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Rainwater Harvesting – Backend API A real-time simulation server that models rainwater collection, flow dynamics, and electricity generation. Built with Node.js, Express, MongoDB, and Socket.IO, it streams live sensor data every 5 seconds to power a dynamic environmental dashboard.
🌧️⚡ Real-Time Harvesting Dashboard is a full-stack MERN application that simulates a rainwater-harvesting system with real-time data processing and visualization. It generates sensor-like values every 5 seconds and updates six interactive graphs (Chart.js) on a live dashboard using WebSockets (Socket.IO). Features include tracking water level
A rainwater harvesting simulation built using OpenGL in C++, featuring animated rainfall, gutter collection, and water storage. It’s a modified version of an existing project with unknown origin. We enhanced the visuals, structure, and flow to make it more suitable for academic use. Demonstrates basic OpenGL rendering and environmental concepts.
Designed a sustainable residential building in Revit integrating solar panels, rainwater harvesting, BIM-based structural modeling, and eco-friendly materials to improve energy efficiency, reduce environmental impact, and optimize cost performance.
The survey was conducted across selected communities to assess household water access conditions, perceptions of groundwater systems, and adoption of rainwater harvesting (RWH) practices
Water treatment — RO systems, UV sterilisation, bicarbonate adjustment, rainwater harvesting, grey water recycling. Distinct from pyfarm-irrigation (scheduling) and pyfarm-hydroponics (nutrient solution). Source water quality is a prerequisite for both.
Interactive 2D rainwater harvesting simulation built with Python and Pygame, demonstrating particle systems, real-time rendering, linear interpolation, and basic environmental modeling concepts
Smart IoT project utilizing MQTT protocol with a Laravel 11-powered web dashboard. Developed as part of a Komunikasi Data (IIoT) course, this system enables real-time environmental monitoring, automated water pump control, and sensor data logging through a modern web interface.
AI-powered smart rainwater harvesting system that predicts water quality, harvestable rainwater, and rain energy generation using Machine Learning models with an interactive PyQt desktop application.