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Repsychology is an application developed to prevent the waste of potential reusable materials to promote an eco-friendly environment by seamlessly integrating a trained Clarifai Computer Vision Artificial Intelligence model to determining the data of images then prompting the user to the nearest disposal center via Google Maps API.

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Repsychology

1st Place Award Best Overall Mobile Application in CU3 Hacks Competition July 2017
 $100 Awarded to each team member for 1st Place Award

 Media Coverage from Carnegie Mellon University College of Engineering: 
 https://engineering.cmu.edu/news-events/news/2017/08/31-sv-hackathon-library.html

Repsychology is an application developed to prevent the waste of potentially reusable materials to promote an eco-friendly environment by seamlessly integrating a trained Clarifai Computer Vision Artificial Intelligence model to determining the data of images then prompting the user to the nearest disposal center via Google Maps API.

Introduction

Recycling is a broad subject, and the reason is that a broad range of materials can be recycled, with the goal of recycling being to provide the optimal alternative means of disposal as opposed to “conventional” waste disposal such as incineration methods. The process prevents the waste of potentially reusable materials as well as reducing negative environmental impact including but not limited to water pollution(landfill) and air pollution(incineration).

Expanding on the topic of protecting the environment, recycling is recognized as the third part of the three Rs waste hierarchy, where one takes steps before even disposal, by the processes of reducing and reusing. Reducing means to take action to reduce the amount of waste that a household or factory may produce. Reusing encompasses making the most efficient use of recovered materials. Participating in all three steps is representative of the bigger picture in environmental protection.

The kinds of materials that can be recycled are known as recyclable materials, and these include varieties of glass, cardboard, plastic, paper, as well as salvaging certain products from more complex products, like electronics. This may be done due to the containment of gold in circuit boards, or because of the containment of hazardous chemicals, such as the liquid mercury that is present in many thermometers. Although the decomposition of biodegradable waste demonstrated in composting is technically considered a form of recycling, this will be neglected as the main focus of the topic concerns non-biodegradable materials and will be removed from food packages during the rinsing process.

There are a number of different collection methods that are available: curbside collection usually starts with a waste collection vehicle, but then branches into a central sorting system, where any wrongly placed materials are thrown out, as opposed to the single-stream system where greater public education is more greatly emphasized in importance. These two methods are recognized as mixed waste collection, while source separation is much more cost-extensive in the fact that all material is cleaned and sorted prior to collection. Drop-off centers simply collect it and send it to a centralized location. Buy-back centers buy the cleaned recyclates are bought.

Creator

The HTML Website was created by Aditya Sharma, Bill Xiang, & Pranava Parasa.

The Android Application was created by Nikhil Pillai & Aayush Bhat

Credits: The website was created during a hackathon and therefore Start Bootstrap Template was used. Start Bootstrap was created by and is maintained by David Miller, Owner of Blackrock Digital.

Copyright and License

Copyright 2016 HackApp30. Developed by Aditya Sharma. All Rights Reserved.

About

Repsychology is an application developed to prevent the waste of potential reusable materials to promote an eco-friendly environment by seamlessly integrating a trained Clarifai Computer Vision Artificial Intelligence model to determining the data of images then prompting the user to the nearest disposal center via Google Maps API.

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  • HTML 85.4%
  • JavaScript 12.7%
  • CSS 1.9%