Ali Toghani

GameStat Tracker is a personal project I built to collect and display seasonal KvK (Kingdom vs. Kingdom) stats from a mobile game. The data is gathered using a Python script that leverages pytesseract for OCR and pyautogui for screen automation to read player IDs, names, and other relevant info directly from the game interface. The collected data is then uploaded to a Firebase Cloud Firestore database. On the frontend, I use a React app built with TypeScript to fetch and display the data in a clean, user-friendly way. The site is still a work in progress and I continue to maintain and improve it as I go.

I'm working on moving the entire data collection process to the cloud. The plan is to host the script on an AWS EC2 instance and use AWS Lambda to trigger the scan remotely. This will allow server leaders to initiate scans on-demand, eliminating the need for manual runs on my end. The goal is to make the system fully automated, scalable, and easier for others to interact with.

In a collaborative effort, our team of three has put together a simple calendar app for Android. We used Java and SQLite in Android Studio to make it. It does what you'd expect a calendar to do: you can transfer your existing calendar into it, set up reminders for your events, and search for specific events easily. It's a straightforward, no-frills app that helps keep your schedule organized.

The objective of our project was to simulate a realistic traffic light intersection. We designed a system where vehicles of varying sizes and pedestrians can signal their intent to cross. The hardware foundation is built on Arduino Uno, complemented by an array of sensors, including ultrasonic sensors and buttons. For software, we utilized MATLAB to program the logic and control mechanisms that manage the intersection's operation.

This bot is engineered to emulate the functionalities akin to JARVIS from the Marvel Cinematic Universe. Utilizing the OpenAI ChatGPT API, it replicates JARVIS's informative responses and conversational style. Google's speech-to-text technology captures user inputs, while Amazon Web Services' text-to-speech capabilities articulate the ChatGPT responses in a refined British accent reminiscent of JARVIS.