Inspired by the technology embedded into our daily lives, we decided to harness this potential by creating a smarter waste management solution for the 21st Century.
What it does
Every bin has multiple sensors, such as ultrasonic and moisture sensors, to capture real-time data. It is then processed and using machine learning, optimizes things such as times of collection and maintenance, saving money for the company and reducing a carbon footprint on the earth.
How we built it
We used Django to write the core functionality of our web program, using HTML/CSS to display it to our users. To capture, store, and analyze our data, we read and processed raw data from our Arduino Uno, and stored it into a MongoDB database.
Challenges we ran into
Using asynchronous calls within python was a big challenge in getting real-time updates for notifying the employee.
Accomplishments that we're proud of
We were able to implement real-time tracking for a live demonstration for one of our bins. Additionally, we implemented individual user login, which allows for multiple employees to use the system.
What we learned
With proper planning and good teamwork, you can go farther than you think. Additionally, the implementation of hardware was very interesting and took less time than we thought.
What's next for HastyWaste
We would like to implement GPS tracking systems for all bins, allowing them to be in a meshed network of bins across a office, city, or even state. We would also like to use API's such as Esri's ArcGIS to map and plan the fastest, most efficient route for collection.