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Engineering Minor Project (EC-3082)-A machine learning-based solution to counter the negative impact of large scale industrial paper production on nature and the economy using Python.

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Introduction

After the COVID-19 pandemic students and working professionals all over the world have transitioned to electronic media. This has changed the global work culture. The future is digital and needs integration and a hybridized system to evolve. Therefore, we have decided to develop a software based solution to tackle the impact of:

● Large-scale industrial paper production on environment and,
● Heavy institutional charges for the purchase & distribution of study materials/textbooks per
academic term/semester.


Problem Statement

Since the pandemic has begun, students have been receiving a good amount of books and study materials delivered via courier per semester. The materials can be divided into core and non-core domains. For instance, Engineering Mathematics, Digital Image Processing, Networking, etc. find their place under core subjects, whereas Professional Communication and Engineering Biology are listed under the non technical wing of syllabus that demands theoretical expertise. Therefore, students should always have a choice to receive a particular volume in either electronic format (eBooks - PDFs, ODP, Doc) or hardcopy, depending upon their needs in this online era. This customized mechanism will help a learner optimize his study routine by reading books from a combination of:

● Electronic devices (laptops/smartphones/tabs) and/or
● Paperback (hardcopy).

This, as a consequence, will not only help save the transport & delivery charges but will also exponentially reduce the production amount of paper in institutions on a global scale.


The Solution

The solution to this problem lies in analysing the student's past preference and deciding the best possible quantity of materials by predicting the student's preference in future semesters using Machine Learning. The mechanism stores the student data and computes the quantity of material that needs to be delivered via courier and electronic formats. Lastly, the charges are estimated per student and an analysis is performed that displays the quantity of paper saved per academic semester/year. We will also try to predict and estimate the future demands (file format types) using the previous trends in order to get an idea of the investments that must made into purchasing the materials.


Advantages

  • Reduction in paper consumption (and deforestation, as a consequence).
  • E-books come with font style and size flexibility.
  • Better Memory Management: E-readers can store thousands of books on a single device.
  • Efficient in carrying: Books on paper are difficult to carry around, especially hardcovers.
  • Satisfaction of having an entire library at your fingertips, an infinite supply just a click away, ready to download instantly.
  • No need of an e-reader to read e-books. One can use laptop, an Apple iPad or other tablet device, or even a phone app.
  • Better management of energy requirement for production.
  • Decrease in the amount of industrial toxins used to create pulp and bleach for paper.
  • Boost in the efficiency of water treatment.
  • Promotes the concept of three R’s (Reduce, Reuse, Recycle)

Facts

  1. IT industry once predicted that its emergence is to make paperless offices but its amazing to find that about 95% of office work across the world is still done on paper.
  2. 42% of all global wood harvest is used to make paper. Is it really worth it to cut down our life saving trees for this product? Also the bleaching reagents without proper treatment that get released into river bodies prove to be graveyard for hydrological ecology.
  3. According to a survey, an average tree gets converted in to 12000 A4 sheets. As per our calculations, we require almost 300 trees to run an engineering semester (6 month duration) and a tree requires a minimum of 3 years to grow and become mature.

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Engineering Minor Project (EC-3082)-A machine learning-based solution to counter the negative impact of large scale industrial paper production on nature and the economy using Python.

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