Supervisor: Mrs. Payam Wali
Abstract: These days, many of us frequently use websites to access information, check news, browse, and more. This paper describes Charity MS’s core functionality, from browsing projects to managing donations in the admin panel. The platform allows NGOs to find donors easily, enabling more effective donations.
Supervisor: Mr. Bilal Ahmed
Abstract: The project helps users find apartments that meet their demands, manage payments, and contact management easily via a web system, simplifying daily life.
Supervisor: Mr. Bilal Ahmed
Abstract: Automates the current manual laboratory system using hardware and software, allowing secure, long-term data storage and better management of tasks.
Supervisor: Mr. Savriddin Khalilov
Abstract: An online shopping mobile app using Flutter, Dart, and Firebase, providing separate views for public users and admins for efficient product management.
Supervisor: Mr. Mohammad Salim
Abstract: A mobile app showing the zoo map, animal types, ticket prices, and information for visitors, solving navigation and information problems.
Supervisor: Mr. Rebin M. Ahmed
Abstract: Detects face masks using Python and TensorFlow to prevent the spread of COVID-19 with 98.8% accuracy.
Supervisor: Mrs. Payam Wali
Abstract: A web application to help hospitals and users find and reserve ICU rooms efficiently, solving time-consuming manual reservations.
Supervisor: Mrs. Payam Wali
Abstract: Recognizes license plates using neural networks and stores data in SQL-Lite for easy retrieval.
Supervisor: Dr. Taha Basheer
Abstract: A mobile app for psychological monitoring and communication with psychologists, providing free support for anxiety and stress management.
Supervisor: Mr. Mohammed Kamal
Abstract: Explores project management processes for student competitions, integrating planning and control systems for events.
Abstract: A mobile app for plasma donation, connecting donors and recipients efficiently during COVID-19.
Supervisor: Mr. Alaa Ghazi
Abstract: Compares CISSP and CCIE certifications based on cost, duration, requirements, and benefits for cybersecurity professionals.
Supervisor: Mr. Mohammed Kamal
Abstract: A mini IoT self-driving car using Raspberry Pi, Arduino, and neural networks for path prediction and vehicle control.
Supervisor: Dr. Taha Basheer
Abstract: Mobile app for farmers to schedule and manage appointments for truck deliveries using Flutter/Dart and Firebase.
Supervisor: Mr. Mohammed Kamal
Abstract: Improves company network infrastructure with WLC devices, Microsoft Server, and security measures to optimize efficiency and reduce costs.
Supervisor: Mr. Mohammed Kamal
Abstract: Detects social distance using Raspberry Pi hardware components to reduce COVID-19 transmission.
Supervisor: Mr. Mohammed Kamal
Abstract: Designs TIU university networks using Cisco Packet Tracer, applying star topology and backup systems for secure and efficient operation.
Students: Andro Abduljabbar Hawel, Mubin Kordo Sabah, Osamah Jakhsi Hassan
Abstract:
This project presents the development of an automated recycling machine that incorporates state-of-the-art technologies to streamline the recycling process. The machine combines a camera system, machine learning models, servo motors, and a Raspberry Pi controller to accurately identify and sort different types of recyclable materials. By employing machine learning algorithms trained on a large dataset. The initial model yielded a modest accuracy of 33%, highlighting the need for further development. Subsequent iterations of the model resulted in accuracies of 81% and 78%, showcasing incremental progress. The final model, after addressing overfitting challenges, achieved an impressive training accuracy of 85% and an even higher test accuracy of 91%. The successful implementation of the recycling machine underscores its potential to revolutionize recycling practices, reducing human intervention and bolstering sustainability efforts. Future work entails refining the hardware setup, exploring alternative energy sources like solar power, and expanding the model’s classification capabilities to encompass a broader range of recyclable material
Students: Botan Mariwan Nuraddin, Saeb Tahsin Yahya, Eman Hiwa
Abstract:
This study focuses on the computer vision field, in which computers are enabled to identify and recognize images and moving objects just like a person would. Challenges in such studies are primarily caused due to incomplete understanding of the logical vision. To extract high-dimensional data gathered from the real world and create symbolic or numeric information that may be used to make decisions, computer vision includes gathering, processing, analysis, and understanding of computer images. The concept of computer vision has been utilized in this work to build an intelligent system that can predict a person’s age and gender. Using a webcam or inputting an image into the system, the system can predict the age and the gender of the face in the image it sees. If time remains, the system will be applied on OpenCV to let it work and predict the live situation. Moreover, the system can be implemented in a way it counts the number of male and female people it has seen so far. This can be advantageous during fairs and conferences to let the organizers know their visitors better based on age and gender.
Students: Rager Essa Saeed, Zhiar Sulhi Ghazi, Rozhbin Rafiq Fariq
Abstract:
Technology is evolving at a rapid pace. Every day, new innovations, solutions, and issues emerge. It is vital for a technology enthusiast to remain updated on new technologies and challenges. Therefore, there is no better way to accomplish this than to have a reputable tech news source that provides the users with regular updates on the fields of technology such as artificial intelligence, IT project management, cybersecurity risks, machine learning, and so on. As a result, the goal of this research is to create and implement an IT trending news website that offers site visitors the most recent trending news in the technology field and opens a chance for industry professionals and specialists to share their observations and points of view. The website is also created with two dashboards: an admin dashboard for managing the website and an author dashboard for authors to manage their posts. The SDLC (systems development life cycle) method is utilized to create the IT trending news website. The outcome of this research is the IT Trending News Website, which seeks to provide site visitors with the latest trending news in the technology field. This research was completed successfully based on the results of functional tests performed using the Black Box Test method, which reveal that the website’s functionality works as expected
Students: Barzan Rizgar Mirkhan, Danial Salih Omer, Sizar Muhsin Othman
Students: Sipan Nasradin, Ahmad Araz, Abdulmalik Rashid
Students: Yousif Sherwan, Qamar Dhiya, Lava Ahmed
Students: Mohammed Ardalan, Omed Kamal, Mohammed Othman
Students: Alaa Ali Jahfer, Abdulbari Ibrahim Braym, Zhila Khalid Rasool
Students: Ayub Omer, Ala Frsat, Muhammed Swara
Students: Khansa Suad Sabir, Rayan Fahad Mohammed, Rukhsar Taha Zahir
Students: Mahmood Zryan Pasha, Muhamed Wasfi Tahir, Mahmood Dler Ali
Students: Shad Muhammed Taha, Abdullah Khalil, Farahjan Masroor
Students: Mohammad Rizgar Abdulkadir, Mustafa Ali Hussen, Ziryan Barzan Othman
Students: Hewr Dler Ahmed, Anas Bilal Ali, Kamaran Bakhtiar Abdulqadir
Students: Zanar Othman Saeed, Ahmed Sarhang Mohammed, Qasim Luqman Othman
Students: Muhammed Muhsin Hadiatullah, Hezha Muhammed Salih, Awin Mahdi Salih
Students: Ahmad Rajo, Amanj Sawri, Rebin Farsat
Students: Mahshad Malashin, Halwest Sami Ahmed, Tara Shkur
Students: ARAS KAMERAN HUSSEIN, ZHEWAR ALI MUSTAFA, HEVIN FAKHRALDDIN MOHAMMED
Abstract:
This project aims to enhance existing intrusion detection systems by integrating advanced machine learning algorithms. The system can analyze network traffic patterns, detect unusual behavior, and identify potential security threats in real-time.
Students: MARSEL MOFAQ AZO, ONEL NAZAR HABEEB, USAMA SARDAR HAKIM
Abstract:
An interactive website designed to connect orphanages with donors and volunteers. The platform allows users to view children’s profiles, make donations, and track their contributions securely.
Students: ANAS AHMED ILHAMDARWEESH, GONA ADNAN ABDULQADIR, MARYAM CHAWSHEEN HASAN
Abstract:
A mobile and web application that simplifies property searching by enabling users to browse, filter, and contact property owners directly. It includes location-based suggestions and smart recommendations.
Students: AHMED SALAH ISMAIL, AHMED SARKAWT JALAL, MIRAN SANGAR KAKAMEER
Abstract:
This project develops an online calculator that estimates the cost, savings, and efficiency of installing solar panels. It helps users make informed decisions about renewable energy investments.
Students: AHMED ABDULQADIR TAHA, MAHMOOD YOUSIF SABIR, SAHAR HADI QASIM
Abstract:
A digital platform showcasing Erbil’s mosques with historical details, prayer times, and community announcements. It serves as both an informational and cultural preservation website.
Students: MOHAMMAD AMEEN SULEMAN, YOUSIF JAWHIR SAEED, ZAINAB SALAH HAMAD
Abstract:
An augmented reality mobile app that provides interactive tours of Erbil Citadel. Visitors can point their cameras at landmarks to receive virtual information and 3D visuals.
Students: TARA DLER TAHER, WARIN ASWAD AHMED, ZHYAR FARHAD MOHAMMAD
Abstract:
A real-time bus and taxi tracking system that displays vehicle locations and estimated arrival times. The project enhances public transportation efficiency in Erbil.
Students: BANAZ FOUAD AHMED, HIBA BURHAN MIRZA, MATIN YAQUB MUHAMMEDSALIH
Abstract:
A mobile application designed to help users manage their diet and nutrition. It includes calorie tracking, meal planning, and personalized health recommendations.
Students: BANEL ADDAY EWAN, HUDA BAKIR RASHID, MABAST ABDULAZIZ MOHAMMED
Abstract:
An automated system that generates fair and optimized invigilation schedules for university exams. It minimizes human errors and reduces administrative workload.
Students: KIYAN SAEED AHMED, NABIL MOHAMMAD MAROOF, NIAZ FATAH MUHAMAD
Abstract:
This prototype uses image processing and machine learning to recognize traffic signs from real-time video feeds. It assists in driver safety and autonomous vehicle development.
Students: AMANJ AZAD AMEEN, DANYAL OTHMAN FAZIL, SAWA SERWAN HASKO
Abstract:
An AI system that analyzes facial expressions and voice tones to detect customer emotions. It helps companies understand satisfaction levels and improve service quality.
Students: ARAM FARHAD TAHIR, ASHRAF IMAD HASHIM, SARBAND SAYWAN MOHAMMAD
Abstract:
A web platform that allows users to rate and review various media content including movies, music, and TV shows. It provides an interactive and community-driven experience.
Students: AHMAD TARIQ AHMAD, AYAT SARAN ABDULWAHAB, MAHMOOD ZANA FARIS SAEED
Abstract:
A smart control system that automatically adjusts street lighting based on movement and ambient light levels. It reduces energy waste and supports sustainable city development.
Students: IDRIS URFI ABDULLAH, YOUSIF EMYAN AZIZ, ZEDAN SHAKIR KHALID
Abstract:
An internal web system for managing employee leave requests and approvals. It streamlines HR workflows and ensures transparent leave tracking.
Students: HOLAN OMEED K. MOHAMMED, IBRAHIEM HAIDAR SALIM RASUL, AHMED AUDAY AHMED
Abstract:
A research-based project combining natural language processing and computer vision to create an AI robot capable of recognizing objects and responding intelligently to voice commands.
Students: SAVA AHMED MOHAMMED, AYA SORAN MOHAMMED, SHOKH SALIM SABAH
Abstract:
An online platform developed to facilitate charitable donations (Sadaqah). It ensures transparency, connects donors to verified causes, and tracks contributions effectively.
Students: MUBIN SULHI HASAN, MUSTAFA SHERZAD TARIQ, ROZH DLER HAMID
Abstract:
A collaborative web-based platform that connects students and educators for sharing academic resources, research ideas, and online learning opportunities.
Students: EMAN DLSHAD, YUSRA FARHAD, ZAGROS RAMZI
Abstract:
This project focuses on collecting and labeling a dataset of handwritten Kurdish characters. The dataset supports handwriting recognition research and AI model development.
