there's a pressing need for a sustainable, smart irrigation approach that maximizes water efficiency and crop productivity. Integrating rainwater harvesting, sensor-based monitoring, and crop-specific intelligence offers a forward-thinking solution to these regional challenges.

Proposed Solution

AgroSmart: A Sensor-Based Smart Irrigation System with Crop Intelligence and Rainwater Harvesting. This system aims to provide affordable, automated irrigation tailored to each crop’s needs using soil moisture and environmental sensors. It integrates a rainwater harvesting unit with real-time water level monitoring, ensuring efficient water use even during dry periods.

The solution will include:
- Soil moisture and temperature sensors to monitor field conditions.
- A crop database that determines optimal watering levels.
- Automated valve control through microcontrollers (Arduino/ESP32).
- Rainwater harvesting with level sensors to track available water.
- A mobile/web dashboard for farmers to monitor data and control irrigation remotely.
- Alerts and updates via SMS or app to keep farmers informed.

Impact

Conserves water, improves crop yields, minimizes manual labour, and helps farmers in Jorethang adapt to climate variability with a smart, self-sustaining irrigation system.
Implementation of Smart Agriculture for Efficient Cultivation in Hilly Regions
Organization: Government of Sikkim
Category: Hardware | Theme: Agriculture FoodTech & Rural Development

Background

The agricultural region of Jorethang in South Sikkim experiences harsh, rainless summers and frequent water scarcity, making traditional irrigation unreliable and inefficient. Farmers struggle to provide adequate water to crops, often leading to reduced yields and wasted resources. With climate change intensifying these issues, there's a pressing need for a sustainable, smart irrigation approach that maximizes water efficiency and crop productivity. Integrating rainwater harvesting, sensor-based monitoring, and crop-specific intelligence offers a forward-thinking solution to these regional challenges.

Proposed Solution

AgroSmart: A Sensor-Based Smart Irrigation System with Crop Intelligence and Rainwater Harvesting. This system aims to provide affordable, automated irrigation tailored to each crop’s needs using soil moisture and environmental sensors. It integrates a rainwater harvesting unit with real-time water level monitoring, ensuring efficient water use even during dry periods.

The solution will include:
- Soil moisture and temperature sensors to monitor field conditions.
- A crop database that determines optimal watering levels.
- Automated valve control through microcontrollers (Arduino/ESP32).
- Rainwater harvesting with level sensors to track available water.
- A mobile/web dashboard for farmers to monitor data and control irrigation remotely.
- Alerts and updates via SMS or app to keep farmers informed.

Impact

Conserves water, improves crop yields, minimizes manual labour, and helps farmers in Jorethang adapt to climate variability with a smart, self-sustaining irrigation system.
Developing a cost effective solution for detecting the breakage of Low Voltage AC Distribution Over Head conductors
Organization: Government of Kerala
Category: Hardware | Theme: Disaster Management

Background

A cost-effective solution is required for detecting the breakage of Low Voltage AC Distribution Over Head conductors towards isolating the source of supply to prevent hazardous electric shock scenarios to the public, while also sending alarms to the concerned section office for immediate fault rectification.

Recently, several cases of accidental deaths of children and adults due to electrocution from broken live conductors lying on the ground were reported in Kerala. Low voltage distribution lines often snap due to falling trees during natural calamities and also due to aging or corrosion. This dangerous condition is not detected or isolated by upstream fuses in these feeders because of high earth resistance and low fault current, leading to electrocution deaths when people come into contact with live bare conductors. Many existing solutions identified so far are not cost-effective or viable for the vast distribution network.

Expected Solution

An innovative solution based on IoT and AI, including edge intelligence, may provide an economical and scalable solution for this socially relevant problem faced by KSEBL.
Improving the Renewable Energy hosting capacity in Distribution Feeders improving the Power quality of Distribution network during high RE injection
Organization: Government of Kerala
Category: Hardware | Theme: Renewable / Sustainable Energy

Background

Kerala has a large penetration of Roof Top Solar PV systems amounting to nearly 1500 MW. These systems are connected to low voltage distribution feeders either in single-phase or three-phase mode. A majority of the systems are below 5 kW and hence get connected in single-phase, which causes severe unbalanced loading in feeders and results in an uneven voltage profile. This unbalanced loading also limits the quantum of PV that can be integrated into the network.

Any load balancing work carried out during daytime under PV injection gets negated during the evening peak hours when solar power is unavailable. This situation calls for a solution that can dynamically reconfigure the network based on renewable energy (RE) injection and local demand scenarios.

Expected Solution

A cost-effective controller incorporating IoT and edge intelligence can be developed at the local node level for auto-balancing of the load across various phases in a feeder under the above conditions.
Designing and development of an application for on spot assessment of Roof Top Rain water harvesting and artificial recharge potential and size of the RTRWH and AR
Organization: Ministry of Jal Shakti
Category: Software | Theme: Smart Automation

Background

Groundwater replenishment is a critical factor for the augmentation and sustainability of water resources in the country. There is significant potential in both rural and urban areas for harvesting rainwater from individual rooftops. The Central Ground Water Board (CGWB) has published several scientific manuals and reports on rooftop rainwater harvesting (RTRWH) potential, as well as FAQs and practical guides for artificial recharge. However, there is currently no user-friendly digital platform where individuals can directly assess their rainwater harvesting potential.

Proposed Solution

To promote public participation in groundwater conservation, it is proposed to develop a web/mobile application that enables users to easily estimate the feasibility of rooftop rainwater harvesting (RTRWH) and artificial recharge at their locations. By entering simple details such as name, location, number of dwellers, roof area, and available open space, the system will generate personalized outputs using GIS-based and algorithmic models.

Key Features
- Feasibility check for rooftop rainwater harvesting
- Suggested type of RTRWH/Artificial Recharge structures
- Information on principal aquifer in the area
- Depth to groundwater level
- Local rainfall data
- Runoff generation capacity
- Recommended dimensions of recharge pits, trenches, and shafts
- Cost estimation and cost-benefit analysis

Impact

The application will empower individuals and communities to take informed decisions about groundwater conservation and rainwater harvesting. It will enhance public awareness, encourage participation, and support sustainable water management efforts. The tool should also support regional languages for better accessibility and inclusivity.
Development of an AI-driven ChatBOT for INGRES as a virtual assistant
Organization: Ministry of Jal Shakti
Category: Software | Theme: Smart Automation

Background

The Assessment of Dynamic Ground Water Resources of India is conducted annually by the Central Ground Water Board (CGWB) and State/UT Ground Water Departments, under the coordination of the Central Level Expert Group (CLEG), DoWR, RD & GR, MoJS. The assessment uses a GIS-based web application named INGRES (India Ground Water Resource Estimation System), developed by CGWB and IIT Hyderabad (https://ingres.iith.ac.in/home). The process estimates annual groundwater recharge, extractable resources, total extraction, and the stage of groundwater extraction for each assessment unit (Block/Mandal/Taluk). Units are categorized as Safe, Semi-Critical, Critical, or Over-Exploited, forming the scientific basis for groundwater management and regulation.

Currently, results are published via the INGRES portal, but users face challenges in retrieving results and historical data due to the vast database.

Proposed Solution

To improve accessibility, it is proposed to develop an AI-driven ChatBOT for INGRES. This intelligent virtual assistant will enable users to easily query groundwater data, access historical and current assessments, and obtain instant insights without navigating complex datasets.

Key Features
- Intelligent query handling for groundwater estimation data
- Real-time access to current and historical assessment results
- Interactive scientific diagrams and visualizations
- Multilingual support, including Indian regional languages
- Seamless integration with the INGRES database for quick information retrieval

Impact

The AI-powered ChatBOT will enhance user engagement, simplify access to groundwater resource data, and support informed decision-making for planners, researchers, policymakers, and the general public. It will make the INGRES portal more user-friendly, accessible, and effective in disseminating groundwater information.
Proposal for Design and development of application for Heavy Metal Pollution indices
Organization: Ministry of Jal Shakti
Category: Software | Theme: Miscellaneous

Background

The presence of heavy metals in drinking water, even at trace levels, poses significant health risks, making accurate and timely assessment critical for public safety and environmental monitoring. Although several indices exist for assessing heavy metal pollution, their manual computation is tedious, time-consuming, inconsistent, and vulnerable to human error due to the complexity and variability of formulas.

Proposed Solution

It is proposed to develop an automated, user-friendly application that can compute Heavy Metal Pollution Indices (HMPI) in groundwater using standard formulas with minimal manual intervention. This tool will streamline calculations, reduce errors, and provide reliable outputs for stakeholders.

Key Features
- Automated computation of heavy metal pollution indices using standard methodologies
- Integration of groundwater heavy metal concentration datasets with geo-coordinates
- Categorization of groundwater quality based on heavy metal presence
- User-friendly interface for scientists, researchers, and policymakers
- Reduction of manual effort and error-prone processes

Impact

The application will provide accessible and reliable insights into groundwater heavy metal contamination, enabling better decision-making, enhanced environmental monitoring, and improved public health protection.
Real time Groundwater resource evaluation using DWLR data
Organization: Ministry of Jal Shakti
Category: Software | Theme: Miscellaneous

Background

The presence of heavy metals in drinking water, even at trace levels, poses significant health risks, making accurate and timely assessment critical for public safety and environmental monitoring. Although several indices exist for assessing heavy metal pollution, their manual computation is tedious, time-consuming, inconsistent, and vulnerable to human error due to the complexity and variability of formulas.

Proposed Solution

It is proposed to develop an automated, user-friendly application that can compute Heavy Metal Pollution Indices (HMPI) in groundwater using standard formulas with minimal manual intervention. This tool will streamline calculations, reduce errors, and provide reliable outputs for stakeholders.

Key Features
- Automated computation of heavy metal pollution indices using standard methodologies
- Integration of groundwater heavy metal concentration datasets with geo-coordinates
- Categorization of groundwater quality based on heavy metal presence
- User-friendly interface for scientists, researchers, and policymakers
- Reduction of manual effort and error-prone processes

Impact

The application will provide accessible and reliable insights into groundwater heavy metal contamination, enabling better decision-making, enhanced environmental monitoring, and improved public health protection.
AI-Driven Life Cycle Assessment (LCA) Tool for Advancing Circularity and Sustainability in Metallurgy and Mining
Organization: Ministry of Mines
Category: Software | Theme: Miscellaneous

Background

As industries increasingly emphasize sustainability, Life Cycle Assessment (LCA) is emerging not just as a tool for measuring environmental impact, but as a key strategy for advancing circularity. Metals like aluminium and copper, vital to sectors from energy to infrastructure, undergo multiple stages — from extraction and processing to use and end-of-life. Traditional linear models often result in resource depletion and waste. Modern LCA frameworks now assess not only emissions and resource use, but also the potential for reuse, recycling, and closed-loop systems. By informing decisions on product design, manufacturing, and end-of-life recovery, LCA enables a shift toward a circular economy where materials are kept in use longer and waste is minimized.

Problem Statement

There is a need to design an intuitive, AI-powered software platform that enables metallurgists, engineers, and decision-makers to perform automated LCAs for metals such as aluminium, copper, or critical minerals, with a special emphasis on circularity.

Proposed Solution
The platform should:
- Allow users to input or select process and production details (including raw vs. recycled routes, energy use, transport, and end-of-life options).
- Use AI/ML models to estimate missing parameters and predict both environmental and circularity indicators (e.g., recycled content, resource efficiency, extended product life, potential for reuse).
- Visualize circular flow opportunities alongside environmental impacts across the full value chain — from raw material extraction through reuse or recycling.
- Enable easy comparison of conventional and circular processing pathways.
- Generate actionable reports and recommendations for reducing impacts and enhancing circularity, even when users have limited data or specialized expertise.

Impact

With this tool, the metals sector will be empowered to make practical, data-driven choices that foster environmental sustainability while advancing circular, resource-efficient systems.
Secure Data Wiping for Trustworthy IT Asset Recycling
Organization: Ministry of Mines
Category: Software | Theme: Miscellaneous

Background

India is facing a growing e-waste crisis, generating over 1.75 million tonnes annually. A key reason why millions of old laptops and smartphones remain unused or improperly discarded is fear of data breaches. Most users hesitate to recycle their devices due to concerns about sensitive personal or organizational data being recovered. Existing data sanitization tools are either too complex, expensive, or lack verifiable proof of erasure. This gap has led to over ₹50,000 crore worth of IT assets being hoarded in homes and offices, hindering circular economy efforts. A user-friendly, tamper-proof, and auditable data wiping solution is urgently needed to promote safe disposal and reuse of electronic devices.

Problem Statement

Design and prototype a secure, cross-platform data wiping application that works on Windows, Linux, and Android devices. The tool must:
- Securely erase all user data, including hidden storage areas like HPA/DCO and SSD sectors.
- Generate a digitally signed, tamper-proof wipe certificate (in PDF and JSON formats).
- Feature an intuitive one-click interface suitable for general public use.
- Offer offline usability (e.g., bootable ISO/USB).
- Enable third-party verification of wipe status.
- Be scalable, standards-compliant (aligned with NIST SP 800-88), and support trust and transparency in IT asset disposal and recycling workflows.

Impact

This solution will build user confidence in device recycling, reduce hoarding of IT assets, promote safe e-waste management, and advance India’s circular economy initiatives.
AI-Based Rockfall Prediction and Alert System for Open-Pit Mines
Organization: Ministry of Mines
Category: Software | Theme: Disaster Management

Background

Rockfalls in open-pit mines pose a significant threat to both personnel and equipment, often resulting in serious injuries, operational delays, and financial loss. Traditional rockfall detection systems rely on visual inspection or expensive proprietary solutions, which are either labor-intensive or lack real-time predictive capabilities. With the increasing use of digital monitoring and AI, there is a pressing need to integrate predictive analytics into slope stability assessments for proactive decision-making.

Description

This problem invites participants to design a smart, AI-based system capable of predicting potential rockfall incidents in open-pit mines. The system should process multi-source data inputs including:
- Digital Elevation Models (DEM)
- Drone-captured imagery
- Geotechnical sensor data (displacement, strain, pore pressure)
- Environmental factors (rainfall, temperature, vibrations)

Machine learning models should identify patterns that precede rockfall events. The system must feature a user-friendly dashboard for mine planners, along with:
- Real-time risk maps
- Probability-based forecasts
- Alert mechanisms (via SMS/email)
Integration with low-cost monitoring hardware would be an added advantage.

Expected Solution

- A machine learning model trained on real or synthetic data to predict rockfall risks.
- A web/mobile-based dashboard for visualization of vulnerable zones.
- Real-time alert generation with suggested action plans.
- Open-source integration possibilities for scale and customization.

Impact

The solution should be cost-effective, scalable for different mine sites, and adaptable for both public and private mining operations, enabling safer and more resilient mining practices.