Portfolio
My Works
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- Mobile App
- Data Visualization
- Web App
- AI/ML Apps
My Works
EMRS is an Android-based application designed to revolutionize environmental monitoring and reporting. It enables users to track key environmental parameters such as temperature, humidity, air quality (PM2.5, PM10, CO, SO₂, NO₂), wind speed, and wind direction. Users can also report incidents like pollution, spills, and waste issues in real time.
A personal hobby project featuring a cross-platform real estate application built with Flutter for browsing and managing property listings.
A Novetiv is a Social Media Mangement that allow user to manage a a post and interact with novetiv AI chartbot
MyAI is an AI/ML-based chatbot application built to simulate natural human-like conversations and assist users in real time. Similar to ChatGPT, it can answer questions, provide information, and hold engaging discussions on various topics. Designed with a user-friendly interface, MyAI leverages natural language processing (NLP) and machine learning models to understand user queries and generate context-aware responses.The app supports text-based input and returns intelligent replies tailored to user intent. It's ideal for customer service, education, productivity, or personal support tasks.
The Agricultural Footprint Calculator is a smart, role-based web app that enables Nigerian farmers and agricultural administrators to monitor, analyze, and improve their environmental impact. Users can log farm activities—such as crop yield, fertilizer use, water consumption, machinery fuel usage, and livestock data—and receive personalized sustainability insights via interactive dashboards and footprint calculators. The system computes carbon, water, and land degradation footprints, generating tailored sustainability scores and improvement tips. Admins can validate datasets, manage users, and adjust models through a secure panel, supported by alerts and visual reporting for informed decisions.
RetinaScan is an AI-powered Django web application for automated diabetic retinopathy detection from retinal images using a ResNet-50 deep learning model, providing real-time predictions with confidence scores and Grad-CAM visual explanations.
An interactive data analytics dashboard developed during the Excelerate internship to visualize insights and support data-driven decision-making.