Ecommerce App
Description
This project focuses on the development of a hybrid e-commerce platform, which includes both a mobile application and a web application. The platform is designed to provide users with efficient tools to manage purchases, sales and personal data, as well as security options and usage preferences.
Features
- User Authentication: Secure login and registration functionality.
- Shopping Cart: Add, remove, and update products in a shopping cart.
- Wishlist: Save products to a wishlist for future purchase.
- Search and Filtering: Advanced search and filtering options to find products easily.
- Responsive Design: Optimized for mobile and desktop viewing.
- User account management for buyers and sellers
- Purchase and sales history
Technologies
- Frontend: Android Studio with Kotlin
- Version Control: GitHub
- Design: Figma
Inventory — AI-powered Smart Pantry
Detect, name, classify, and store ingredients in Firebase
Features
- Inventory Management: Add, delete, and view items.
- Image Upload: Upload from files or capture directly from the camera.
- Automatic Image Detection: Google Cloud Vision API extracts the item name from the image.
- Recipe Suggestions: OpenAI API suggests recipes based on your pantry.
Technologies
- React for UI
- Material-UI for components
- Firebase (Storage + Database)
- Google Cloud Vision API (label detection)
- OpenAI API (recipe suggestions)
Usage
- Search Items: filter with the search field.
- Add Items: “Add New Item” → upload image, take a photo, or use auto-detection.
- Delete Items: “Remove” on any item card.
- Recipe Suggestions: click the lightbulb icon to get ideas from your pantry.
EcoVentus: AI-Driven UAV Monitoring Platform
Description
EcoVentus is an advanced AI-powered platform designed to optimize UAV (Unmanned Aerial Vehicle) operations for industries like environmental monitoring, renewable energy, and agriculture. By combining real-time data collection, route planning, and analytics, EcoVentus enables precise, efficient, and sustainable solutions for monitoring and managing key resources.
The platform integrates a web-based interface to control and visualize UAV missions, leveraging artificial intelligence to detect patterns, analyze data, and support informed decision-making.
Features
- Real-Time Monitoring: Visualize UAV flight paths and data collection in real-time.
- Customizable Drone Configuration: Adjust parameters such as altitude, speed, and mission priority.
- AI-Driven Insights: Automatically detect and analyze patterns in collected data.
- Interactive Dashboard: View mission priority scores and flight times, download Waypoint (WP) files for custom UAV configurations, visualize routes on a detailed map.
- Scalable Use Cases: Renewable energy, agriculture, and environmental assessment.
Technologies Used
- Frontend: Next.js, React.js, CSS3, JavaScript, Leaflet.js, React Router, Google Fonts
- Backend: Flask, Node.js, Python
- Database: MongoDB
- Cloud: Huawei Cloud
HoneyRoute — Apiary Intelligence Platform (Powered by EcoVentus)
AI-powered PWA for hive health detection and actionable recommendations
Description
HoneyRoute is a mobile-first Progressive Web App that empowers beekeepers to detect hive health risks using AI-based image analysis, receive smart recommendations, and log actions — even while offline. Designed for rural environments, it supports English and Spanish (ES-MX) and integrates a sustainability-oriented UX.
Developed as part of the Huawei Developer Competition LATAM 2025 (Brazil), HoneyRoute was recognized for its impact on sustainable agriculture and AI innovation in LATAM.
Features
- AI Risk Detection: Capture hive photos and detect health or pest issues.
- Actionable Recommendations: Step-by-step actions with “Done” tracking.
- Alerts Inbox: Filter alerts by severity and resolve them quickly.
- Hive Management: Create, view, and monitor hives with KPIs and history.
- Offline Mode: Operate fully offline with background synchronization.
- Bilingual Interface: EN/ES-MX with instant switch and accessible UI.
Technologies Used
- Frontend: React.js, TypeScript, Tailwind CSS, Service Workers
- Backend: Node.js, Supabase (comming soon), REST/GraphQL API
- AI Integration: Custom vision API for hive health risk detection
- Architecture: Offline-first with IndexedDB queue and background sync
- Localization: i18n (EN base + ES-MX)
CongestionAI — AI-Powered Departure Advisor
Built for Hack-Nation Global AI Hackathon 2025 (Venture Track)
Description
CongestionAI is an AI-powered departure advisor that helps you decide when to leave, not just how to get there. It samples traffic over a time window, estimates ETA, risk, and potential savings, and then surfaces the best departure slot.
Built for the Hack-Nation Global AI Hackathon 2025 (Venture Track), the goal is to enable proactive, data-driven mobility decisions for drivers, city planners, and fleets.
Features
- Plan: Origin/destination input (address, @lat,lng, or placeId) with tunables like window, step, budget mode, avoid tolls/highways.
- Result: Best departure time with ETA, risk level, and “Don’t leave yet” / “OK to go” advisor.
- Departure Advisor Chart: Custom SVG chart overlaying ETA over your window with risk-tinted background (green → red).
- History: Save evaluations with baseline vs. savings (time, fuel, CO₂ / money), search, filters, pin/unpin, import/export JSON.
- Settings: Map provider, units, country/city/locale, and savings model defaults (fuel price, consumption profiles, typical distance).
Technologies Used
- Frontend: Next.js 15, React, TypeScript, Tailwind CSS
- APIs: Google Routes API v2 for traffic-aware routing
- Storage: Local/session storage for cache, settings, and history
- Visualization: Custom SVG charts (no heavy chart libraries)
Upcoming Projects
-
Innovative Social App
Currently in development: A platform focused on connecting users through shared values and soft skills, built using Swift.