Maaly MOULAY EL HASSEN

Design of a forest digital twin system integrating IoT sensors, predictive models and immersive 3D visualization. Development of real-time monitoring interfaces, fire spread simulation , and conversational virtual assistant.

This project aimed to develop an end-to-end data-driven solution to support the monitoring and forecasting of foreign exchange rates published by the Central Bank of Mauritania. The system included the following main components: Automated Web Scraping Module: Built to extract daily exchange rate data directly from the Central Bank’s official website. The scraper was designed to update regularly and handle data formatting, missing values, and duplicates efficiently. Interactive Dashboard: Developed using web technologies such as Django and Plotly, the dashboard allows users to visualize the historical evolution of currency exchange rates by month and year. It also includes search, filtering, and export functionalities. Exchange Rate Calculator: A simple tool integrated into the interface to allow users to calculate the MRU value of a chosen foreign currency based on the latest official rate. Forecasting Module: Implemented machine learning models (including ARIMA and LSTM) to predict short-term exchange rate trends, using historical central rate data for each currency.

Short-term internship focused on discovering public data workflows across three departments: statistics, economics, and accounting. Tasks included basic data cleaning, report formatting, and visualization of key indicators used in national development planning.