VentFlow

The Project

This project is an innovative solution for the issue of increasing energy costs caused by a waste of energy in AC systems. This solution is a smart vent system that allows the user to regulate the air flow in their home through altering different settings in a mobile app. The system has many components to ensure its proper function: The hardware and motorized parts, the raspberry pi and its code, the frontend application, and the backend cloud database. To start, we have modified a standard AC vent by connecting a 5V servo motor using linkage rods. The servo motor is attached to three of the pins on a breadboard which is circuited properly to supply the sufficient amount of power to the motor. In addition, a digital thermometer pin is also connected to the breadboard, allowing us to read the temperature of the surroundings. This breadboard is then naturally connected to the Raspberry Pi, which uses the built-in Python IDE to open or close the vent after reading the temperature. Subsequently, the Raspberry Pi will then upload the temperature reading to the Firebase database. The database stores many important pieces of information, such as the ID number of each vent, whether the thermostat system is cooling or heating, the current temperature, target temperature, and more. This information is not only used when determining whether the vent should be open or not, but is also the basis for the mobile app. The mobile app displays the current temperature and allows users to both manually control the vent or set it on auto mode. When the vent is in auto mode, the user will set a target temperature and the vent will open or close depending on whether the thermostat is heating or cooling, and then maintain the target temperature until a new one is set. This app is developed in the Android studio IDE using Google’s open-source UI development kit Flutter. Flutter uses the object-oriented programming language, dart.

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Team Comments

I initially made this project because I wanted to regulate the airflow inside my home so that each room could maintain a temperature that suited a family member's preferences. However, as I did more research, I realized that this project could also be beneficial to the community and the community.

A difficult part about this project was updating variables on the app live. To accomplish this, I used reference variables that corresponded to cells in the Firebase database. Then, by editing these references, I was able to push/pull information to and from the database, updating information live.

If I had extra time, I would clean up the wiring, and condense the parts. Additionally, I would try to add more AI sensors and features such as sound, vision, thermo, etc. in order to train a model that can accurate predict what temperature the user would want without needing any input.