Smart Waste Despenser

Waste Despenser

Inspiration

As university students, we found sorting garbage is very frustrating as it can be time-consuming when your lunch waste have plastic, organic, and paper. Moreover, many people do not sort the garbage correctly, and it has a negative environmental impact as well. Therefore, we believe a solution is needed to make the garbage sorting process more efficient.

What it does

A system that essentially sorts garbage based on the type of waste it is using an AI image recognition algorithm.

How we built it

We used multiple sensors including a Bluetooth transmitter, ultrasonic motion sensor, and implemented them onto an Arduino board. We programmed the sensors using C++ to allow the system to detect the presence of the object being thrown into the garbage can. When the motion is detected, the camera will be triggered by the Bluetooth transmitter which will then capture the image of the garbage to send to the server for image processing. In addition, a servo motor is used to correct guide the garbage into the correct category.
We are using Python for the AI algorithm in sorting the garbage into 5 different categories. The AI system will get trained on recognizing the different types of garbage through a code. Once the system reaches a high accuracy of sorting, the software can then be implemented to correctly sort wastes. We downloaded a pip package and we tried to collect data on the Google Colab.

Challenges we ran into

In the mechanical aspect of the project, an issue we ran into was when we were trying to integrate all the individual sensors together. This caused the dysfunctionality of some components when combined into a single program. The circuitry of the Arduino also became advanced as we had to figure out how to utilize the ports for all the sensors.

One challenge we faced in the software portion was getting the IDE to work. We did not have experience working with Python and the coding environment, but I still decided to give it a try. We encountered many issues when we were trying to download the PIP package, and we spent a long time setting things up.

Accomplishments that we're proud of

-We were able to implement a system that combines various disciplines of tech such as AI, programming, and engineering We are proud of the fact that this project is a system that if further implemented in the future, it can have a great impact on reducing waste and improving the environment.

What we learned

-Learned different applications and platforms of AI -Gained skills in collaborating in a team with members from different backgrounds and skill sets -Learned how to problem solve create a solution in a short amount of time

What's next for Smart Waste dispenser

-Improving accuracy into image processing -Implementing more waste categories -Making the system efficient and allowing it to sort the garbage in a reduced time frame