Discover innovative problem statements and build solutions for India's future
Search through curated problem statements from various ministries and domains. Use our intelligent search to find challenges that match your skills and interests.
238 results found
This problem focuses on developing a smart health surveillance system to detect and prevent water-borne disease outbreaks in rural Northeast India. The system will collect health data, use AI/ML for outbreak prediction, monitor water quality, and provide alerts to health officials and communities.
This problem focuses on developing a Smart Tourist Safety Monitoring & Incident Response System using AI, Geo-Fencing, and Blockchain. The system aims to provide secure digital IDs, real-time monitoring, and rapid response capabilities for tourists, enhancing their safety and security.
The problem focuses on developing low-cost, sustainable road infrastructure in the Northeastern Region of India to improve transportation of agricultural produce from remote farms. The solution involves using bamboo and recycled plastic to create prefabricated modular road panels that are durable and erosion-resistant.
The Indian government seeks an AI-driven solution to accurately identify cattle and buffalo breeds using images. This aims to improve data accuracy in the Bharat Pashudhan App, addressing the issue of breed misclassification by field workers. The solution should integrate with the app and provide breed suggestions.
The problem focuses on automating Animal Type Classification (ATC) for cattle and buffaloes using image analysis to improve the accuracy and efficiency of the process. The goal is to develop an AI-driven system that extracts body structure parameters from images and generates standardized scores, integrating with the existing Bharat Pashudhan App (BPA). This solution aims to enhance data quality and support the Rashtriya Gokul Mission (RGM) by the Government of India.
The problem is to develop a digital farm management portal to help pig and poultry farmers implement biosecurity measures. The portal should provide tools for risk assessment, training, compliance tracking, and real-time alerts, with a focus on accessibility and data analysis.
The problem involves developing a digital farm management portal to monitor antimicrobial usage (AMU) and ensure compliance with Maximum Residue Limits (MRL) in livestock. The portal aims to track drug usage, integrate with veterinary records, provide alerts, offer data visualization, and utilize secure technologies like blockchain.
This problem focuses on the lack of disaster preparedness education in Indian schools and colleges. The goal is to develop a digital platform to provide interactive modules, virtual drills, and real-time communication tools to improve safety during disasters.
The problem addresses the lack of engaging environmental education in Indian schools and colleges, which relies heavily on theoretical content. The goal is to develop a gamified platform to motivate students to adopt eco-friendly practices and understand environmental issues through interactive lessons and real-world tasks.
The problem addresses the lack of personalized, real-time crop advisory services for small and marginal farmers in India, leading to poor yields and environmental issues. The goal is to develop a multilingual AI-based mobile app providing location-specific advice, soil health recommendations, weather alerts, pest detection, and market price tracking.
This problem addresses the inefficiencies of manual attendance systems in educational institutions and the lack of structured activities for students during free periods. The goal is to develop an app that automates attendance tracking and provides personalized academic task suggestions, improving student productivity and aligning with their goals.
This problem focuses on automating attendance in rural schools in India, which currently rely on manual systems. The goal is to reduce errors, save time for teachers, and improve resource allocation by implementing a low-cost, user-friendly software or mobile application.
This problem focuses on the lack of real-time public transport tracking in small cities, leading to commuter inconvenience and reduced public transport usage. The goal is to develop a mobile or web platform providing real-time bus tracking and estimated arrival times, optimized for low-bandwidth environments.
Urban local bodies face challenges in waste segregation, leading to inefficiencies and environmental issues. The problem requires a system to monitor segregation and provide feedback to improve compliance and waste management.
The problem addresses the overuse of pesticides in agriculture, leading to environmental and health issues. The goal is to develop an intelligent system that detects plant infections and regulates pesticide application accordingly, promoting sustainable farming practices.
The problem involves automating student attendance tracking in colleges, which is currently done manually, leading to inefficiencies and errors. The goal is to develop a system that automates attendance, provides analytics for better academic planning, and works seamlessly in both in-person and online settings.
The problem is the lack of a centralized system for managing alumni data in educational institutions, leading to poor engagement and missed opportunities. This results in scattered data, limited communication, and difficulty in leveraging alumni networks for mentorship, fundraising, and other collaborations.
Rural areas near Nabha face healthcare challenges due to staff shortages, long travel distances, and poor infrastructure. The problem leads to worsened health outcomes and financial strain for residents. The goal is to improve healthcare delivery through telemedicine and digital health solutions.
The problem focuses on the lack of digital resources and infrastructure in rural schools in Nabha, leading to a digital literacy gap. This hinders students' access to modern educational content and essential digital skills, impacting their academic growth and future employability.
Indian Railways seeks to develop an indigenous, contactless Integrated Track Monitoring System (ITMS) to replace costly and limited foreign systems. The ITMS must comply with specific standards, measure track geometry, rail profiles, and component conditions, and provide real-time data processing and analysis. The project aims to promote self-reliance, reduce costs, and improve railway infrastructure monitoring.
The problem involves developing an AI-based system for laser-based QR code marking on track fittings (clips, pads, liners, and sleepers) for Indian Railways. The system aims to enable mobile scanning, integrate with existing portals, and provide AI-driven reports for quality monitoring and inventory management.
The problem focuses on optimizing train traffic control in Indian Railways to maximize section throughput and minimize travel time. It involves developing an AI-powered decision-support system to assist controllers in making real-time decisions for train precedence and crossings, considering various constraints and priorities.
The project aims to develop a software solution for Panchakarma patient management and therapy scheduling. The software will automate scheduling, provide notifications, and offer real-time therapy tracking and feedback mechanisms to improve efficiency and patient care.
The problem is to develop cloud-based software for Ayurvedic dietitians to create and manage patient-specific diet charts. The software should integrate Ayurvedic principles with modern nutritional metrics, offering features like a food database, automated diet chart generation, and patient management.
The problem involves developing an AI-enabled device, incorporating an electronic tongue and analytical techniques, for objective quality assessment of herbal samples. The device aims to classify herbs based on taste profiles and phytochemical composition, addressing issues of adulteration and standardization.
Develop an API to integrate NAMASTE and ICD-11 (TM2) into existing EMR systems in India, complying with EHR standards. The API should enable clinicians to record traditional medicine diagnoses and map them to ICD-11 codes for interoperability and analytics. The solution should include a terminology micro-service with auto-complete, translation, and FHIR bundle upload capabilities.
Develop a blockchain-based system for tracking Ayurvedic herbs from collection to the consumer, using geo-tagging and smart contracts to ensure quality, authenticity, and sustainability. The system aims to improve transparency, build consumer trust, and support ethical sourcing practices.
The problem focuses on creating an optimized timetable scheduler for higher education institutions to address inefficiencies in class scheduling. The solution should consider various parameters like classroom availability, faculty, and student preferences to maximize resource utilization and minimize conflicts. The expected solution is a web-based platform for authorized personnel to generate and manage timetables.
The problem is to create a digital platform to verify the authenticity of academic degrees and certificates in Jharkhand, combating the rise of fake credentials. The platform should use technologies like OCR, AI, and blockchain to cross-verify documents against institutional databases, ensuring security and scalability.
This project aims to develop an AI-driven mobile application that provides farmers with personalized crop recommendations. The system will integrate real-time data on soil properties, weather forecasts, market trends, and past crop rotation to suggest the most suitable crops, forecast yields, and promote sustainable agriculture.
This project aims to create a mobile and web-based system for citizens to report civic issues to the local government. The system will allow users to submit reports with photos, location data, and descriptions, while also providing a dashboard for government staff to manage and resolve these issues.
The Jharkhand government aims to develop a smart digital platform to boost eco and cultural tourism. The platform will address issues like lack of information, limited digital presence for local communities, and unorganized services by providing features such as AI-powered itinerary planning, blockchain-enabled transactions, and an integrated marketplace.
The problem focuses on developing an AI-based system to match PM Internship Scheme applicants with suitable opportunities. The system should consider skills, preferences, and affirmative action, aiming to improve selection efficiency. The expected solution is a functional prototype with an AI-based matchmaking engine and a front-end demonstration.
The problem is to develop an AI-based internship recommendation engine for the PM Internship Scheme to help candidates, especially those with limited digital literacy, find relevant internships. The system should provide 3-5 personalized suggestions based on candidate profiles and preferences.
The Ministry of Corporate Affairs needs an AI model to analyze comments on draft legislation submitted through an eConsultation module. The model should perform sentiment analysis, generate summaries, and create word clouds to help users efficiently understand the feedback.
The project aims to develop a low-cost, efficient, and portable sensor to detect microplastics in water sources. The sensor will use optical detection techniques and machine learning algorithms for real-time analysis. The solution should be field-deployable and provide data for pollution control and mitigation.
The project aims to develop a low-cost, camera-based system to automatically map beach sand grain size distribution. This system will use image processing and a GNSS/GPS receiver to classify beach types and monitor changes in sediment over time.
The problem involves creating a blockchain-based system for monitoring, reporting, and verifying blue carbon ecosystem restoration efforts in India. The system aims to ensure transparency and accuracy in carbon credit generation by utilizing blockchain technology and smart contracts.
The project aims to develop a platform for crowdsourced ocean hazard reporting and social media analytics. This platform will allow citizens to report observations, visualize data, and integrate social media feeds to understand hazard events.
The project aims to develop an AI-powered conversational interface, FloatChat, for exploring and visualizing oceanographic data from ARGO floats. This system will ingest NetCDF data, convert it into structured formats, and use a RAG pipeline with LLMs to translate natural language queries into database queries and generate visualizations.
CMLRE seeks an AI-enabled platform to integrate diverse marine datasets for ecosystem assessment and fisheries management. The platform will support data ingestion, analysis, and visualization, enabling data-driven decisions for conservation and sustainable resource utilization. The goal is to create a national marine data backbone.
The project aims to develop an AI-driven pipeline to analyze eDNA data from deep-sea samples to identify eukaryotic taxa and assess biodiversity. The current methods rely on databases that lack comprehensive sequences for deep-sea organisms, leading to misclassifications and underestimation of biodiversity. The proposed solution will minimize reliance on reference databases and reduce computational time.
The problem involves developing an embedded AI system for identifying and counting microscopic marine organisms from microscopy images. This system aims to automate the labor-intensive process of manual analysis, improving efficiency and accuracy in marine biodiversity assessments. The solution should handle challenges like overlapping organisms and illumination inconsistencies.
Develop an AI-powered platform to predict crop yields and provide actionable recommendations for farmers. The platform will use historical data, weather patterns, and soil metrics to optimize irrigation, fertilization, and pest control. The goal is to increase productivity for small-scale farmers through data-driven insights.
Develop a blockchain-based system to track agricultural produce from farm to consumer, ensuring transparency in pricing, quality, and origin. The platform should allow stakeholders to verify transactions and reduce exploitation in the supply chain.
Develop an IoT-enabled system using sensors and machine learning to automatically classify household waste. The system will integrate with municipal waste management for efficient collection and recycling. The expected outcome is a prototype device with high accuracy and a mobile app for monitoring and incentives.
Develop a drone-based system for delivering medical supplies and communication devices to remote areas during natural disasters. The drone will use AI for navigation and obstacle avoidance, and a mobile app will be developed for coordination.
Develop a gamified digital platform (mobile app or web) to improve STEM learning for students in rural schools (grades 6-12). The platform should feature interactive games, multilingual content, and offline access to address limited internet connectivity.
Develop a multilingual AI chatbot to educate rural and semi-urban populations about preventive healthcare, disease symptoms, and vaccination schedules. The chatbot will integrate with government health databases and provide real-time alerts for outbreaks.
Develop an AI-powered traffic management system to optimize signal timings and reduce urban congestion. The system will use real-time data from cameras and IoT sensors to predict and mitigate traffic bottlenecks, aiming to reduce commute times.
Develop an IoT-based monitoring system for solar or wind microgrids in rural areas. The system will provide real-time data on energy generation, storage, and consumption, alerting users to inefficiencies. The expected outcome is a hardware-software prototype improving microgrid efficiency by 15% with a mobile app for community operators.
Develop an augmented reality (AR) platform to digitize and preserve Indian cultural heritage sites, offering virtual tours with historical narratives. The platform should be accessible to users in rural areas with low-bandwidth access.
The problem focuses on improving onion storage technology to extend shelf life and reduce losses, addressing seasonal price volatility. The goal is to develop cost-effective storage solutions that manage temperature and humidity, potentially incorporating technological advancements.
The problem involves automating high-current short-circuit tests for Miniature Circuit Breakers (MCBs) to comply with IEC 60898-1:2015. Existing manual methods are inaccurate, time-consuming, and pose safety risks. The proposed solution is an automated machine with precise control and data acquisition for accurate and safe testing.
The project aims to develop an automated machine for preparing cable specimens for testing according to Indian standards. This machine will replace manual processes, reducing errors and improving the consistency of test results for cable safety and quality.
The problem focuses on finding a non-destructive method to test the purity of gold jewelry, replacing the current destructive fire assay method. The goal is to develop a method that is accurate, handles heterogeneous compositions, eliminates harmful emissions, and is suitable for regulatory and commercial use.
The problem involves developing an AI-powered automated compliance checker for e-commerce platforms to ensure adherence to Legal Metrology regulations. The system should extract text from product images, validate information against rules, and flag non-compliance issues. The solution should provide a dashboard for regulators to monitor violations and track compliance trends.
The problem focuses on developing a system to detect and prevent tampering in weighing and measuring instruments. The system should identify both physical and digital tampering attempts in real-time and alert relevant authorities. The solution may involve AI/ML, secure logging, and remote verification.
The problem focuses on students' lack of awareness regarding the difference between Aadhaar-linked and DBT-enabled bank accounts, leading to scholarship disbursement delays. The goal is to increase student awareness through various public awareness programs.
India faces a significant waste management challenge, with a large portion of waste untreated and posing environmental risks. The problem proposes solutions like mandatory citizen training, waste worker training, community participation, and digital monitoring systems to improve waste management.
The project aims to create a digital platform, Monastery360, to showcase the monasteries of Sikkim for tourism and cultural preservation. The platform will offer virtual tours, digital archives, interactive maps, and integration with local services. This initiative seeks to boost tourism, preserve cultural assets, and empower local communities.
The project aims to implement a smart irrigation system in Jorethang, South Sikkim, to address water scarcity and improve crop yields. The system will use sensors, a crop database, automated controls, and rainwater harvesting to provide efficient and sustainable irrigation. A mobile/web dashboard will allow farmers to monitor and control the system remotely.
The Kerala State Electricity Board Limited (KSEBL) needs a cost-effective solution to detect broken low-voltage AC distribution overhead conductors to prevent electrocution. The solution should isolate the fault and alert the section office. The problem stems from high earth resistance and low fault current, which prevents upstream fuses from detecting breaks.
The Kerala State Electricity Board Limited (KSEBL) is facing challenges with unbalanced loading and uneven voltage profiles in its distribution feeders due to the high penetration of rooftop solar PV systems. The problem requires a solution to dynamically reconfigure the network based on renewable energy injection and local demand scenarios.
The project involves developing a web/mobile application to assess the feasibility of rooftop rainwater harvesting and artificial recharge. Users will input details to receive personalized outputs, including feasibility checks, structure suggestions, and cost estimations. The application aims to promote groundwater conservation and sustainable water management.
The project aims to develop an AI-driven ChatBOT for the INGRES web application, which provides groundwater resource data. The ChatBOT will enable users to easily query data, access historical assessments, and obtain insights, improving accessibility and user engagement.
The problem involves developing an automated application to compute Heavy Metal Pollution Indices (HMPI) in groundwater. This tool aims to streamline calculations, reduce errors, and provide reliable outputs for stakeholders by integrating groundwater heavy metal concentration datasets with geo-coordinates.
This problem focuses on developing a mobile application to evaluate groundwater resources in real-time using data from Digital Water Level Recorders (DWLR) across India. The app aims to analyze water level fluctuations, estimate recharge, and provide real-time groundwater availability information to stakeholders.
The problem is to develop an AI-powered software platform for Life Cycle Assessments (LCAs) in the metals industry, focusing on circularity. The platform should allow users to input data, use AI/ML to predict environmental and circularity indicators, visualize circular flow opportunities, and generate actionable reports.
The problem is to design and prototype a secure, cross-platform data wiping application for electronic devices to address the e-waste crisis in India. The application should securely erase data, generate tamper-proof wipe certificates, and be user-friendly, promoting safe disposal and reuse of devices.
Develop an AI-based system to predict rockfalls in open-pit mines using multi-source data like DEMs, drone imagery, and geotechnical sensor data. The system should include a user-friendly dashboard with real-time risk maps, probability-based forecasts, and alert mechanisms.
The problem involves implementing a solar-powered dewatering system at a copper mining site to reduce operational costs, enhance reliability, and promote sustainability. The solution will utilize an OPEX model with a third-party vendor for installation, operation, and maintenance, incorporating hybrid backup for uninterrupted pumping.
The Sports Authority of India (SAI) needs a mobile-based platform to assess sports talent across India, especially in remote areas. The platform should use AI/ML to analyze videos of athletes performing fitness tests, providing instant feedback and securely submitting data.
Develop an AI-powered personal farming assistant for Kerala farmers to provide personalized agricultural advice. The assistant will use a conversational interface in Malayalam, track farmer activities, and offer proactive guidance based on local context.
The problem is to design a gamified digital platform to encourage sustainable farming practices among farmers. The platform should use interactive challenges, rewards, and community participation to educate and motivate farmers to adopt eco-friendly methods.
The project aims to develop an AI-powered advisory system for farmers in Kerala, enabling them to ask questions in Malayalam and receive instant, context-aware answers. The system will utilize natural language processing, image recognition, and a knowledge engine to provide tailored advice, incorporating location, crop, and season data.
The problem involves developing hardware to detect and prevent unauthorized use of electric fences. This aims to enhance security and potentially reduce associated risks.
The problem focuses on developing software to detect and shut down low-tension (LT) lines when they break, as an alternative to circuit breakers. The Kerala State Electricity Board Limited (KSEBL) seeks a software solution for disaster management.
Kochi Metro Rail Limited (KMRL) faces a document overload problem, hindering decision-making and operational efficiency. The challenge involves creating a system to condense, contextualize, and route critical information from various sources to relevant stakeholders.
Kochi Metro Rail Limited (KMRL) needs an AI-driven platform to optimize train induction planning and scheduling. The current manual process is inefficient and error-prone, leading to issues with punctuality, maintenance costs, and branding commitments. The platform should integrate data, enforce constraints, generate optimized schedules, and learn from historical data.
NATPAC needs a mobile app to collect travel data (trip number, origin, time, mode, destination, etc.) from users to improve transportation planning. The app should automatically detect some details and prompt users for others, storing the data on a server for analysis.
The Kerala government seeks a software solution to manage health records for migrant workers. This system aims to prevent disease transmission, improve public health surveillance, and support Sustainable Development Goals by ensuring equitable healthcare access.
The problem focuses on the lack of earthquake-resistant technology in dialysis infrastructure in India, which poses a risk to patients during seismic events. The goal is to develop a stabilization system to ensure continuous dialysis delivery, thereby safeguarding patient lives.
The problem focuses on reducing non-revenue water loss, improving water conservation awareness, and treating wastewater for domestic reuse. The Kerala government's water supply and sanitation agency is the organization involved.
The problem focuses on grey water management, reuse, and wetland management for water conservation. The project is initiated by the Government of Kerala and involves multiple departments.
The problem involves developing an AI-powered timetable generation system for higher education institutions, aligning with the NEP 2020 framework. The system should handle complex course structures, student preferences, faculty workload, and resource availability to automate timetable creation and prevent scheduling conflicts.
This problem focuses on developing a digital mental health support system for college students to address the increasing mental health issues and the lack of accessible support. The system will include AI-guided support, a booking system, a resource hub, a peer support platform, and an admin dashboard for data analysis.
The problem is the lack of a centralized digital platform to track and showcase student achievements in higher education institutions, leading to inefficiencies and limitations for students. The solution is to develop a mobile and web application that acts as a Smart Student Hub, managing student records and achievements.
The problem is the decline in student enrollment in government degree colleges due to a lack of awareness about career paths and educational opportunities. The proposed solution is a personalized digital platform that guides students on subject selection, college choices, and career options.
Students are tasked with redesigning a sports equipment using Fusion software, focusing on additive manufacturing techniques. They will utilize features like generative design and topology optimization to enhance functionality and efficiency for 3D printing. The project emphasizes learning about additive manufacturing and its applications in design, particularly in aerospace.
Students are tasked with using Fusion software to generate NC code for industrial components, requiring skills in CAD/CAM, G-code programming, and machining fundamentals. The project emphasizes creating viable, real-world solutions using CAM systems, which involve software, machinery, and post-processing.
The problem involves designing an autonomous machine for planting crops or weeding, focusing on lightweight and flexible design for easy transportation. The machine should incorporate Industry 4.0 applications like IoT and AI for smart agriculture, optimizing crop production.
Students are tasked with designing a 4-story commercial office building using Revit Architecture and Revit Structure, focusing on BIM model integration. The project involves creating a clash-free model for MEP design, quantity takeoff, and construction documentation, including 2D structural drawings and a 30-second walkthrough.
This problem focuses on developing an AI-powered platform for monitoring crop health, soil conditions, and pest risks using multispectral/hyperspectral imaging and sensor data. The platform integrates remote sensing and sensor data to provide timely insights, enabling proactive crop management. The solution involves using AI, ML, and DL techniques to analyze data and provide actionable alerts.
MathWorks seeks solutions to accelerate the creation of detailed digital twins of Indian road networks for realistic traffic simulations. The goal is to develop toolsets and workflows that incorporate features like potholes and erratic driver behavior, improving traffic management and infrastructure planning.
The problem focuses on creating a remote classroom solution for rural colleges with limited bandwidth. The solution should prioritize audio quality, compress visual content, and support interactive sessions while being accessible on entry-level smartphones and financially sustainable.
The problem involves creating an AI-based system to predict student drop-out risk by analyzing attendance, assessment scores, and fee payment data. The system should consolidate data from various spreadsheets, apply rule-based thresholds to identify at-risk students, and notify mentors for early intervention.
The problem involves creating an integrated student management system for a college using readily available cloud-based tools to streamline admissions, fee collection, hostel allocation, and examination records. The goal is to eliminate manual data entry, provide real-time institutional overview, and improve efficiency without the high cost of a full ERP suite.
The problem involves developing a multilingual chatbot for a college to answer student queries in multiple languages, including Hindi and a local language. The chatbot should deflect routine inquiries, freeing staff, and provide 24/7 information access. The solution must integrate with existing platforms, respect privacy, and be maintainable by student volunteers.
The problem involves developing computer programs to identify the design principles of Kolam art, a traditional Indian art form, and recreate the designs. The goal is to leverage computational methods to understand and replicate the mathematical and artistic aspects of Kolam patterns.
This project aims to develop an AI-powered FRA Atlas and a WebGIS-based Decision Support System (DSS) to improve the implementation of the Forest Rights Act (FRA). It involves digitizing legacy data, creating an interactive atlas, mapping assets using AI and satellite data, and building a DSS to recommend and layer government schemes for FRA holders.
This problem challenges students to develop innovative solutions for the Indian agricultural sector, focusing on enhancing agricultural practices and processing produce. The initiative is organized by AICTE and aims to leverage technology to address challenges in agriculture, food technology, and rural development.
The problem focuses on leveraging decentralized and distributed ledger technology (like blockchain) for innovative solutions, particularly in areas like cryptocurrencies and NFTs. The goal is to explore how this technology can transform various sectors.
The problem focuses on student innovation in clean and green technology, specifically addressing waste management and sanitation. Solutions should aim to improve waste segregation, disposal, and sanitation systems.
The problem focuses on generating innovative ideas to enhance fitness activities and promote physical well-being. The goal is to find solutions that can help individuals stay fit and improve their overall health through technological advancements.
The problem focuses on student innovation to showcase India's cultural heritage and traditions. The initiative is organized by AICTE and MIC-Student Innovation, falling under the theme of Heritage & Culture.
This problem focuses on fostering innovation in cutting-edge technology, particularly in healthcare and related fields. It highlights opportunities arising from shifts in healthcare trends and population growth.
This problem focuses on generating technology ideas for various tertiary sectors, including Hospitality, Financial Services, Entertainment, and Retail. The initiative is organized by AICTE and MIC-Student Innovation.
This problem focuses on generating innovative ideas for managing and generating renewable/sustainable energy sources more efficiently. The initiative is organized by AICTE and targets student innovation in the field of renewable energy.
The problem focuses on designing drones and robots to address challenges in India, such as medical emergencies and search and rescue. The initiative is led by AICTE and aims to foster student innovation in robotics and related hardware.
The problem focuses on student innovation using artificial intelligence to transform technology and gain insights from various sources. The goal is to intelligently use resources for advancements in technology and smart automation.
The problem focuses on developing intelligent devices to enhance the commutation sector. This initiative is part of a student innovation program under AICTE, focusing on smart vehicles.
The problem focuses on generating innovative solutions to improve the tourism industry, including hotels and travel services. The goal is to boost the current state of the tourism sector through new ideas and technologies.
Students are invited to submit innovative ideas to address challenges related to city resources, transport, and logistics. The problem focuses on hardware solutions within the theme of transportation and logistics.
This problem focuses on student innovation in disaster management, encompassing risk mitigation and planning across various phases of a disaster. The initiative is organized by AICTE and MIC-Student Innovation, with a hardware category focus.
The problem focuses on Smart Education, aiming to enhance learning through digital technologies. It seeks to make learning more effective, efficient, flexible, and comfortable for students.
This problem challenges students to design and develop innovative toys and games. The focus is on conceptualization and hardware development within the toys and games theme.
This problem focuses on student innovation for space-related travel and activities, such as spaceflight and exploration. The project is organized by AICTE and falls under the theme of Space Technology, specifically hardware.
The problem focuses on developing software solutions to enhance India's agricultural sector, including managing and processing agricultural produce. The initiative is organized by AICTE and targets student innovation.
The problem focuses on leveraging decentralized and distributed ledger technology (blockchain) for innovative solutions, particularly in areas like cryptocurrencies and NFTs. The goal is to explore how this technology can transform various sectors.
The problem focuses on student innovation in clean and green technology, specifically addressing waste management and sanitation. Solutions should aim to improve waste segregation, disposal, and sanitation systems.
The problem focuses on generating innovative ideas to enhance fitness activities and promote a healthy lifestyle. The goal is to find software solutions that can assist individuals in staying fit.
The problem focuses on generating innovative ideas that highlight India's cultural heritage and traditions. The initiative is organized by AICTE and MIC-Student Innovation, targeting student participation.
This problem focuses on fostering innovation in cutting-edge technology, particularly in healthcare and biotechnology, driven by evolving trends and population growth. The goal is to encourage student participation in developing innovative solutions within these sectors.
This problem focuses on generating technology ideas for various tertiary sectors, including Hospitality, Financial Services, Entertainment, and Retail. The initiative is organized by AICTE and MIC-Student Innovation.
This problem focuses on innovative ideas to improve the management and generation of renewable and sustainable energy sources. The goal is to find software-based solutions that enhance efficiency in this area.
The problem focuses on designing drones and robots to address challenges in India, such as medical emergencies and search and rescue. The initiative is led by AICTE and aims to foster student innovation in robotics and related software.
This problem focuses on student innovation in technology, specifically using AI to explore resources and gain insights for advancements. The goal is to leverage AI for smart automation and transformation.
The problem focuses on developing intelligent devices to enhance the commutation sector. This initiative is organized by AICTE and MIC-Student Innovation, with a theme centered around smart vehicles.
The problem focuses on developing innovative solutions to improve the tourism industry, including hotels and travel services. The goal is to boost the current situation of these industries.
Students are invited to submit innovative ideas to address challenges in city resources, transport, and logistics. The problem focuses on finding software-based solutions for urban issues.
This problem focuses on student innovation in disaster management, encompassing risk mitigation and planning before, during, and after disasters. The project is organized by AICTE and MIC-Student Innovation, and categorized under software.
The problem focuses on Smart Education, aiming to enhance learning through digital technologies. It seeks to make learning more effective, efficient, flexible, and comfortable for students.
This problem challenges students to design and develop innovative toys and games. The focus is on conceptualization and creation within the toys and games theme.
This problem focuses on student innovation for space-related travel and activities, such as spaceflight and exploration. The initiative is organized by AICTE and MIC-Student Innovation, with a theme centered around space technology.
The project aims to develop a real-time pressure measurement device, "Spinobar", for spinal orthoses to improve patient outcomes. The device will use a sensor array to provide non-invasive, real-time data on pressure distribution, enabling personalized orthotic adjustments and biomechanical research. The goal is to create a cost-effective and easy-to-use solution to overcome limitations of current methods.
This project aims to develop a smart, foldable axillary crutch using lightweight aluminum, incorporating IoT and sensor technology for enhanced mobility and rehabilitation. The crutch will feature shock absorption, ergonomic design, and a mobile app for real-time feedback and fall detection.
The project aims to develop an affordable and smart blind stick for visually impaired individuals, integrating sensors, GPS, and IoT. The stick will provide real-time obstacle detection, navigation, and an emergency SOS feature. The solution focuses on enhancing mobility, safety, and independence for the visually impaired.
The project aims to develop an affordable and functional upper limb prosthetic terminal device for partial hand amputees, particularly targeting low-income individuals in India. The device will utilize a push-button mechanism and servo motor-driven gear system for enhanced grip, focusing on cost-effectiveness, lightweight design, and ease of repair.
The problem focuses on the need for a compact and portable device to contour soft inserts for 3D-printed prosthetic sockets. Current methods rely on bulky equipment, hindering accessibility and efficiency, especially in resource-constrained settings. The goal is to create a handheld device that eliminates the need for traditional molds and equipment.
This project focuses on designing and developing a switch-controlled wrist-hand orthosis to assist individuals with impaired hand function. The device will use an ESP32 microprocessor and a servo motor to provide active control for grasping and releasing objects, improving independence in daily activities. The orthosis is intended to be low-cost, user-friendly, and portable.
The problem involves developing a mobile app for loan beneficiaries to upload geo-tagged photos/videos of assets purchased with loan funds, validated by AI. The app should allow offline functionality and remote review/approval by State Agency officers. The goal is to reduce fraud and improve efficiency in loan disbursement.
Develop an AI/ML-based credit scoring model for beneficiaries of concessional loans, integrating repayment behavior with income assessment using consumption-based metrics. The model should classify beneficiaries into risk bands and enable a direct digital lending module for eligible individuals. The goal is to ensure loans reach genuine beneficiaries, reduce processing time, and enable same-day loan sanctioning.
The project aims to identify infrastructure, amenity, and service gaps in Scheduled Caste (SC)-majority villages to facilitate their development into Adarsh Grams (Model Villages). The challenges include lack of real-time project status updates, difficulty in identifying gaps, and the absence of a data-driven mechanism for prioritizing interventions.
The problem focuses on improving beneficiary identification and tracking for the PM-AJAY grant program. It aims to address challenges like inclusion/exclusion errors, poor outcome tracking, and fragmented data through a digital mechanism. The goal is to enhance transparency, accountability, and improve livelihood opportunities for beneficiaries.
The problem involves the lack of a centralized mapping system for implementing and executing agencies within the PM-AJAY program, leading to delays and confusion. The goal is to streamline communication, improve accountability, and optimize fund flow through a digital repository and improved oversight.
The problem focuses on improving the Direct Benefit Transfer (DBT) process for victims of caste-based discrimination and atrocities under the PCR and PoA Acts. The goal is to create tech-enabled solutions to ensure accurate identification, real-time tracking, data security, transparency, and accessibility, while integrating with existing national databases.
The problem is to develop a mobile app that can transliterate street signs from any script in India to another. This will help people who are not familiar with a particular script to read road signs in different regions. The app aims to improve accessibility for travelers and local communities.
The problem involves developing software to generate the dimensions of ancient Indian astronomical instruments (yantras) for any given latitude and longitude in India. These instruments were used for timekeeping and tracking celestial objects, and the software aims to replicate their functionality based on location. The software will be useful for educational and research purposes.
The problem focuses on identifying mudras (hand gestures) in Indian dance forms using machine learning. The goal is to develop algorithms to recognize mudras from images or videos, expanding beyond existing work on Kathakali.
The problem involves developing a program to identify the type of Chandas (rhythm) in a given Shloka (verse) based on the arrangement of short and long syllables. This requires understanding the principles of Chandas Shastra, which involves binary numbers and combinatorial mathematics. The goal is to create a software solution for accurate identification.
The problem is the ineffectiveness of current anti-phishing systems against sophisticated and evolving cyber threats. The goal is to develop a real-time phishing detection and prevention framework using AI/ML, NLP, and graph-based analytics.
The problem focuses on the limitations of traditional firewalls in the face of advanced cyber threats. It proposes an AI-powered Next-Generation Firewall (NGFW) that integrates deep learning, NLP, and graph-based anomaly detection for intelligent security enforcement and Zero Trust implementation.
This problem focuses on mitigating national security risks posed by Large Language Models (LLMs) used in malicious information operations. It requires developing a framework to detect, analyze, and mitigate the misuse of LLMs, incorporating AI, machine learning, and cyber defense methodologies.
The problem involves identifying fake integrated circuits (ICs) in high-volume electronics production using an automated optical inspection (AOI) system. The system should capture and verify IC markings against OEM specifications to prevent counterfeit components from entering the production line, reducing delays and costs.
The problem involves designing an embedded system with redundant pathways and reconfigurable logic to autonomously detect and bypass faulty circuit sections in real-time. The goal is to create a self-healing computing platform that maintains uninterrupted operation without manual intervention. The solution should be demonstrated on an evaluation platform.
The problem focuses on developing a decentralized swarm maneuver algorithm for autonomous drones to neutralize adversarial drone swarms and protect ground assets. The algorithm must enable drones to collaboratively engage hostile drones using effective swarming maneuvers, prioritizing the protection of designated ground assets. The solution should be decentralized and robust, functioning even in communication-denied environments.
The problem focuses on managing large crowds at pilgrimage sites in Gujarat, addressing issues like overcrowding, safety, and inefficient resource allocation. The goal is to develop technology-driven solutions to improve the pilgrim experience, ensuring safety and convenience.
The problem focuses on developing smart solutions for the Sabarmati Riverfront and other urban water bodies to address challenges like water quality degradation, waste management, and safety concerns. The goal is to create innovative, technology-driven, and scalable solutions using IoT, AI, GIS, and data analytics.
The project aims to develop an AI and IoT-powered system to detect elephant movement in real-time, alert communities, and prevent human-elephant conflict in Chhattisgarh. The system will integrate various sensors, utilize AI/ML for detection and prediction, and provide alerts via mobile apps and dashboards.
The Ministry of Agriculture & Farmers Welfare (MoA&FW) aims to enhance farmer productivity through innovative technology solutions. The project falls under the Digital Agriculture Division and focuses on agriculture, food technology, and rural development.
The problem focuses on developing a ROS-based autonomous robot for lunar habitats. The robot should navigate, map, and monitor the environment, performing maintenance tasks in a simulated lunar environment. The goal is to reduce astronaut workload and ensure habitat safety.
The project aims to enhance OpenAI's GPT-OSS with multimodal vision capabilities, enabling it to process and reason over images. This involves aligning vision embeddings with the LLM, sourcing multimodal datasets, and achieving competitive performance within reasonable compute budgets. The solution will be extensible to ISRO EO data for applications like land cover classification and environmental monitoring.
This problem focuses on developing a deep learning pipeline to generate high-resolution thermal IR imagery by fusing thermal and optical data. The goal is to create super-resolved thermal maps that maintain temperature accuracy while capturing spatial details, addressing challenges like multi-sensor alignment, modality fusion, and thermal image super-resolution.
The challenge involves building a transformer-based Web Application Firewall (WAF) pipeline to detect anomalies in web traffic. Participants need to create a system that ingests logs, parses data, trains a transformer model, and performs real-time anomaly detection. The solution should support both batch and streaming log ingestion, continuous model updates, and demonstrate live detection of malicious requests.
The problem involves building an NLP-powered assistant for ELK-based SIEMs to enable conversational investigations and automated report generation. The assistant should translate natural language queries into SIEM queries, support multi-turn interactions, and present results in various formats. Key challenges include accurate entity mapping, handling ambiguity, and ensuring query efficiency.
Develop an Android application using AI to identify fish species, estimate their health and volume, and store the results with geotagging. The app should work offline in low-connectivity environments and provide instant verification of catch for various stakeholders.
Develop a multimodal AI assistant, MAITRI, to monitor the emotional and physical well-being of astronauts using audio-video inputs. The AI assistant should provide psychological support and adaptive conversations to maintain a balanced emotional state and report critical issues to the ground.
The challenge involves developing AI/ML models to predict time-varying errors in satellite clock and ephemeris parameters for GNSS satellites. Participants will use a seven-day dataset to predict errors at 15-minute intervals for an eighth day, focusing on accuracy across various prediction horizons.
The challenge is to develop a positioning algorithm using raw measurement data from Android mobile phones to enable safe autonomous navigation. The solution involves sharing navigation data between phones, detecting proximity and potential collisions, and generating warnings in real-time.
This project aims to develop a short-term forecasting model for ground-level ozone (O3) and nitrogen dioxide (NO2) in urban areas like Delhi, using satellite data and reanalysis data. The project involves preprocessing data, training machine learning models, and evaluating their performance against ground-based measurements.
The problem is to develop a secure email client application (QuMail) that integrates Quantum Key Distribution (QKD) to enhance email security. The application should be compatible with existing email servers and allow users to exchange emails with attachments securely over untrusted networks.
NaCCER, the R&D arm of CIL, needs an AI/ML-based system to automate the evaluation of research proposals. The current manual process is time-consuming and prone to errors. The system should assess novelty, perform financial checks, and generate an objective evaluation score.
The problem involves developing an AI-powered mobile application to improve safety in Indian mining operations. The app will provide role-based safety prompts, engaging safety videos, and a hazard reporting module to address safety violations and accidents.
The problem focuses on developing a smart system to monitor and ensure PPE compliance for mine workers in underground coal mines. The system should use technologies like computer vision or RFID to verify PPE in real-time, generate reports, and alert non-compliance. The solution aims to improve safety, reduce human error, and ensure legal compliance.
The problem is to develop an AI-enabled cyber incident and safety web portal for defense personnel, their families, and veterans. The portal should securely ingest complaints, analyze them using AI/ML, provide alerts and mitigation steps, and generate risk-ranked dashboards for CERT-Army.
The problem is to develop a secure communication platform for defense personnel and their families, operating over public networks. The platform should provide end-to-end encryption, controlled group membership, and prevent data leakage.
MDoNER needs an AI-powered system to assess the quality of Detailed Project Reports (DPRs) for infrastructure and socio-economic development projects. The system should use NLP and ML to analyze DPRs, identify gaps, predict risks, and provide a user-friendly dashboard for decision-makers.
The project aims to design a sustainable and low-cost geocell road system for landslide-prone rural areas in North East India. The solution should utilize locally available materials, withstand harsh conditions, and be easily deployable by local communities. The goal is to improve road stability, reduce costs, and promote rural connectivity.
The problem involves automating the tracking of hot metal and steel ladles in steel plants by automatically capturing their numbers and displaying their real-time location. This aims to replace manual tracking, improve efficiency, and enable better decision-making based on ladle usage data. The solution should automatically read ladle numbers, track locations, and display the data on a local server.
The problem involves the lack of real-time tilt position feedback for a Torpedo Ladle Car (TLC) used to transport hot metal, leading to potential spillage or overfilling. The goal is to provide operators with a real-time display of the TLC's tilt position for safer and more controlled pouring operations.
Develop an AI-driven diagnostic framework for EHV circuit breakers using Dynamic Contact Resistance Measurement (DCRM) data. The system will analyze DCRM signatures to detect abnormalities, predict potential faults, and provide maintenance recommendations. This aims to improve the reliability and safety of power transmission systems.
The problem involves developing an AI-powered software to analyze Frequency Response Analysis (FRA) data from power transformers to detect faults. The software needs to handle various data formats, perform automated analysis using machine learning, and provide actionable insights for maintenance.
The project aims to develop an AI/ML-enabled Digital Twin for EHV substations to improve monitoring, diagnostics, and optimization. This involves integrating diverse data sources, modeling asset behavior, and creating a visualization interface for operational insights.
POWERGRID needs a machine learning model to predict cost and timeline overruns for its projects. The model should identify key factors and dependencies impacting project completion. The goal is to avoid delays in projects of national importance.
The problem involves forecasting material demand for Power Grid projects to optimize supply chain planning, procurement, and inventory. The goal is to predict material quantities based on factors like budget, project locations, and taxes to minimize costs and avoid project delays. The solution should provide accurate demand forecasting for various materials.
The problem involves creating an AI-powered system to generate personalized Individual Development Plans (IDPs) for employees at Power Grid Corporation of India Limited (PGCIL). The system will analyze employee profiles and target role requirements to identify skill gaps and recommend tailored development activities.
POWERGRID needs a centralized, AI-powered helpdesk ticketing system to improve employee satisfaction by unifying ticket submission and automating resolution. The system should integrate with existing platforms, classify tickets using NLP, intelligently route them, and offer self-service options.
The problem involves designing a portable surveillance camera capable of operating in adverse weather conditions like fog, haze, and darkness. The camera should identify human-sized targets at significant distances, transmit live video, record data, and integrate with augmented reality displays.
The problem involves analyzing vast amounts of video data from surveillance systems to identify potential threats and extract meaningful insights. The goal is to develop an AI/ML-powered software solution that automates video analysis, identifies objects, and tracks movements with minimal human intervention.
The problem is to develop an AI-based tool for law enforcement to analyze UFDR reports, which contain large amounts of data from digital devices. The tool should allow investigators to use natural language queries to search the data, highlight key findings, and generate easy-to-understand reports, improving efficiency and reducing investigation time.
The problem is to develop an AI-powered system that generates personalized learning paths for vocational training in India, considering learners' profiles, career aspirations, and industry demands. The system should recommend courses, micro-credentials, and training opportunities, and continuously update recommendations based on learner progress and job market trends.
The problem involves developing a blockchain-based platform for issuing and verifying vocational skill certificates in India. This aims to address issues like forgery and delays, enhancing trust and interoperability within the vocational education system. The solution should provide secure, tamper-proof digital credentials and integrate with existing national platforms.
The problem involves designing and implementing an IoT and AI-based system to monitor vocational training equipment in real-time. The system aims to track equipment usage, health parameters, detect faults, enable predictive maintenance, and provide usage analytics to improve training quality and reduce costs.
The problem involves creating a Micro-Credential Aggregator Platform to consolidate and manage micro-credentials from various sources. This platform aims to provide a unified learner profile, enabling validation, stackability, and easy access for employers and institutions.
The problem is to develop an AI-powered multilingual content localization engine for vocational training materials in India. This engine should translate and adapt content into multiple Indian languages, considering cultural contexts and industry-specific terminology.
This project aims to develop a robotic floating platform equipped with a hyperspectral radiometer to monitor chlorophyll concentration and detect plastic pollution in aquatic environments. The platform will collect spectral data to estimate chlorophyll-a levels and identify plastic debris, providing real-time data for water quality monitoring and pollution mapping.
Develop a cybersecurity framework for digital banking in rural areas, focusing on fraud detection and user authentication. The solution should be lightweight and compatible with low-end devices and limited internet connectivity.
The problem focuses on replacing conventional pneumatic Simba drills with Electric Hydraulic System (EHS) based drills in underground mining. The EHS drills aim to improve drilling speed, safety, energy efficiency, and compatibility with automation compared to the older technology.
The problem is the failure of internship systems in colleges, particularly under the New Education Policy (NEP) 2020. The proposed solution is a student-industry-college tie-up to develop an app to streamline the internship process.
Develop an AI/ML-based decision support system to optimize rake formation strategies for SAIL, focusing on movements from Bokaro Steel Plant. The system should dynamically form optimal rake plans, minimize logistics costs, and ensure efficient material allocation.
The problem involves optimizing vessel scheduling and port-plant logistics for a steel supply chain to minimize transportation costs. The solution requires an AI-powered system to handle various constraints, predict delays, and integrate data from existing sources.
The problem focuses on improving energy efficiency in iron ore mining operations, specifically in the energy-intensive processes of crushing and grinding. The goal is to reduce energy consumption, operational costs, and environmental impact through AI-driven optimization, process simulation, and renewable energy integration.
The problem involves developing a Virtual Reality (VR) simulator to train National Disaster Response Force (NDRF) personnel in handling chemical disasters. The simulator should replicate realistic environments and allow trainees to practice critical skills without real-world danger. The system needs to support multi-user training, performance evaluation, and scenario customization.
The problem requires a mobile or simulation-based tool to assess the structural stability of collapsed buildings during disaster scenarios. The tool should help determine safe entry points, estimate load-bearing capacity, and identify hazards. It needs to support building details input, real-time stability estimation, GIS integration, hazard flagging, photo/video upload, and offline functionality.
The problem involves developing a wearable device for real-time monitoring of vital signs, gas exposure, and fatigue in rescue operations. The device should transmit data wirelessly, provide alerts, and store data for post-operation analysis. The goal is to improve responder safety and enable timely medical intervention in hazardous environments.
The problem focuses on developing a radar-based system to detect living persons trapped under rubble after disasters. The system should be portable, effective in various conditions, and capable of detecting vital signs through debris. The goal is to create a device that aids rescue operations by providing rapid and accurate life detection.
The project aims to design and develop a low-cost, decentralized smart air purification and monitoring system for the Delhi-NCR region. The system should measure air pollutants, identify pollution sources, and provide localized air purification using IoT-enabled adaptive filters.
The project aims to develop a software platform to identify pollution sources in Delhi-NCR, forecast air quality, and provide a policy dashboard. The platform will use AI/ML, satellite data, and sensor data to offer insights to citizens and policymakers. The goal is to enable evidence-based interventions and promote citizen engagement.
The problem involves developing a Cognitive Opportunistic LEO-PNT receiver system to utilize signals of opportunity from LEO satellites for accurate positioning, navigation, and timing services. The system aims to overcome vulnerabilities of traditional PNT systems by leveraging signals from various mega-constellations and compensating for errors.
The problem focuses on developing a low-cost, accessible screening tool for early detection of neurological conditions like Parkinson's and Alzheimer's. The tool should be non-invasive, easy to use by primary healthcare workers, and function in resource-limited settings. The solution should provide actionable outputs for referral to specialists.
The problem involves developing a mobile application for ASHA workers in rural India to manage electronic health records (EHRs) in areas with limited internet connectivity. The app should function offline, store data securely, sync automatically when internet is available, and support local languages and voice input.
The problem involves developing a digital solution to trace contacts and screen for Multi-Drug Resistant (MDR) pathogens in hospitals. The system should leverage hospital data, patient interactions, and real-time inputs to identify potential outbreaks early and suggest containment protocols.
The problem involves creating a VR experience with eye-tracking to capture customer reactions to EV designs. The goal is to gather data on gaze patterns and attention to improve ergonomics, aesthetics, and user experience. Students are expected to design a VR prototype that simulates EV models and generates heatmaps and analytics.
The problem involves creating a digital twin for an urban area to simulate COâ‚‚ emissions, dispersion, and capture methods. The goal is to design a software prototype that models COâ‚‚ flow, integrates sensor data, and evaluates different capture strategies to support urban planning.
The problem focuses on developing high-efficiency electric motors that do not rely on rare-earth magnets. The goal is to create a motor with comparable or superior performance using alternative materials and designs. Students are expected to design and validate a prototype motor concept.
The problem focuses on developing an indigenous, cost-effective stealth coating for defense assets to reduce radar cross-section and infrared signatures. The solution should be durable, weather-resistant, and field-deployable, with students expected to propose a lab-scale formulation and demonstrate its effectiveness.
The problem focuses on designing a cost-effective, lightweight, and safe hydrogen storage cylinder to promote the adoption of hydrogen as a clean energy source. The solution should utilize new materials or fabrication techniques to reduce costs and meet safety standards.
The problem focuses on developing an AI-based screening tool to detect early signs of dementia. The tool should analyze speech, behavior, and cognitive patterns, providing risk scores for clinical referral. The expected solution is a mobile or web-based cognitive screening app.
This problem focuses on developing a real-time early warning system for cloudbursts in hilly regions. The system should utilize sensor networks, weather radar data, and AI to predict rainfall anomalies and alert local authorities and residents.
The problem involves creating a system to collect and categorize cryptocurrency addresses from various online sources, associating them with suspect entities. The system should scrape the internet, store the data, and provide an analytical front-end for querying the data and exporting results.
The problem focuses on developing a system to identify URL-based cyberattacks using IP data. The system should detect various attack types, visualize results, and allow data export. It should also ingest external PCAP data for attack identification.
The problem focuses on identifying and preventing data exfiltration attacks using Virtual Network Computing (VNC) servers, specifically TigerVNC and RealVNC. The goal is to develop a system that simulates various data exfiltration scenarios and suggests defense mechanisms to detect and prevent such attacks.
The problem requires building a multimodal Retrieval-Augmented Generation (RAG) system that can ingest, index, and query diverse data formats like DOC, PDF, images, and audio recordings. The system should support natural language queries and generate grounded summaries, integrating retrieved context via an LLM. The solution should provide a unified query interface and enable cross-format search and citation transparency.
The problem involves developing a software tool to automatically detect and visualize open crust mining activity from satellite imagery. The tool should identify mining areas, including those outside defined boundaries, calculate mining depth and volume, and generate reports. The solution requires 3D visualization and integration with an interactive mapping platform.
The problem is to develop an automated Vulnerability Assessment and Penetration Testing tool specifically for CCTV cameras and DVRs. The tool should scan for vulnerabilities, simulate attacks, and use machine learning for anomaly detection and vulnerability prediction.
Develop a centralized vulnerability detection system with a web GUI that integrates various scanning tools. The system should aggregate scan results, correlate them with threat intelligence, and provide a RAG-based chatbot for natural language queries on vulnerabilities.
The problem requires developing a portable log analysis tool for isolated networks to monitor cybersecurity events. The tool should collect, parse, and analyze logs from various sources without relying on external services. Key features include portability, multi-source log collection, log parsing, analysis, a user interface, offline functionality, security, and reporting.
The project aims to develop an application that obfuscates object files generated from C and C++ code using LLVM. The tool should generate obfuscated binaries for Windows and Linux, making them difficult to reverse engineer, and provide a report detailing the obfuscation process.
The problem is the manual, time-consuming, and error-prone process of hardening operating systems (Windows, Ubuntu, CentOS) to meet security standards. The objective is to develop an automated, cross-platform security hardening tool that assesses, enforces, and reports compliance.
The problem involves developing threat rules within an ELK stack (Elasticsearch, Logstash, Kibana) to detect Advanced Persistent Threats (APTs). This requires analyzing log data from various sources to identify suspicious activities indicative of APT attacks, using APT samples for realistic data generation.
The problem focuses on developing an AI/ML-based framework to automatically identify and analyze cryptographic primitives and protocols within firmware binaries across various architectures. The goal is to create a system that can detect known and proprietary crypto implementations, classify crypto types, and identify protocol patterns, even in black-box firmware.
The problem involves developing an AI/ML-based software to translate printed text from Nepalese and Sinhalese languages into English. This aims to make literature accessible to a wider audience, overcoming the limitations of manual translation.
The problem focuses on empowering Gram Panchayats to manage rural piped water supply systems' daily operations and maintenance using low-cost digital tools. The goal is to improve the functionality, efficiency, and sustainability of these systems by providing tools for monitoring, preventive maintenance, and water quality checks.
The problem focuses on developing an Audio Language Model (ALM) that can understand both speech and non-speech audio signals, along with their relationships. The goal is to create a model capable of speech recognition, audio event detection, speaker diarization, and paralinguistic analysis, using a dataset that includes Asian languages.
The problem involves developing an AI-driven system to enhance underwater images for improved maritime security. The system should address issues like low visibility and color distortion, enabling better threat detection and reconnaissance in challenging underwater environments. The solution should be deployable on edge devices and provide real-time image enhancement.
The problem focuses on identifying internal threats within an organization using User and Entity Behavior Analytics (UEBA). It highlights the limitations of traditional security tools and the need for a solution that leverages machine learning to detect anomalies in user behavior.
DRDO needs an automated platform to gather and analyze technology intelligence, forecast trends, and aid strategic decision-making. The current manual methods are time-consuming and produce outdated insights. The platform should integrate data from various sources, provide real-time updates, and generate forecasts.
Learn how to win Smart India Hackathon 2025 with our comprehensive guide! This platform provides everything you need to know about participating in SIH, finding the correct problem statements, and building winning solutions.
Finding the right problem statement is crucial for SIH success. Here's how to find correct problem statement for SIH: 1) Analyze your team's technical skills and expertise, 2) Review problem difficulty levels using our filters, 3) Choose domains that match your interests (AI, healthcare, fintech, etc.), 4) Consider the feasibility of implementation within the hackathon timeline, 5) Look for problems with clear evaluation criteria and measurable outcomes.
Complete guide on how to participate in SIH 2025: 1) Form a team of 6 members (students + mentor), 2) Register on the official SIH portal during registration period, 3) Browse and select problem statements using our platform, 4) Submit your innovative solution proposal, 5) Prepare for internal hackathon at your institute, 6) Qualify for the grand finale through regional selection.
Top SIH winning tips from past champions: 1) Choose problems aligned with your technical expertise, 2) Focus on user experience and practical implementation, 3) Prepare a compelling presentation and demo, 4) Research the problem domain thoroughly, 5) Build a minimum viable product (MVP), 6) Practice your pitch multiple times, 7) Show real-world impact and scalability, 8) Demonstrate technical innovation and creativity.
Expert guide on how to choose SIH problem statement: 1) Assess problem complexity vs. team capabilities, 2) Use our difficulty filters (Easy, Medium, Hard), 3) Consider available technology stack and resources, 4) Evaluate market potential and social impact, 5) Check if similar solutions already exist, 6) Ensure problem aligns with your career goals, 7) Review past winning solutions for insights.
How to prepare for SIH 2025: 1) Start early with problem analysis, 2) Build prototypes and test concepts, 3) Create detailed project timeline, 4) Prepare backup solutions for technical challenges, 5) Practice presentation skills, 6) Study judging criteria and evaluation parameters, 7) Network with mentors and industry experts, 8) Keep updated with latest technology trends.
SIH team formation tips for success: 1) Include diverse skill sets (frontend, backend, AI/ML, design, business), 2) Choose committed and reliable team members, 3) Select an experienced mentor from industry or academia, 4) Ensure good communication and collaboration, 5) Define clear roles and responsibilities, 6) Practice working together on smaller projects first.
Steps to build winning SIH solutions: 1) Conduct thorough problem research and user analysis, 2) Design user-centric and innovative solutions, 3) Choose appropriate technology stack, 4) Focus on scalability and real-world implementation, 5) Create compelling demos and presentations, 6) Prepare for technical questions from judges, 7) Document your solution architecture and business model.
How to choose technology for SIH: 1) Match technology with problem requirements, 2) Consider team expertise and learning curve, 3) Evaluate development time and complexity, 4) Check for available APIs and resources, 5) Ensure technology supports scalability, 6) Consider deployment and maintenance aspects, 7) Stay updated with trending technologies like AI, blockchain, IoT.
Understanding SIH judging criteria: 1) Innovation and creativity (30%), 2) Technical implementation and complexity (25%), 3) Social impact and feasibility (25%), 4) Presentation and demonstration (20%). Presentation tips: Keep it simple, focus on problem-solution fit, demonstrate live working prototype, explain technical architecture clearly, highlight unique features and benefits.