Description Micro-businesses in India often miss critical market shifts due to lack of timely insights. They need a simple platform that aggregates global trends in customer preferences, supply disruptions, and regulations, presenting them as clear, actionable recommendations—preferably in local languages. Expected Solution - Ingest data from freely available sources (e.g., open APIs, news aggregators, mock scrapers). - Use basic analytics to highlight emerging trends (e.g., spikes in demand, supply bottlenecks). - Build an intuitive, multilingual interface that displays alerts, suggestions, and visual insights. - Explain predictions by showing underlying data and noting any biases or limitations. Deliverables Working prototype, short demo video, documentation. Implementation Note for Students Use open or locally simulated data to demonstrate trend detection. You are encouraged to design your own lightweight pipelines (like scrapers or dataset generators) rather than relying on paid APIs. Focus strongly on the recommendation logic, explainability, and multilingual support. Innovative visualization and clarity of insights will set your solution apart. Additional Notes Ensure that any AI or prediction components include brief notes on potential bias and limitations for transparency. Description Many Indian communities lack timely, hyperlocal disaster predictions, leading to loss of lives and resources. A community-driven AI platform is needed to provide early alerts for floods, power cuts, or urban fires, using both open data and citizen inputs, focusing on hyperlocal areas in India. Expected Solution - Collect and analyze weather data from free/open APIs (OpenWeatherMap, WeatherAPI, NASA POWER) and Indian sources (IMD Open Data, Bhuvan, India Water Portal). Students may simulate local sensor inputs using mock datasets. - Simulate community-reported disaster inputs (floods, power outages, urban fires) using mock datasets, Google Forms, or a simple input interface. - Optional: generate simulated sensor data (rainfall, temperature, water levels) in CSV/JSON to feed the AI model or dashboard for alerts. - Verify citizen-reported inputs before publishing alerts (e.g., cross-check with weather or sensor data). - Provide multilingual notifications and offline fallback support for low-connectivity areas. - Ensure explainability in AI outputs to build trust. Deliverables - Working prototype, short demo video,documentation. Implementation Note for Students - Use free weather APIs combined with mock citizen or sensor data to demonstrate disaster prediction. - Focus on simple, clear alert mechanisms that communities can easily understand. - Innovate in crowdsourcing citizen inputs and presenting localized alerts. Additional Notes Emphasis should be on local relevance, low-cost scalability, and community trust-building. Description AI bias can negatively impact decisions in finance, healthcare, recruitment, and public services. There is a need for a tool that audits AI models or APIs for fairness across multiple domains and provides actionable mitigation strategies. Expected Solution - Accept inputs such as user’s model, dataset, or API endpoint. - Analyze results for potential bias across demographics, sectors, or contexts. - Generate fairness scores, reports, and recommendations. - Offer explainable outputs to promote trust and ethical use. Deliverables Working prototype, short demo video, documentation. Implementation Note for Students Start with open datasets or mock datasets to demonstrate fairness auditing. Use simple statistical checks or open-source fairness libraries for initial bias detection. Focus on presenting bias findings clearly and suggesting simple, practical mitigation strategies. Innovative visualizations and cross-domain adaptability will strengthen your solution. Additional Notes Students should prioritize explainability and ease of use over complexity. The solution should be designed as a reusable tool for multiple sectors. Description With increasing use of AI tools, users may experience reduced mental agility, memory retention, focus, and critical thinking. A gamified solution can help maintain cognitive health while interacting with AI systems. Expected Solution - Develop AI-based games targeting memory, focus, critical thinking, problem-solving, and emotional intelligence. - Provide adaptive difficulty based on user performance. - Offer analytics on cognitive improvement over time. - Ensure engaging UX with local language support. Deliverables - Prototype web/mobile game. - Demo video showing gameplay and analytics. - Documentation. Implementation Note for Students Students can use mock user data or simulated AI usage patterns to demonstrate effectiveness. Emphasis should be on game mechanics, cognitive challenge design, and progress tracking. Additional Notes Focus on social impact, user engagement, and measurable cognitive improvement metrics. Description AI-generated text is increasingly used for misinformation, plagiarism, or automated content creation. Detecting AI-generated content is critical for authenticity, education, and regulatory compliance. Expected Solution - Build a system to identify AI-generated text content. - Provide confidence scores and highlight suspicious sections. - Support multiple languages and content types (articles, essays, social media posts). - Optionally suggest verification or rewriting mechanisms. Deliverables - Prototype detection tool (web/app). - Demo video showing sample detections. - Documentation. Implementation Note for Students Use open-source AI text datasets or simulated AI-generated content for demonstration. Focus on model accuracy, UI clarity, and reporting insights. Additional Notes High relevance for educational institutions, media platforms, and online communities. Description Farmers often suffer unpredictable losses due to microclimate changes, pest outbreaks, and market volatility. There is a need for a platform that can forecast risks and provide timely, actionable advisories to reduce crop loss. Expected Solution - Merge Indian open datasets such as Bhuvan satellite imagery, IMD weather data, and Agmarknet mandi price data. Students can simulate datasets for farm/pest/weather data locally to demonstrate risk detection. - Highlight risks like pest threats, weather extremes, or sudden market price drops. - Provide farmer-friendly advisories in local languages. - Support offline accessibility for rural areas with limited internet. Deliverables - Working prototype - Short demo video - Documentation Implementation Note for Students - You can use mock datasets or free Indian open data to simulate crop risks. - Focus on creating a simple dashboard with clear advisories rather than complex analytics. - Local language support, offline capability, and easy visualizations will make the solution highly impactful. Additional Notes AI is optional — students may use basic analytics or rule-based approaches. Emphasis should be on usability for rural farmers and scalability for different crops and regions. Description Fake organic labels undermine consumer trust and create unfair practices in the food market. A scalable solution is needed to validate the authenticity of organic claims using public datasets and community inputs. Expected Solution - Build a crowdsourced platform for verifying organic product claims. - Use public datasets, FSSAI reports, and community inputs to validate organic claims. Students can simulate certification data or use sample CSVs from government open data. Real API integration is optional. - Use fraud detection algorithms to spot suspicious patterns. - Provide GIS mapping of certified vs. non-certified producers. Deliverables Working prototype, short demo video, documentation. Implementation Note for Students Start with mock data or publicly available datasets to simulate organic product claims. Use basic pattern-detection techniques or open-source ML libraries to validate authenticity. Focus on building a clear reporting and mapping interface to showcase trust and transparency. Additional Notes The emphasis should be on trust-building, ease of reporting, and scalability for different products and regions. Description India loses billions due to food wastage during transport and warehousing. Real-time visibility of loss events is minimal, making it hard for stakeholders to take preventive action. A platform is needed to track and visualize these leakages and recommend interventions. Expected Solution - Build a tool that maps food loss events along the supply chain. - Integrate logistics/transport APIs or simulated datasets. - Provide analytics dashboards for monitoring and prevention. - Support offline reporting modules for field-level users. Deliverables Working prototype, short demo video, documentation. Implementation Note for Students Use sample logistics datasets or simulate data to map leakage points. Focus on visualization and identifying preventive measures rather than complex backend systems. Clear dashboards and actionable recommendations will make your solution stand out. Additional Notes Integration with IoT devices is optional but not mandatory. Priority should be given to usability, scalability, and low-cost adaptability for small farmers and supply chain partners. Description Indian cities are increasingly facing intense heatwaves, affecting public health, worker productivity, and overall urban livability. However, most cities lack localized, real-time tools to understand and respond to heat stress at a granular level (ward or street). A platform is needed that combines open datasets, sensor data, and citizen reports to generate actionable insights for communities and decision-makers. Expected Solution - Integrate weather and satellite APIs with citizen-sourced data (mobile/web reporting of hotspots). - Create dynamic maps showing heat stress levels across city zones in real time. - Suggest risk reduction measures (hydration points, shaded areas, work-shift adjustments). - Enable multilingual access for inclusivity. Deliverables - Working prototype platform (web or mobile). - Live demo video explaining the workflow. - Documentation (system design, data sources, limitations). Implementation Note for Students You can use freely available weather APIs (like OpenWeather, NASA heat index data) combined with mock citizen inputs instead of costly or unavailable live sensor data. Focus on building a simple visual heat map dashboard and recommendations engine. Even small datasets are sufficient for a meaningful demo. Prioritize clarity of visualization, multilingual support, and easy user interaction. Additional Notes This problem has strong social impact and is hackathon-friendly. Students are not expected to build hardware sensors; simulated or small-scale input data is enough. Teams should focus on innovation in data visualization, inclusivity, and actionable recommendations rather than technical complexity. Description Despite increasing focus on recycling and the circular economy, data about waste flows, collection points, and recycling options is fragmented and poorly accessible. Citizens and companies often do not know how or where to reuse, recycle, or safely dispose materials. A localized digital solution is needed to connect stakeholders and encourage active participation in waste circularity. Expected Solution - Build a dashboard that tracks waste flows and provides nearby recycling or reuse options. - Integrate municipal open data, NGO initiatives, and crowdsourced information. - Provide gamified features (rewards, leaderboards) to encourage citizen and student participation. - Show clear environmental impact metrics (waste diverted, CO₂ saved, etc.). Deliverables - Web or mobile dashboard prototype. - Demo video showing sample use case. - Documentation (data sources, design flow, limitations). Implementation Note for Students You can simulate municipal/NGO data and crowd inputs rather than relying on official APIs. Focus on user-friendly dashboards, gamification elements, and impact metrics. Even a small dataset with mock entries is enough to demonstrate the value. Creativity in engagement and visualization is key here. Additional Notes This problem has huge real-life applicability and very little existing implementation in Indian cities. Teams should emphasize practicality and inclusivity, ensuring that the tool works in regional languages and low-data environments. Description Urban water cuts, theft, and unequal distribution are common in Indian cities, but citizens lack visibility into how water is being supplied, consumed, or lost. There is no easy mechanism for communities to hold utilities accountable. A grievance-driven digital platform is needed to combine citizen reports with supply data for better transparency. Expected Solution - Build a reporting platform where citizens can log water issues (shortage, theft, leaks). - Combine inputs with open water supply/consumption data to generate analytics dashboards. - Provide multilingual interfaces and anonymous reporting options. - Offer clear visualization of water distribution and accountability reports. Deliverables - Functional prototype (mobile/web). - Demo video with sample reports. - Documentation (workflow, datasets, mock inputs). Implementation Note for Students You may simulate water supply data and combine it with mock citizen reports for demonstration. Focus on easy reporting workflows, simple analytics dashboards, and strong data visualization. Innovation lies in making the system transparent and community-driven, not in large-scale integrations. Additional Notes This problem is highly novel and socially impactful. It empowers communities while being hackathon-feasible with mock data. Students should emphasize clarity, transparency, and inclusivity in their solutions. Description Millions of first-time users struggle with onboarding onto DPI platforms such as UPI, ONDC, and ABDM because of language barriers, digital literacy gaps, and complex KYC/documentation flows. A supportive and multilingual onboarding solution can bridge this gap and make DPI more inclusive. This is for first-time users to get started with DPI platforms easily. Expected Solution - Build a multilingual guided onboarding tool for first-time DPI users. - Provide step-by-step KYC assistance, account linking, and usage tutorials. - Integrate voice/chatbot support in multiple Indian languages. - Allow offline self-paced guides for rural/low-connectivity areas. Deliverables - Prototype of onboarding tool (mobile/web). - Demo video showing user journey. - Documentation with flow diagrams and mock integrations. Implementation Note for Students You can simulate DPI APIs using sandbox/mock data—real KYC/UPI integrations are not required. Focus on user experience, multilingual support, and simplicity. Even a working demo with dummy data flows is sufficient to showcase innovation. Additional Notes This problem is practical and impactful because it directly contributes to DPI adoption in rural and semi-urban India. Solutions should emphasize inclusivity, ease of use, and cultural fit. Description Users often face difficulties with UPI, ONDC, and ABDM transactions and onboarding, but support is fragmented across multiple channels. This creates frustration and reduces trust in DPI platforms. A unified troubleshooting assistant can simplify issue resolution and improve user satisfaction. This is for existing users to resolve issues with DPI transactions efficiently. Expected Solution - Build a virtual assistant that can handle common DPI issues like failed UPI transactions, ONDC order errors, or ABDM linking problems. - Provide multilingual, conversational support (chat/voice). - Offer troubleshooting tips, FAQs, and guided workflows. - Ensure privacy compliance and local device data storage where possible. Deliverables - Prototype chatbot/assistant demo. - Short demo video with common use cases. - Documentation of features, workflows, and limitations. Implementation Note for Students You can use mock user cases and sandbox flows to show functionality. Focus on conversational design, multilingual support, and clear troubleshooting steps rather than complex integrations. Innovation lies in how well the assistant resolves user pain points. Additional Notes This problem emphasizes usability and trust-building. A simple prototype with realistic demo scenarios can create strong impact in the hackathon setting. Description Most users do not know how their personal and transactional data is shared across DPI platforms. Lack of transparency reduces trust in digital adoption. A tool that visualizes and tracks how user data flows, where it is shared, and for what purpose can improve awareness and accountability. Expected Solution - Build a dashboard that shows users their data-sharing history across platforms like UPI, ONDC, or ABDM. - Provide clear visualizations of what data was accessed, when, and by whom. - Enable users to view permissions, revoke consent, or adjust data-sharing settings. - Ensure privacy-first design with strong authentication. Deliverables - Functional prototype (web/mobile). - Demo video with sample data flows. - Documentation explaining design logic and mock datasets. Implementation Note for Students You can simulate data-sharing events using mock logs. The key focus should be on visual clarity, user empowerment, and actionable controls (like revoke consent). Innovation lies in creating intuitive transparency reports and visualizations. Additional Notes This is a novel and socially relevant problem with high future scope. Even a mock demo of data flows can be powerful in raising awareness about privacy and trust in DPI. Description Patients with chronic conditions (like diabetes, hypertension, heart disease) often struggle to follow prescribed routines in telemedicine setups. Lack of reminders, feedback, and tracking reduces treatment effectiveness. A digital compliance coach can improve adherence and support better health outcomes. Expected Solution - Create a mobile/web app that reminds patients of medicines, check-ups, and lifestyle tasks. - Integrate with basic IoT devices (wearables, BP machines, glucometers) or simulate data. - Provide gamified progress tracking (badges, streaks, reminders). - Share progress securely with healthcare providers via ABDM sandbox APIs. Deliverables - Prototype app demo. - Short video showcasing patient journey. - Documentation of features, ABDM sandbox use, and limitations. Implementation Note for Students Students can simulate health data instead of using real medical devices. Focus on user experience, gamification, and secure sharing rather than heavy integrations. Even a mock IoT data generator is sufficient. Additional Notes A highly impactful project that aligns with Digital Health Mission priorities. Judges will look for simplicity, patient usability, and innovation in adherence strategies. Description Emergency rooms in India face overcrowding and delays in triage (categorizing patients based on urgency). This leads to critical delays in treatment. A real-time triage solution can help prioritize patients quickly and efficiently. Expected Solution - Build a triage assistant that uses basic patient inputs (symptoms, vitals, history) to categorize urgency. - Multilingual, nurse-friendly UI with minimal clicks. - Provide instant risk classification (Critical, Urgent, Non-Urgent). - Secure backend to store and retrieve case history. Deliverables - Prototype triage tool (mobile/web). - Demo video with sample emergency cases. - Documentation of workflows and logic used. Implementation Note for Students Students can simulate patient inputs and demonstrate the triage classification logic. Focus on speed, clarity, and UI friendliness. No real-time hospital integration is required. Additional Notes This is a novel solution for Indian ERs where delays are common. The project should balance usability + accuracy, even with simple algorithms. Description Outbreaks like dengue, flu, or local epidemics often catch communities unprepared due to late information. A proactive forecasting and awareness platform can help people and health workers take preventive measures early. Expected Solution - Use health datasets, news feeds, and citizen reports to forecast potential outbreaks. - Send alerts in vernacular languages to citizens and health workers. - Provide simple visualizations of outbreak hotspots and spread scenarios. - Enable community participation (crowdsourced reporting). Deliverables - Prototype platform (mobile/web). - Demo video with simulated outbreak scenario. - Documentation of data sources, logic, and communication workflows. Implementation Note for Students You can simulate datasets (e.g., mock disease cases or outbreak clusters). Focus on awareness, easy visualization, and multilingual alerts. A creative, community-driven approach will be valued. Additional Notes This problem is unique to Indian healthcare—it blends AI, awareness, and inclusivity. Even simple prototypes with mock alerts can demonstrate huge potential impact. Description Most citizens have shared personal data (emails, phone numbers, IDs, financial info) across multiple platforms over the years. They lack awareness of the risks this creates, often called “privacy debt.” A visualization tool can help users understand and manage their digital footprint. Expected Solution - Build a secure web/mobile tool that allows users to enter or fetch data from platforms (social, email, govt portals, financial). - Visualize the level of “privacy debt” with scoring or categories (low, medium, high risk). - Provide simple, actionable steps (e.g., revoke access, update passwords, delete old accounts). - Focus on clarity and awareness, not heavy cybersecurity backend. Deliverables - Prototype tool demo. - Short video showing user journey. - Documentation of approach and limitations. Implementation Note for Students Students can simulate user accounts and data exposure instead of real logins. Use dummy data to show how “privacy debt” increases and how it can be reduced. Creativity in visualization and risk explanation will be highly valued. Additional Notes A unique idea with high awareness impact in India, where digital adoption is rising fast. Judges will value simplicity, security, and user education. Description Small and medium enterprises (MSMEs) often don’t test their digital systems for vulnerabilities due to cost and lack of expertise. A safe, simulated environment can help them understand and prepare for cyberattacks. Expected Solution - Create an interactive simulator where MSMEs can test common cyberattack scenarios (phishing, weak passwords, malware). - Provide impact visualization (e.g., what happens if a system is breached). - Recommend fixes (e.g., 2FA, stronger passwords, software patches). - Keep the interface simple, non-technical, and training-focused. Deliverables - Simulator prototype demo. - Video walkthrough with sample SME scenario. - Documentation of attack types and recommendations. Implementation Note for Students Students can mock attack scenarios (e.g., fake phishing email, weak password breach) without building real malware. Focus on education + training value, not hacking. Additional Notes This is a rarely explored problem in India. Judges will look for creativity in simulations, clarity in recommendations, and usefulness for MSMEs. Description Users frequently provide consent to apps and platforms (for location access, contacts, financial info, etc.) but rarely track or manage them. Over time, this leads to loss of data control and security risks. A unified solution is needed to simplify consent management. Expected Solution - Develop a cross-platform consent dashboard that shows all past consents in a timeline view. - Enable easy revoke, modify, or re-grant options. - Clearly explain the impact of each consent (e.g., “Location shared with XYZ app for targeted ads”). - Must be multilingual and user-friendly for wide adoption. Deliverables - Prototype dashboard (mobile or web). - Demo video showing how users manage their consents. - Documentation of workflow and design logic. Implementation Note for Students Students should simulate consent records (e.g., mock permissions database) instead of relying on real APIs. Focus on UI/UX clarity, simplicity, and strong visualization of consent implications. Additional Notes This problem is novel in India and directly addresses privacy rights. Judges will value empowerment of end users, simplicity, and clarity in explaining technical choices. Description Urban commuters waste significant time standing in queues for tickets and passes at stations or bus stops. A seamless, contactless solution is required to improve daily transit efficiency. Expected Solution - Develop a multi-modal transit access system using QR codes, NFC, or mobile-based IDs. - Enable offline ticket validation for areas with poor connectivity. - Include fraud detection and security checks. - Support integration across buses, trains, metros, etc. Deliverables - Working prototype (app + backend). - Demo video showing ticketless boarding. - Documentation with workflows. Implementation Note for Students Use mock transit datasets or simulated ticketing systems. Focus on user experience, speed, and security features instead of live API integration. Additional Notes Judges will look for practical usability, integration logic, and scalability to real-world cities. Description With the rapid adoption of electric vehicles in India, charging infrastructure often becomes overburdened or underutilized due to poor demand forecasting. This leads to long queues, power wastage, and reduced convenience for EV owners. Expected Solution - Build an AI-based system to forecast EV charging demand based on location, time, and travel trends. - Recommend optimal station placement or expansion. - Provide real-time dashboards for operators and EV users. Deliverables - Prototype forecasting engine + visualization dashboard. - Demo video showing simulated EV demand vs. supply adjustment. - Documentation of datasets, algorithms, and optimization strategies. Implementation Note for Students - Use Indian EV adoption datasets, transport data, or generate mock EV usage data. - Focus on prediction models, visualization, and smart recommendations. Additional Notes - Emphasis is on sustainability, AI-driven insights, and supporting India’s EV growth vision. Description Urban last-mile delivery systems (groceries, parcels, food) create unnecessary emissions and congestion due to uncoordinated schedules. A solution is needed to optimize delivery slots sustainably. Expected Solution - Create a platform that assigns delivery slots based on traffic, weather, and emission data. - Allow logistics providers to trade or optimize delivery slots for greener routes. - Provide analytics on emissions saved and efficiency gained. Deliverables - Prototype tool + dashboard. - Demo video with mock delivery simulation. - Documentation of optimization logic. Implementation Note for Students Students can use simulated datasets (traffic, weather, pollution) instead of real-time paid APIs. Focus on optimization models, dashboards, and sustainability visualization. Additional Notes Judges will value climate-conscious design, urban impact, and scalability. Description Many soft skills, creative talents, or emerging tech skills are not recognized by traditional certificates. Students and professionals need a community-driven way to validate real abilities. Build a peer-driven soft skill assessment platform for Indian vocational skills (e.g., craftsmanship, local trades, coding tasks) with micro-projects and endorsements. Focus on community validation and skill mapping to local employability. Expected Solution - Build a platform where users can demonstrate skills via micro-projects, tasks, or video proofs. - Enable peer validation and endorsements. - Provide digital badges/skill bank for verified abilities. - Ensure fraud detection and moderation. Deliverables - Prototype web/mobile app. - Demo video with sample validation. - Documentation. Implementation Note for Students Students can design mock skill tasks and sample peer validations. Focus on UI/UX, fairness, and gamified validation mechanisms. Additional Notes Novel idea in India, promotes practical skill recognition and employability. Description Current education content is often disconnected from regional job demands and local industries. A solution is required to generate custom curricula for industry-specific needs. Expected Solution - Build a tool that uses local job data and inputs from industry to design learning modules. - Support AI-assisted content generation. - Export content in formats usable by schools, colleges, or training centers. - Enable multilingual support. Deliverables - Prototype curriculum builder app. - Demo video showing curriculum creation. - Documentation. Implementation Note for Students Students may use mock local job datasets or industry case studies. Focus on practical usability, adaptability, and curriculum quality. Additional Notes Strong industry demand; innovation in education-industry alignment is highly valued. Description Tracking all forms of learning—formal courses, certifications, workshops, and informal achievements—is difficult for individuals. Employers also lack a complete view of lifelong learning progress. A solution is needed to aggregate and visualize learning journeys. Expected Solution - Build a portfolio aggregator that collects learning data from diverse sources (certificates, training, micro-courses). - Provide dynamic visualization of progress over time. - Ensure privacy-first design and secure backups. - Enable multilingual and mobile-friendly usage. Deliverables - Prototype portfolio builder. - Demo video showing a sample user’s journey. - Documentation. Implementation Note for Students You may use mock learning achievements and sample data to demonstrate. Focus on clean design, intuitive visualization, and user empowerment rather than API integrations. Additional Notes Unique opportunity to create a personal growth tracker, highly useful for students, professionals, and recruiters. Description MSMEs often face severe losses during supply chain shocks (pandemics, export bans, natural disasters). They lack tools to assess vulnerabilities and plan alternatives. Students should build a platform that helps MSMEs identify risks, simulate alternative sourcing strategies, and visualize impact. Expected Solution - Build a platform to diagnose supply chain risks. - Use sample MSME data or simulated supply networks (e.g., sector type, suppliers, raw material sources). - Simulate disruptions like pandemics, export bans, or natural disasters to show their impact. - Visualize alternative sourcing strategies and provide an impact/risk scorecard for decision-making. Deliverables - Prototype tool. - Demo video with sample MSME case. - Documentation. Implementation Note for Students - Use mock or sample MSME data to simulate supply chain scenarios. - Focus on visual clarity, showing which suppliers or raw materials are most vulnerable. - Generate risk impact scores for each alternative strategy. - Even a simple demo with mock datasets is sufficient; emphasis is on insightful visualization and decision support. Additional Notes Novel and highly impactful for small businesses; solutions can scale across industries. Description MSMEs struggle to access timely financing due to slow traditional processes. A digital aggregator could provide instant funding visibility. Expected Solution - Build a platform to aggregate loan options, peer funding, and govt schemes. - Include KYC workflows and analytics dashboard. - Prioritize ease of use for non-tech-savvy entrepreneurs. Deliverables - Prototype marketplace tool. - Demo video of loan-matching flow. - Documentation. Implementation Note for Students You may simulate funding options and workflows instead of real APIs. Ensure simplicity and user trust in the design. Additional Notes Very practical solution with direct benefit to MSMEs; scope for real-world adoption. Description Regulatory non-compliance (GST, labor, data privacy) can cripple MSMEs. Manual compliance tracking is tedious and error-prone. Expected Solution - Build a tool that audits and monitors compliance gaps in real time. - Provide alerts and visual compliance dashboards. - Simulate common compliance checks relevant to Indian MSMEs. Deliverables - Prototype checker tool. - Demo video showing alerts. - Documentation. Implementation Note for Students Use mock compliance scenarios and datasets. Focus on usability, clear alerts, and visualization. Additional Notes Underexplored yet critical domain; unique opportunity for legal-tech innovation. Description Most Indian websites/apps fail accessibility standards, limiting inclusion for people with disabilities. Manual audits are slow, incomplete, and resource-intensive. Students should develop a tool that automates accessibility evaluation, highlights issues, and suggests actionable improvements. Expected Solution - Develop an AI-based auditor that scans apps/websites for accessibility compliance. - Suggest contextual fixes with real-time recommendations. - Ensure adherence to WCAG guidelines and Indian accessibility standards. Deliverables - Prototype auditor tool. - Demo video showing sample website/app analysis. - Documentation with findings and recommendations. Implementation Note for Students - Use sample websites or app interfaces to demonstrate auditing. - Focus on analysis, reporting, and actionable recommendations, not full remediation. - Even a simple demo with mock inputs is sufficient; emphasize clarity and usability of recommendations. Additional Notes High social impact by promoting digital inclusivity. Solutions should be simple, scalable, and demonstrate clear improvements in accessibility awareness. Description News is often text-heavy, leaving out people with visual, hearing, or cognitive disabilities. Expected Solution - Build a multi-sensory news platform integrating TTS, sign language AI, and simplified visuals. - Ensure offline reading and accessibility-first design. Deliverables - Prototype news app. - Demo video showing multiple access modes. - Documentation. Implementation Note for Students You can simulate sample news feeds. Focus on usability and inclusiveness. Additional Notes Highly inclusive; fills a major accessibility gap in media. Description India’s dialectal diversity blocks digital inclusion; most apps miss local voices. Expected Solution - Build a translator tool that adapts web/app content into local dialects. - Use AI + community feedback to improve accuracy. Deliverables - Prototype translation app. - Demo video with sample content. - Documentation. Implementation Note for Students Simulate with limited local datasets or create mock examples. Focus on scalability, usability, and community participation. Description This domain encourages students to explore and propose their own innovative problem statements. Ideas may come from any vertical (AI, IoT, Sustainability, Healthcare, FinTech, Agritech, Education, Smart Cities, etc.) or from domains not listed in the hackathon problem statements. The goal is to provide flexibility while ensuring originality. Expected Solution - Identify a real-world problem and propose a novel technology-driven solution. - Clearly define the problem statement, scope, and target users. - Build a prototype/MVP that demonstrates feasibility. - Ensure originality – solutions must not be replicas of already built, widely available, or previously submitted projects. Deliverables - Defined problem statement and proposed approach. - Prototype or working demo. - Documentation explaining the uniqueness, use-case, and scalability. Implementation Note for Students - Solutions must be innovative, practical, and relevant to today’s challenges. - Avoid reusing existing popular hackathon projects or cloned solutions. - Provide clarity on datasets, technologies, and implementation steps. Additional Notes The emphasis is on creativity, originality, and applicability. Teams are free to explore any vertical or propose ideas from new, unlisted domains, but projects must be genuinely new and impactful.
🧩 Hackathon Overview
🎯 Final Judging Panel
🔐 IP Policy
📊 Judging Parameters
Parameter
Description
Weightage
Innovation & Creativity
Uniqueness of idea
20%
Feasibility
Real-world applicability
20%
Technical Depth
Quality of architecture/code
20%
Presentation
Clarity, team communication
20%
Impact
Potential for societal/industrial value
20%
Domain 1: Applied AI & Data Intelligence
Problem Statement 1.1: Real-Time AI Trend Radar for Micro-Enterprises
Problem Statement 1.2: Community-Powered AI for Local Disaster Risk Forecasting
Problem Statement 1.3: Cross-Sector AI Fairness Auditor
Problem Statement 1.4: AI-Powered Cognitive Fitness Games
Problem Statement 1.5: AI-Generated Content Detection System
Domain 2: Agritech & Food Safety (IoT/Software)
Problem Statement 2.1: Predictive Crop Loss Early-Warning Dashboard
Problem Statement 2.2: AI-Assisted Organic Certification Validator
Problem Statement 2.3: Food Supply Chain Leakage Mapper
Domain 3 : Sustainability & Climate Action
Problem Statement 3.1: Dynamic Urban Heat Stress Mapper
Problem Statement 3.2: Waste Circularity Optimizer Dashboard
Problem Statement 3.3: Water Accountability & Transparency Reporter
Domain 4: Digital Public Infrastructure
Problem Statement 4.1: Vernacular DPI Onboarding Suite
Problem Statement 4.2: Single-Window DPI Troubleshooting Assistant
Problem Statement 4.3: DPI Data Use Transparency Tracker
Domain 5 : Healthcare Innovation (ABDM, IoT/Software)
Problem Statement 5.1: Remote Patient Monitoring Compliance Coach
Problem Statement 5.2: Zero-Latency Medical Triage System
Problem Statement 5.3: Proactive Epidemic Awareness Simulator with Community Integration
Domain 6 : Cybersecurity & Privacy
Problem Statement 6.1: Privacy Debt Visualizer for Indian Users
Problem Statement 6.2: Vulnerability Red-Teaming Simulator for MSMEs
Problem Statement 6.3: Consent Flow Optimizer for Personal Data
Domain 7 : Smart Mobility & Logistics (IoT/Software)
Problem Statement 7.1: Queueless Transit Experience Platform
Problem Statement 7.2: AI-Powered EV Charging Station Demand Forecaster
Problem Statement 7.3: Green Urban Delivery Slot Allocation Suite
Domain 8 : EdTech & Skills Empowerment
Problem Statement 8.1: Peer-to-Peer Skill Validation Platform
Problem Statement 8.2: Generative Curriculum Designer for Local Industries
Problem Statement 8.3: Dynamic Lifelong Learning Portfolio Generator
Domain 9 : MSME Digitization & Commerce
Problem Statement 9.1: MSME Resilience Planner for Supply Disruption
Problem Statement 9.2: MSME-Focused Instant Working Capital Marketplace
Problem Statement 9.3: Real-Time Digital Compliance Health Checker
Domain 10 : Accessibility & Inclusive Tech
Problem Statement 10.1: AI-Powered Contextual Digital Accessibility Evaluator
Problem Statement 10.2: Multi-Sensory News Platform for Disabilities
Problem Statement 10.3: Inclusive Content Translator for Local Dialects
Domain 11: Open Domain (Student Innovation)
Problem Statement 11.1: Open Innovation Challenge
DOMAIN-WISE PROBLEM STATEMENTS WILL BE UNVEILED SOON
— BE PREPARED TO TACKLE REAL-WORLD CHALLENGES IN THE HACKATHON. 🔥🔥
Hackathon
About the Hackathon
Name: SciTech Innovation Hackathon - 2025
Rounds:-
Participants: Up to 4 members per team
Rewards: ₹3.75 Lakhs Total
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