Urban Oasis is a project investigating the energy efficiency of live walls compared to traditional walls by examining different wall types and insulating materials. The model measures heat transfer rates using plants like Pothos, Philodendron, and Boston Fern, and compares temperature and humidity on both sides of live and traditional walls. Utilizing AI and machine learning, it aims to optimize energy conservation and reduce reliance on air conditioning. This project provides comprehensive insights into the thermoregulatory capabilities of indoor live wall systems, building on existing studies to advance sustainable building practices.
The frames are made from acrylic sheets, selected for their durability and ease of customization. These opaque acrylic frames provide robust support for the live wall structures and integrate seamlessly with the sensors measuring temperature and humidity, ensuring stability and functionality.
The experiment employs diverse materials to assess energy efficiency. Wall types like red brick, cement, and plaster of Paris provide durability and insulation. Insulating materials such as cork sheet and rockwool offer thermal protection. Selected plants like Pothos and Philodendron aid in air purification and cooling, promoting sustainable construction practices.
Arduino Mega, with its 54 digital I/O pins, 16 analog inputs, and multiple UARTs, interfaces with various sensors efficiently. Its enhanced memory and I/O ports enable seamless data acquisition and control, making it indispensable for managing complex tasks and ensuring optimal performance.
The DS18B20 temperature sensor measures indoor and outdoor temperatures, while the DHT11 sensor compares temperature and humidity levels indoors and outdoors. These sensors provide essential data for understanding environmental variations, aiding in the project's analysis of climatic conditions
In the project, the LCD 16x2 module serves as a user interface, displaying real-time sensor readings and project data. Its compatibility with the Arduino Mega enables seamless integration, providing clear and concise information for monitoring environmental conditions and system status.
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