Inspiration

Abstract

Smart Trash Sort - Waste Classification helps in effective disposal of waste. However, separating them manually is a tedious process and also not efficient. Improper segregation results in pollution and affects the environment. We intend to develop an automated bin that automatically classifies and segregates wastes as Bio-Degradable and Non-Biodegradable and places them in the respective bin. We plan to achieve the same using IoT by passing the image data to the Cloud to perform analytics and return the classified output to the controller of the bin and triggers it to place the waste in correct container. We also send the usage data to the cloud to perform analytics about the bin usage and deploy it in a web app to report the live status. The users will also be awarded some credit points based on the amount of biodegradable waste they throw-in. They can use these credit points as vouchers on Amazon/eBay etc.

Why waste Classification is Important

Biodegradable and non-biodegradable wastes should be discarded in two different dustbins so that they can be collected separately. Waste can be segregated at the source itself which in turn allows effective treatment and disposal. The biodegradable waste can be decomposed in a natural manner by the process of composting. Non-biodegradable wastes can be sent for recycling. Because they don't break down easily, if not disposed of properly, non-biodegradable waste can cause pollution, block drains, and harm animals. If the two wastes are collected in a single bin, they would mix and may form toxic compounds which can cause pollution.

Impact On Climate

The inefficient segregation of waste is a major cause of environmental pollution. As we all know, pollution is a major factor contributing to the deterioration of the world’s climate scenario. In India, the Swachh Bharat Mission was created by the government to promote proper waste disposal to maintain clean cities and thereby protect the environment. Unfortunately, it is not being followed by a major portion of citizens. It is inhumane to expect the government to manually segregate biodegradable and non-biodegradable waste from landfills. So, biodegradable waste is not used for energy generation and further contributes to pollution. Although inculcating responsibility among citizens is the top priority, it is a time-consuming goal. So, we have created a system that automates the entire waste segregation process thereby eliminating the need for ‘dirty work’. Through this system, the waste classified can be used for a variety of purposes - Biodegradable waste can be used to generate sustainable energy and NonBiodegradable waste can be recycled. As an effect, pollution is reduced. If implemented widely, this could majorly affect climate change for the better.

Inspiration

Segregating wastes manually is a tedious task and improper segregation leads to pollution of the environment. Biodegradable waste can also be used effectively for producing biogas and in the fuel industry. If they are not segregated properly it is rendered useless and harmful. So there is a need to develop an automated waste segregator for the efficient disposal of waste.

What it does

The system takes a picture of the object kept on the surface and uses machine learning to predict whether Biodegradable or NonBiodegradable waste or not. The system is triggered when the hx711 module detects a change in weight and this triggers the camera which takes the picture and sends the image to the cloud where the machine learning model is deployed. Based on the result, the corresponding motor is triggered. Also, the system is integrated with a web application where the application tracks the amount of waste classified by different people and awards them with points for using the system. The more bio-degradable waste they throw in the more points they get. This is just a kind of motivation that might encourage people to shift to systems like these. In the future, if possible this can be integrated into actual money if w get support from the country's government

Overall Architecture

Overall Architecture

How we built it

The system is built using Raspberry Pi which controls all the hardware components involved. The machine learning model is trained on Google Cloud and the model is deployed on Heroku to which we have created an API. So when the camera is triggered the RPI takes an image and sends the image to the custom API which helps us decide whether the given waste is Biodegradable or Nonbiodegradable

Challenges we ran into

  1. Connecting RPI with all the components

2.Integrating Motor and Weight module

3.Putting together all the various components involved to make a single product

Accomplishments that we're proud of

1 . Training a deep learning model that accurately classifies the waste as biodegradable or non-biodegradable

2 . Integrating Raspberry pie with the servo motor and design the hardware so that it passes the waste into the respective bin based on the output from the deep learning model - BioDegradable or Non-Biodegradable

3 . Sending data (class, image, timestamp) and image of the waste from raspberry pie to cloud and retrieve it in the web UI and display it

4.Design the hardware circuits rigid and strong so as they don't get disturbed by the trash thrown

What we learned

We learned a lot about RPI and how to work with the motor and sensors. We learned how to deal with problems caused when developing something with RPI. We learned a lot about machine learning and API creation as the whole projects rely on the Backend result of whether is Biodegradable or not

What's next for SMART TRASH SORT

To develop the product completely and make it suitable for all kinds of wastes so that it flawlessly detects the type and hence could be deployed in a real-world situation making waste segregation easy. We are also planning to add more features like sending a notification to the concerned authorities when a trash can is full so that they could empty it quickly

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