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Abdus Sami

FAST · 2020 · i16 - 0402
Email
Phone
LinkedIn
GitHub

Academic

Program
CGPA
Year
2020
Education
Address
DOB

Career

Current role
Target role
Skills
Raspbian, PyCharm, CNN, Convolution Neural Network

Verbatim text

The exact text the LLM saw on the page (or the booklet text from the old import). This is what powers semantic search.
Smart Beverage Container Collecting Machine 
 
This Project aims for collecting empty beverage containers at the source and increasing the 
recycling rates with a reward system. It becomes possible for users to preserve and to collect the 
waste separately and cleanly at the point that the waste occurs by throwing different beverage 
containers. If people are given an incentive to properly dispose of PET bottles it will reduce littering 
and allow recycling. More than 480 billion plastic drinking bottles were sold in 2016 across the 
world, up from about 300 billion a decade ago. If placed end to end, they would extend more than 
halfway to the sun. By 2021 this will increase to 583.3 billion, creating an environmental crisis. So 
the need to improve recycling processes and restrict environmental crises gives this project the true 
value and importance. 
Smart Beverage Container Collecting Machine collects recyclable bottles and cans. Firstly, the user 
inserts a beverage container and an RGB camera detects using CNN (Convolution Neural Network) if 
it matches the accepted type of container. After acceptance, it goes into the conveyor belt system 
to be sorted to its related dustbin depending on its type (Cans, bottles). A reward is sent to the 
user’s mobile phone in the form of a text message. Also, a cloud is used to show the current 
capacity of all the dustbins to the recycling company. 
 
 
 
 
 
 
 
 
 
 
Technology Used: 
Raspbian, PyCharm,CNN 
Supervisor Name: 
Dr. Wasim Ikram 
Group Members:   
Muhammad Haseeb Ahmed (i16 - 0514) 
Abdus Sami (i16 - 0402)

AI enrichment

Abdus Sami is a student who collaborated on a smart beverage container collecting machine project utilizing CNNs for object detection and a conveyor system for sorting. The project involved integrating hardware with software to automate recycling and reward users via mobile notifications.
Skills (AI)
["CNN", "Raspbian", "PyCharm", "Object Detection", "Conveyor Systems", "Cloud Integration"]
Status: ai_done
Provenance
Source file: Graduate Directory FAST School of Engineering - 2020 (Final) (1).pdf
From job #20 page 87
Created: 1778120242