Traffic Data Analysis

Ascendly is an AI-powered startup growth platform designed to connect startups with investors, marketing agencies, and business advisors through a unified digital ecosystem. The platform provides role-based dashboards, AI-driven analytics, and collaboration tools to help startups scale efficiently, streamline operations, and make data-driven business decisions.

Laaba.lk is a smart deal discovery mobile platform that aggregates retail offers, coupons, and real-time product prices from multiple stores into a single app. The system uses automated data scraping and AI-powered processing to track price changes and help users quickly find the best deals and product availability across retailers.

University Resource Hub is a full-stack web platform designed to centralize academic resources for students across multiple universities. It enables users to upload, organize, search, and access notes, guides, past papers, and learning materials through a structured, user-friendly digital system.

Assignment Plagiarism Checker is a full-stack web application that detects text similarity between student assignment submissions and highlights potentially copied content. Built using Next.js for the frontend, Node.js with Express (REST API) for the backend, and MongoDB for storing submissions and comparison data, the system uses text-similarity algorithms to analyze documents and generate plagiarism reports to support academic integrity.

Developed a Python application to analyze traffic data from CSV files and generate statistics based on user-defined queries. Implemented time-based filtering and vehicle-type analysis to provide insights into traffic patterns.

A Java console application for theatre reservations includes various actions such as reserving seats, printing tickets, cancelling reservations, and viewing ticket details within the application.