Mateus Araújo

My academic project from the 1st semester of the CESAR School Computer Science undergraduate course in partnership with AACD (Associação de Assistência à Criança Deficiente) was called "Ta Na Mão". In this project, a prototype was developed to assist in collecting donations from AACD’s donation box, using an Arduino Uno, an RTC DS3231 (Real Time Clock) to keep date and time information, along with some buttons, LEDs, and a switch. This product will create an Excel spreadsheet with the information read from the donation box and saved on an SD card, using code on the Arduino, and a Python script when the device is connected to the computer.

My academic project from the 2nd semester of the CESAR School Computer Science undergraduate course, in partnership with Jornal do Commercio (JC), specifically the Sistema Jornal do Commercio de Comunicação (SJCC), was called "JConnect". The objective of this project was to make JC a relevant product for young people, and to achieve this, a web portal called JConnect was created along with an Instagram profile to increase engagement. This web portal aims to be interactive, allowing users to receive personalized news and offering a loyalty benefits program using a virtual currency called JCCoins, which is used internally within the application. For the development of the web prototype's Front-End, Bootstrap with HTML, CSS, and JavaScript was used, along with a Python implementation using Flask for the Back-End. 

My academic project from the 3rd semester of the Computer Science undergraduate course, aimed at improving the security of public transport users using digital technologies, was called "SafeRide". To carry out this project, 4 semi-structured interviews were conducted with the director of the Borborema group, the Secretary of Urban Mobility and Control of Recife, the MPPE transport prosecutor, and the director of CTTU. As a prototype created for this project, an object recognition system was developed to be used with the cameras present on Recife's buses. Additionally, a web application prototype was developed to provide user feedback on the camera and the bus in general. The tools used included Spring Boot, with Java and Python, for the object recognition system, and Wordpress with JavaScript, HTML, and CSS. The prototype code can be found at this link.

My academic project from the 4th semester of the Computer Science undergraduate course was called "Eureka". It was developed to improve and optimize the data collection and analysis processes used by FOZ Inovação. The goal was to enhance efficiency and engage entrepreneurs more effectively. As part of the project, three SQL scripts were created using DBeaver.

 My academic project from the 5th semester of the Computer Science undergraduate course was called "Insights".  In this project, a system was developed to classify and better visualize data, with the goal of improving the performance evaluation of CESAR`s suppliers. This system was developed using tools like Google Colab, Python, MySQL, Flask, GitHub among others.

My academic project from the 6th semester of the Computer Science undergraduate course, called "SoundsBetter", in which a program was developed using Machine Learning, employing MLP (Multi-Layer Perceptron) and KNN (K-Nearest Neighbor), to recommend songs based on the user's emotion. The user indicates the emotion they are feeling, and the program makes predictions to recommend the 10 best songs for that emotion. The project was developed in Python on Google Colab, using a public Spotify dataset for the recommendations. This project GitHub repository can be found here.

 This project, which I developed in collaboration with other students, is a door automation system based on IoT, built using an STM Núcleo and a Node MCU. This solution provides the convenience of remote control and the security of a customized locking system, utilizing WiFi connections and web interfaces to enable effective integration with other IoT devices.

All the development  and implementations details can be found here.

  My internship consisted of creating the back-end of a easy-to-use web application for the evaluation of professors from the student's perspective. It was created using GitHub, Docker, Node.JS, Express.JS and PostgreSQL as the database.

https://github.com/m44g0/evaluat-backend