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Muzammil Shakir

FAST · 2022 · i18 - 0645
Email
Phone
LinkedIn
GitHub

Academic

Program
BSCS
CGPA
Year
2022
Education
SEECS
Address
DOB

Career

Current role
Target role
Skills
Node.js, Next.js, Express.js, MongoDB, Flask, Raspberry Pi, AWS, Electron.js, MERN stack, Object Detection

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.
Online Digital Advertisement Marketplace (ODAM) 
 
ODAM is a web-based application developed in MERN stack for remotely controlling and uploading 
ad campaigns on Digital Billboards using Raspberry PIs and electron JS application. Three different 
applications are developed – Portfolio Website, Client Application and Admin Application – to cater 
to the needs of our project. The Front-end applications are developed using Next.js framework. The 
client application will allow new users to view the geographically dispersed and different billboards 
that are available for booking. The billboards are tagged on Google Maps to ease the process of 
search. The selected billboard will show the time during a day when it is available for booking and 
what price will be charged for a selected period of time. The remote access and control of content 
on the digital billboard is implemented using Raspberry PI. The Raspberry PI will not only run 
Electron.js for display of content but also send a regular pulse to check the live status of the said 
billboard. The admin will approve an ad campaign before it can be run on the billboard. The 
installed IP camera on the billboard will take the live feed of the traffic and run an object detection 
module to detect different vehicles and humans. The resultant data will be saved and will be 
showed as an analytics to the target customer. The Super Admin will have control over all the CRUD 
operations relating to new admin, billboards, advertisements and hirers. The interoperability of 
different independent modules is managed by Node.js main server. We have used Amazon S3 
bucket for uploading of Ad Videos and images. 
 
 
 
Technology Used: 
Node.js, Next.js, Express.js, MongoDB, Flask,   
Raspberry Pi, AWS, Electron.js 
Supervisor Name: 
Dr. Mohammad Adnan Tariq 
Group Members:   
Abdul Waheed (i18 - 0535) 
Muzammil Shakir (i18 - 0645) 
Zohaib Khalid (i18 - 1565)

AI enrichment

Muzammil Shakir is a BSCS graduate who contributed to a MERN stack digital advertisement marketplace project involving web applications and IoT integration with Raspberry Pi. The project utilized Next.js, Node.js, and AWS S3 to manage ad campaigns, billboard control, and analytics via object detection.
Skills (AI)
["Node.js", "Next.js", "Express.js", "MongoDB", "Flask", "Raspberry Pi", "AWS", "Electron.js", "MERN Stack", "Web Development", "IoT"]
Status: ai_done
Provenance
Source file: Graduate Directory FAST School of Computing 2022 Final Version (07-06-2022).pdf
From job #25 page 244
Created: 1778170963