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SmartCart: Your Personal Shopping Assistant
SmartCart is a mobile app which has been developed for catering the needs of customers
which have to go for groceries in a supermart It also facilitates the Mart Managers as well
to see placed orders and keep track of their inventory. This app offers the customer view,
manager view and the admin view. The admin view is used to add more Manager
accounts to the user base whereas the manager is able to track inventory such as each
product details, quantity left, re ordering if the quantity is low. The customer, is able to
create digital shopping lists with which the customer can see the location of each product
in his/her list in the mart. They can also scan the products themselves to add that to bill so
they only have to pay once at the checkout counter. The app can also suggest products
based on previous shopping records.
Features include:
• Digital List creation from a list of products.
• Product suggestion based on previous shopping records
• Self scanning products using the mobile by scanning the product barcode
• Order placement for delivery, pickup
• Inventory checking through manager interface
Technology Used:
Flutter, PostgreSql, Supabase,
Visual Studio Code, Github
Supervisor Name:
Ms. Urooj Ghani
Group Members:
Aftab Zaheer Baig (i20 - 0417)
0306-8851717
i200417@nu.edu.pk
Sawaira Fatima (i20 - 0744)
0333-7633814
i200744@nu.edu.pk
Muhammad Shayan Tariq (i19 - 0535)
0312-8772917
i190535@nu.edu.pk
Real-Time Threat Hunting
The "Real-Time Threat Hunting" project addresses the challenge of identifying and
responding to cybersecurity threats in real time amidst increasing malware attacks. Current
methodologies face limitations due to excessive data volume and traditional practices,
leading to inefficiencies in threat detection. With over 560,000 new malware pieces daily
and escalating cyber-attacks, there's a pressing need for effective threat intelligence
technology. The project caters gto tge problem through a high-performance threat detection
system using parallel processing, enabling real-time analysis of network packets.
Its scope includes:
• Capturing and processing network packets to continuously scan for risks and
anomalies.
• Leveraging parallel processing techniques for efficient packet analysis.
• Malware Detection through signature matching techniques.
• Increased throughput for packet capture and malware detection
• Ultimately, the system will empower security analysts to proactively identify and
respond to emerging threats through intuitive visualization and modern interactive
dashboards.
Technology Used:
Python, Github, JavaScript, NodeJs
React, Visual Studio, Linux, OpenCl
Supervisor Name:
Dr. Qaisar Shafi
Group Members:
Usman Siddiqui (i20 - 0586)
Haaris Anjum (i20 - 2607)
Umar Farooq (i20 - 0644)
TranspaRent
The current rental process is overwhelmed with inefficiencies. Traditional methods are often
time-consuming and prone to disputes. There is a need for a streamlined, secure, and user-
friendly rental platform that ensures legal compliance and promotes trust between landlords
and tenants. We are creating a user-friendly website where individuals can seamlessly
switch between being a tenant or a landlord. Users acting as landlords will begin by
uploading detailed property listings, and our AI feature will suggest a fair rental price based
on the provided information. Tenants can then browse through these listings, view their
reviews and select their desired property, and proceed to book it. Upon booking, a smart
contract is generated which uses our secure multi-signature feature, requiring approval from
both
the
tenant
and
landlord
before
the
agreement
is
finalized.
Features include:
• Contract Management: Users can create, store, and retrieve tenant agreements on
a secure blockchain platform.
• Identity Verification: Robust identity verification services, including integration with
NADRA and third-party screening services, enhance security and trust.
Technology Used:
MongoDB, React.js, Node.js, Express.js,
Solidity, Ganache, Web3.js, Flask, GitHub,
AWS
Supervisor Name:
Dr. Qaiser Shafi
Group Members:
Ahmed Baig (20I-1884) (03345220789)
Ameera Haider (20I-0799) (03374991424)
Usman Kamal (20I-0562) (03176817102)
Truth Tracker
Fake news and misinformation are highly destructive, giving rise to confusion and
uncertainty in society. AI can facilitate the process of fact-checking, aiding information
verification and combating the challenges posed by news fabrication and harmful
propaganda. Truth Tracker aims to use the concepts of machine learning and NLP to
verify whether a piece of text contains fake news or not, and help users understand what
The first phase of the project includes collecting and cleaning textual data, which will serve
as the foundation for model training. The libraries used for data collection are requests,
Beautiful Soup, Selenium, regex, and Pandas. The text data is analyzed using NLP
techniques, and ensemble machine learning models are trained on the augmented
dataset to classify results. The libraries used are scikit-learn, TensorFlow, spaCy, and
PyTorch.
The second phase of the project is focused on creating a web application to classify and
visualize the results and keeping a log of user activity. The tools used for the web
application are Django, HTML/CSS (Bootstrap CSS), JavaScript, and Flask. By the end of
these phases, we aim to have a system capable of identifying and flagging fake news with
an innovative user experience.
Technology Used:
Python, scikit-learn, spaCy, Django, Flask,
Firebase, PyCharm, Visual Studio Code
Supervisor Name:
Ms. Hina Binte Haq
Group Members:
Maliha Masud (i20 - 2606)
0313-6665397)
Rafia Maqbool (i20 - 2464)
0336-5929656)
Asraa Zahoor (i20 - 0861)
0331-5594243)
UNDER-SURVELLENC
The "Under Surveillance" project aims to enhance security and monitoring through a comprehensive
surveillance system. There are two views of this app – Child View and Parent View. Parent View offers a
comprehensive monitoring interface for parents or guardians. It includes GPS tracking of the child's location,
the ability to set up safe and danger zones, instant notifications for breaches, and access to a detailed history
log of the child's movements. Parents can manage settings, receive alerts, and monitor their child's safety in
real-time through this dedicated view. The Child View on the smartwatch features an SOS button that is
designed to trigger immediate action in emergency situations. When activated, the SOS button initiates a call
and sends an SMS to the parent's device, alerting them to the child's distress. Simultaneously, the smartwatch
continuously transmits audio and location data to the parent's device, ensuring that the parent remains
informed of the child's whereabouts and situation in real-time. This comprehensive approach to emergency
communication and monitoring enhances the safety and security of the child, providing parents with peace of
mind knowing they can swiftly respond to any urgent situation.
Features Included
•
Real-time Audio Transmission: Continuous transmission of audio from the child's surroundings to
the parent's device, providing live monitoring capabilities.
•
Location Tracking: GPS-enabled tracking of the child's location in real-time, allowing parents to
always know their child's Location.
•
Call and SMS Alerts: Automatic generation of calls and SMS messages to the parent's device
when the SOS button is activated, ensuring prompt notification of emergencies.
•
Define Safe and Red Zones for Child and receive alerts if child enters red zone.
•
Analyzation of child Audios using Artificial Intelligence.
Technology Used:
Java, Kotlin, Flutter, Android Studio
Supervisor Name:
Dr. Qaiser Shafi
Group Members:
Usama Shafique (19I-0557)
0316-8072474
Abdul Rehman (19I-0568)
0333-5660033
Muhammad Iqbal (i19 - 0576)
03015679327
AdCen
UniRecruit is a transformative web platform aimed at revolutionizing university job fairs by
leveraging Natural Language Processing (NLP) to match student skills with employer
requirements, streamline interview scheduling, and enable remote participation. This
innovative solution addresses the challenges faced by final-year students and recruiters,
providing students with more relevant opportunities and recruiters with access to qualified
candidates while reducing time wastage. By empowering students, recruiters, and Career
Service Offices (CSO) with data-driven insights, UniRecruit enhances career services
effectiveness and broadens the reach of job fairs. The platform's scope includes user
account management, CV creation, recommendation systems, scheduling, communication
tools, and analytics. Additionally, UniRecruit provides CSOs with management capabilities,
allowing them to generate and manage student CVs, and create a graduate directory
through the portal. This comprehensive approach aims to optimize the university job fair
experience, making it more efficient, inclusive, and cost-effective for all stakeholders
involved.
Technology Used:
Node, React, Express, SQL, AWS, Flask
Supervisor Name:
Dr. Ahmad Raza Shahid
Co-Supervisor Name:
Dr. Khubaib Amjad
Group Members:
Muhammad Hashir (i20 - 0440)
03005008444
Abdullah Saqib (i20 - 0458)
03215162770
Rayed Saeed (i20 - 1822)
03368256177
Ustaad
Ustaad aims to develop a comprehensive learning platform catering to first year
programming students seeking to strengthen their coding fundamentals. This application
will offer a user-friendly interface facilitating both self-paced learning and assisted learning
through personalized lesson plans. So the app caters to students needs and requirements
and helps them learn using it.
Key features include:
● Automated syntax and logical error detection using an in-app compiler.
● Progress tracking and analysis tools will generate insightful reports.
● Daily coding exercises, increasing in complexity, will challenge users within their
skill range.
● A teacher collaboration mode will allow instructors to add in questions for the
student to solve.
● Personalized lesson plan according to student’s progress to push them to practice
the areas they are weak in
Technology Used:
Django, React JS, Python, My SQL, VS
Code
Supervisor Name:
Dr. Hassan Mujtaba
Mr. Saad Salman
Group Members:
Zainab Qasim (20i-0631)
(+92 345 3050838)
Maria Ahmed (20i-2451)
(+92 333 0447030)
Noorain Tahir (20i-0517)
(+92 322 5079080)
VisualTeach
VisualTeach is a collaborative virtual teaching web platform which aims to use technology
to make learning an exciting experience for young minds. It aims to address the particular
difficulties experienced by teachers in imparting fundamental knowledge to kids between
the ages of 3 and 9. Our platform is dedicated to providing a vibrant and engaging learning
environment through an interactive canvas, real-time collaboration and real-time chats. The
primary focus is free-hand drawing to enhance object generation, through which effective
communication of concepts is made possible. Furthermore to maintain the decorum of the
virtual class, the teacher can give canvas and chat access upon student request, which is
otherwise
disabled.
Features include:
− Free-hand sketch to enhanced object generation
− Real-time collaboration between meeting participants
− Real-time chat between participants
− Canvas save and retrieve by teacher who initiated the session
− Canvas and chat permissions by teacher to allow students to access chat and
canvas which is otherwise disabled
Technology Used:
MERN, Pytorch, Javascript, Python, Flask,
Git
Supervisor Name:
Ms Noor ul Ain
Group Members:
Samaha Anwar (i20 - 0424) Cell# 0322
8556644
Haissam Bhaur (i20 - 0445) Cell# 0305
3604080
Ali Imran (i20 - 1763) Cell# 0312 9671532
Virtual Tennis Experience (VTX)
This project's scope is to develop a 3D reconstruction system that utilises a single camera
footage (monocular) to capture real-world tennis gameplay and transform it into an
immersive virtual reality (VR) experience. The proposed solution aims to provide tennis
enthusiasts with a unique and engaging way to experience the game, allowing them to
virtually step into the shoes of a live audience and relive their favorite matches.
The main functionalities of the project include:
1. Camera Calibration: The system will incorporate camera calibration techniques to
accurately determine the intrinsic and extrinsic parameters of the single camera used for
capturing the gameplay. This step will ensure precise reconstruction of the 3D scene.
2. Feature Extraction: Computer vision algorithms will be employed to extract relevant
features from the monocular footage, such as player positions, ball trajectories, and court
dimensions. These features will serve as the basis for subsequent stages.
3. 3D Reconstruction: Utilizing the extracted features, a 3D reconstruction of the tennis
court, players, and other game elements will be generated.
Technology Used:
Python, Unity, Blender, YOLOV8,
Keras, TensorFlow, OpenCV, CVAT
Supervisor Name:
Dr. Adnan Tariq & Dr. Faisal Cheema (Co)
Group Members:
Muhammad Rohaan Atique (i20 - 0410)
Ahmed Moiz (i20 - 2603)
Marrium Jillan (k20 - 1748)
Zariqo
Zariqo is a groundbreaking web and mobile application transforming the livestock trading
industry. Serving as an all-inclusive online marketplace, it merges traditional farming
methods with cutting-edge technology. With Zariqo, users seamlessly buy and sell
livestock, ensuring a smooth transaction process.
In addition to the web platform, Zariqo will launch a mobile app, extending accessibility
and convenience to users on-the-go. The app will mirror all web functionalities, providing a
seamless experience across devices.
Features include:
- User-friendly interface for easy trading.
- Secure transaction processing.
- Advanced search and filtering options.
- Urdu voice-based control for intuitive interaction.
- Real-time notifications and an admin dashboard for effective management.
- Seamless integration with web and mobile platforms.
Zariqo's mission is to bridge traditional farming practices with innovative technology,
transforming the trading experience. Its voice-to-text chatbot enhances convenience,
streamlining ad posting for farmers.
Technology Used:
React,Vue js,Go Lang, Tailwind
CSS,Visual Studio
Supervisors Name:
Dr. Muhammad Asif Naeem
Mr. Muhammad Amir Gulzar
Group Members:
Muhammad Adeel (i20 - 0722)  0332-
5300223
Faziha Ikhlaq (i20 - 0473)  0333-5955054
Ali Wahaj (i20 - 1795)  0331-4459672

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