Details:
Title1: Small Object Detection in Gray-Scale Images
Abstract:
This project focuses on developing methods for detecting small objects in gray-scale images, a challenging task due to low contrast, noise, and limited visual cues. Applications include medical imaging, surveillance, and remote s…
Title1: Small Object Detection in Gray-Scale Images
Abstract:
This project focuses on developing methods for detecting small objects in gray-scale images, a challenging task due to low contrast, noise, and limited visual cues. Applications include medical imaging, surveillance, and remote sensing. The project will explore image and signal processing techniques and/or machine learning algorithms to enhance and accurately identify small objects within complex backgrounds. Students will gain hands-on experience in image analysis, algorithm development, and performance evaluation.
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Title2: Integrated Electrical Infrastructure Design and Shop Drawings for a Large-Scale Residential Compound in Accordance with Iraqi and International Standards
Abstract
This project involves the comprehensive design and documentation of the entire electrical infrastructure for a residential compound comprising 2500 houses and associated service areas. The scope includes main power distribution networks, substation layouts, medium and low-voltage distribution, street lighting, earthing systems, and centralized backup power facilities such as generators and UPS systems.
The project will also cover Load assessments, transformer sizing, voltage drop calculations, and network selectivity studies will be conducted to ensure system reliability and regulatory compliance.
All designs will adhere to Iraqi electrical codes alongside international benchmarks including IEC, NEC, BS, and IEEE, with a comparative review of standards from neighboring countries (KSA, UAE, Egypt). The student will utilize design and simulation software such as AutoCAD, DIALux Evo, and other relevant tools to develop comprehensive shop drawings and installation guidelines.
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Title3: Real-Time Mobile Robot Localization Using Wi-Fi CSI Geometric Trilateration in Line-of-Sight Indoor Environments
This project focuses on the development of an innovative indoor tracking system that locates a moving toy robot using ordinary Wi-Fi radio waves. Traditional robotic navigation relies heavily on expensive hardware like LiDAR sensors or digital cameras, which require heavy computing power and fail in dark or smoky rooms. This project introduces a low-cost alternative by using standard Wi-Fi microcontrollers to measure signal behavior directly from the air.
The setup uses three stationary Wi-Fi transmitters placed in the corners of a room and a single Wi-Fi receiver mounted on the moving toy robot. As the robot moves, it listens to the incoming signals, measures how the radio wave energy naturally weakens over distance, and sends this data to a laptop. A Python program then applies standard geometric formulas to calculate exactly where the robot is located and plots its live movement on a digital map. Because the system relies entirely on geometry and physics laws, it does not require complex artificial intelligence or machine learning.
What the Student Will Learn
This project is highly educational because it bridges several core areas of engineering and computer science, allowing an individual student to develop highly marketable, practical skills:
Embedded Systems & IoT Hardware: The student will gain hands-on experience configuring wireless microcontrollers, working with radio frequencies, and understanding how hardware handles low-level wireless data.
Core Python Programming: The student will strengthen their software development skills by writing data pipelines, managing live data streams, and building interactive graphical interfaces from scratch.
Applied Mathematics & Physics: The student will see textbook concepts come to life by applying linear algebra, trigonometry, and radio wave physics to solve real-world navigation challenges.
Signal Processing & Filtering: The student will learn how to deal with real-world sensor noise by designing digital mathematical filters to smooth out raw data.
Hardware and Software Requirements
The project is built using affordable, accessible tools that are easy for a single student to manage:
Hardware: 4x ESP32-S3 microcontroller boards with antennas, 1x basic toy robot car chassis kit, 3x portable USB power banks, and a standard student laptop.
Software: The Arduino IDE (to program the microcontrollers) and a Python development environment.
