"Save the environment. One scan at a time."


Currently, 300 million tons of plastic are produced a year. 91% of this plastic is then never recycled, and makes its way into our environment, with severe, detrimental effects. It has been recognized for a long time that if we do not act on this problem now, the consequences will only escalate from here. That being said, people have been too passive in dealing with our changing climate.

We must integrate better environmental practices into our daily actions. The first, important step is to supply people with the information they need to evaluate their actions. To reduce our plastic waste, we need to provide consumers with the tools and information to make environmentally friendly decisions about the goods and services they purchase. Our app, PlastiCare, is one of those tools.

The frontend was built by using the Unity engine and C# for making the UI elements interactive, as well as communicating with the server to integrate the backend. The backend was created in Flask and Python. Our server accepts GET and POST requests to detect the amount of plastic in a queried image and to add and to return a list of saved products. To detect the amount of plastic in a given image, we used a deep learning object detection package called ImageAI and Tensorflow.

Down below are listed the app’s features in detail.


  • Accurately detects items and displays predicted plastic content
  • Recommends eco-friendly products that contain biodegradable/compostable material or contains less plastic content than currently scanned item
  • Keeps track of the user's consumption history on Dashboard through 'Add to List' feature.
  • Visualizes the user's plastic consumption history compared with the average user's consumption
  • Educates users about plastic consumption and climate change through short fun facts
  • Help feature which includes options to view step-by-step tutorial, report a problem, and manage account

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