Background

NMDC Limited is India’s largest Iron Ore producer, currently producing approximately 53 Million Tonnes Per Annum (MTPA) from its three fully mechanized mining complexes, namely BIOM-Kirandul Complex, BIOM-Bacheli Complex in Chhattisgarh, and Donimalai Complex in Karnataka. The Bailadila Region alone contributes nearly 37 MTPA of Iron Ore production. In line with the National Steel Policy, NMDC has set a target of achieving 100 MT production capacity by 2030, with approximately 80 MT expected from the Bailadila Sector. The Bailadila mining region experiences severe monsoon conditions from June to October, including heavy rainfall, strong winds, high humidity, dense clouds, and thick fog. During this period, visibility on mine haul roads, particularly in hilltop mining areas, often reduces to as low as 3–5 meters. These conditions significantly affect the safe and efficient movement of Heavy Earth Moving Machinery (HEMM), especially dumpers engaged in ore transportation.

Problem Description

Dense fog and extremely low visibility during the monsoon season create major operational and safety challenges in the Bailadila iron ore mines. Poor visibility restricts dumper movement, forcing operators to reduce speed or temporarily halt operations to avoid accidents and unsafe conditions.This results in increased haul cycle times, reduced fleet productivity, lower ore evacuation, and production losses. The risk of vehicle collision, road accidents, and operational disruptions also increases substantially during such conditions. Existing visibility aids and operational controls have limited effectiveness in dense fog environments.There is a need for an intelligent, reliable, and technology-driven solution that can enable safe and efficient movement of mine vehicles under low-visibility conditions while ensuring continuity of operations and maintaining production levels.

Expected Solution

The proposed solution should improve operator situational awareness, assist in vehicle guidance and collision avoidance, and support real-time monitoring and decision-making for safe haul road operations during adverse weather conditions. The solution may leverage technologies such as

Expected Outcomes

Background

In the iron ore mining industry, conveyor belt systems are the backbone of material transportation, enabling continuous movement of iron ore from mining faces to crushing, screening, stockyard, and dispatch areas. One of the major operational challenges is conveyor belt joint rupture and belt damage, as belt joints are highly vulnerable to failure due to excessive tension,misalignment, wear, overloading, and maintenance deficiencies. Unexpected belt failures can cause production downtime, safety risks, high maintenance costs, delays in ore transportation, and damage to associated equipment.Traditional maintenance practices are mostly reactive or schedule based, which often fail to detect early-stage degradation of conveyor belts and joints. As mining operations increasingly move toward Industry 4. 0 and smart mining, there is a growing need for intelligent, real-time, predictive systems that can proactively identify belt health deterioration and prevent catastrophic failures.

Detailed Description

Conveyor belt joints in iron ore mines are continuously exposed to heavy loads, high tension, dust, moisture, and frequent start-stop operations. These harsh working conditions gradually damage the belt joints and conveyor belt through cracks, wear, edge damage, rubber weakening, and splice failure. If these issues are not detected early, they can lead to sudden belt rupture and major operational breakdowns. Mostly inspections are done manually and only at fixed intervals, making it difficult to identify early signs of failure. In normal practices, maintenance is mostly reactive, meaning repairs are performed only after visible damage or breakdown occurs. This results in unexpected shutdowns, emergency repairs, and increased maintenance costs. The major impacts on mining operations are as below Production- Loss of ore transportation capacity Maintenance- Increased repair and spare cost Safety- Risk of accidents during belt rupture Energy- Higher power consumption due to misalignment & friction Asset Life- Reduced conveyor and pulley lifespan Sustainability- Material spillage and wastage Therefore, belt joint rupture and conveyor belt damage remain major operational and financial challenges in iron ore mining industries. Conventional maintenance approaches are insufficient for ensuring high conveyor reliability in modern mining operations.

Expected Solution

To develop an Intelligent Conveyor Belt Health Monitoring and Predictive Maintenance System using digitalization, IoT, AI, and machine learning technologies to detect early signs of belt joint deterioration and damages. The proposed digitalized system architecture may include the following:

The proposed solution aims to reduce unplanned downtime, improve safety, minimize maintenance costs, and enhance conveyor reliability and operational efficiency in iron ore mining industries.

Background

Historically, land surveys in rural lndia were conducted using conventional chain and tape methods, many of which date back several decades or even the colonial period. Over time, multiple issues emerged such as Boundary changes due to inheritance and informal partition, Unrecorded land transactions, Encroachments and overlapping claims, Errors in cadastral maps, Mismatch between textual records and spatial maps, Absence of updated mutation records and inconsistent land classifications. These deficiencies have resulted in prolonged legal disputes, reduced agricultural productivity, and administrative inefficiencies. Land-related disputes reportedly account for a major share of civil litigation in lndia.

Detailed Description

A comprehensive survey/resurvey program is necessary to establish accurate land ownership, Update cadastral maps, Reduce land disputes,Enable transparent land governance, Support precision agriculture, lmprove rural planning, Facilitate digital land administration and Ensure effective implementation of government schemes.Modern technologies such as Drone mapping, Differential GPS (DGPS), GIS platforms, Satellite imagery, CORS, Mobile-based field verification can significanfly improve accuracy, speed, and transparency in rural land management.

Expected Solution

Technology-Driven Land Survey and Resurvey be implemented using modern survey technologies for accurate mapping of agricultural land parcels such as Drone-based aerial surveys, Real-Time Kinematic (RTK) GPS and DGPS systems, GIS-enabled cadastral mapping and Geo-referenced parcel identification. Developing a unified digital land information system integrating Record of Rights(RoR), Mutation records, Registration databases, Survey maps, Ownership history,precise Geo-coordinates of land parcels. This integration should enable real-time updating and verification of land ownership.

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.

Design and develop an indigenous, low-cost, autonomous ocean observation platform capable of long-term deployment in harsh polar and Southern Ocean environments for measuring key oceanographic and atmospheric parameters.

Problem Statement

Cooperative members, farmers, and rural stakeholders often lack awareness regarding cooperative laws, government schemes, PACS services, crop insurance schemes, financial literacy, and grievance redressal mechanisms due to language barriers and limited access to reliable guidance.

Objective

To develop an AI-powered multilingual chatbot capable of providing instant guidance and support on cooperative governance, legal provisions, schemes, and member services.

Expected Solution Features

Multilingual conversational interface Guidance on cooperative laws and by-laws Information on Ministry of Cooperation schemes and services PMFBY and agricultural support guidance Financial literacy assistance Cooperative grievance redressal support Voice-enabled assistance for rural users Integration with mobile and web platforms

Technology Components

Natural Language Processing (NLP) Artificial Intelligence Chatbot Frameworks Speech-to-Text & Text-to-Speech Integration Cloud Computing

Proposed Mode

Software + Hardware

Background

India's retail sector includes millions of neighborhood stores, supermarkets,pharmacies, and large-format retail outlets that serve high customer volumes every day. Retailers face challenges such as inventory shrinkage, stock-outs, long billing queues, inefficient shelf replenishment, and limited visibility into shopper behavior. Many stores, especially in Tier-2 and Tier-3 cities, also operate with constrained internet connectivity and require solutions that can function reliably without continuous cloud access. Recent advances in edge AI allow cameras and sensors to perform real-time analytics directly on local devices, enabling faster decisions, improved privacy,reduced bandwidth consumption, and uninterrupted operation even during connectivity outages. Hybrid and edge AI approaches are increasingly being adopted for real-time monitoring and decision support across multiple industries.

Description

Design an Intelligent Retail Analytics System that uses smart cameras and on-device AI to monitor retail operations in real time. The system should analyze shopper movement, inventory levels, and checkout queues without requiring constant cloud processing.The solution should automatically identify customer traffic patterns, measure dwell time in different store sections, detect out-of-stock products, monitor shelf compliance, and predict queue congestion before it impacts customer experience.AI inference should happen locally on the edge devices to enable low-latency decisions while preserving customer privacy and minimizing network dependency.The system should convert video streams into actionable business insights that help retailers improve operational efficiency, optimize staffing, increase product availability, and enhance customer satisfaction. Edge-based analytics can provide real-time intelligence while reducing dependence on cloud connectivity.

Expected Solution

The proposed solution should implement some or all of the following: