Can we improve the world using tech?
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A Robot that cleans the parks and roads
This project aims to create an AI-powered virtual robot capable of autonomously cleaning parks and public spaces. Using Unity ML-Agents, I’ve developed a simulation where the robot learns tasks such as navigating around obstacles, identifying trash, and efficiently cleaning the area. The robot is trained through reinforcement learning, receiving rewards for completing tasks like trash collection and avoiding collisions, optimizing its behavior over time.
By incorporating advanced AI techniques, the robot is designed to be a potential solution for automating public space maintenance, reducing the need for human intervention while maintaining cleaner, greener environments.
Access all the relevant code on Github
An SOS App (Work in Progress)
The My Buddy app is designed to enhance personal safety by allowing users to send emergency SOS alerts to people nearby within a 500-meter radius. When triggered, the app sends a loud alert, along with a message containing the user's location and other crucial details. It also includes features like automatic calls to emergency contacts, video/audio recording, and more, ensuring comprehensive support in critical situations.
Built for both Android and iOS platforms using React Native, the app aims to create a quick and reliable way to get help when it’s needed the most, whether for personal emergencies or public safety incidents.
The App is still work in progress and I actually need help on a couple of aspects, not able to get some things to work
My Other projects
Mood Detection using Facial Expressions
This project focuses on developing a machine learning model that detects human emotions through facial expressions. Using a dataset of images, the model is trained to classify emotions into multiple categories such as anger, happiness, and sadness. Leveraging TensorFlow and Keras, the model is built using a transfer learning approach with MobileNetV2 as the base. Additional dense layers are added on top to fine-tune the model for emotion classification.
Web Scraping Automation using VBA and Selenium
This project automates the process of retrieving and compiling key company information such as employee count, founding date, and leadership roles using web scraping techniques. Leveraging Selenium and VBA Macros, the automation pulls reports from public sources like Wikipedia and LinkedIn. The solution is designed to streamline tasks by automatically fetching and extracting relevant data such as head of HR, recent job openings, and company profiles, reducing the manual effort involved in sourcing information.
