Ritwik Sharma

Data Analyst

NMIMS Universityfull_time, internship

2Projects

6Skills

3Achievements

Open to roles

Ritwik Sharma

Featured project

UrbanHop - Smart Bus Management System

UrbanHop is a real-time smart transit platform designed to reduce uncertainty in daily commuting (for people like me) by helping users know whether to leave now, wait, or switch routes. Built using Flask, SQLite, OpenStreetMap, and live ETA prediction logic, the system combines live bus tracking, route reliability analysis, and actionable commute suggestions to provide commuters with fast, lightweight, and reliable public transport intelligence directly on their devices. NOTE - This is just a small demo, a lot of changes are to be done using official real-time data Process I started by identifying core commuter problem: people do not just want bus timings, they want confidence in deciding whether to leave now, wait, or take another route. After analyzing apps like Chalo and Google Maps, I focused on building a lightweight solution that works quickly even on low-data networks. We designed the platform using Flask, SQLite, HTML, CSS, JavaScript, OpenStreetMap, and Leaflet.js to keep the system fast, scalable, and easy to demo during the hackathon. Results UrbanHop successfully delivers a fast and interactive real-time transit experience with live map integration, simulated moving buses, location-based interaction, and smart commute recommendations. The platform provides actionable outputs instead of only displaying schedules, making the experience more useful for daily commuters. The lightweight architecture also keeps the app responsive and suitable for low-end devices and slower internet connections. If developed further, the system can be expanded using real GTFS transit feeds, WebSockets for live updates, and machine learning models. Reflection Given more time, I would integrate official real-time transit APIs instead of simulated bus movement to improve ETA accuracy and realism. I would also add route polylines, traffic-aware predictions, multilingual support, and a WhatsApp/SMS interface for commuters using basic phones or low-data connections. Another improvement would be implementing WebSockets or Firebase for smoother real-time synchronization between buses and user devices.

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2 skills backed by real projects on this profile.

Core skills

PythonMachine LearningSQLpandasData AnalysisStatistics

Campus Cashbook: Student Expense Tracking & Budget Analysis System
College students like me spend small amounts daily on food, travel, recharges, study materials, and subscriptions. These expenses often go untracked, making it hard to see where money goes or why budgets run out early. The challenge was to build an offline, command-line expense tracker that lets students record spending, review history, monitor budgets, and spot patterns without internet, apps, or external services. Campus Cashbook solves this with a lightweight Python tool using only standard libraries. It keeps budgeting simple, fast, and accessible for everyday student use Process I started by reviewing the requirements and defining the essential features of the expense tracker. The first version stored expenses only in memory, but that lost data after exit, so I moved to JSON storage for simple persistence without a database. I then built a menu-based interface to keep the tool easy to use, added expense summaries and category analysis, and introduced a monthly budget alert to help users control spending. To make the app more useful, I included a finance score, streak tracking, spending insights, and CSV export. I refined the output with clearer summaries and text charts, while keeping the project lightweight, reliable, and fully compliant with the hackathon rules by using only Python standard libraries Results The final solution delivers a fully offline expense tracker that helps students record, organize, and review their daily spending. Users can add transactions, check history, track monthly budgets, find their top spending category, and export reports for later use. With JSON-based storage, all data stays saved between sessions. The app is lightweight, easy to run, and meets the hackathon rules by using only Python standard libraries with no internet, frameworks, or databases Reflection If I had more time, I would expand the project with visual charts, stronger search and filtering, recurring expense support, and multiple user profiles. I would also improve the analysis engine so it can give smarter spending advice based on past behavior. For a production version, I would move storage to SQLite or PostgreSQL, add user authentication, and build a web or mobile interface while keeping the same simple and student-friendly design
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Ritwik Sharma

UrbanHop - Smart Bus Management System

Proof of work

Core skills

Campus Cashbook: Student Expense Tracking & Budget Analysis System