ABDULLAH ALQAHTANI

I am a final-year Computer Engineering student with a strong foundation in Artificial Intelligence, Network Security, and a deep passion for IoT and embedded systems. My academic journey is marked by a final project that entailed developing a sophisticated real-time vehicle detection and parking occupancy system using technologies like Raspberry Pi, YOLOv8, and OpenCV, alongside programming languages such as Python, Java, and C. This project not only honed my technical skills in software and hardware integration but also emphasized the practical application of theoretical knowledge. My achievement of securing second place in the NASA Space Apps Challenge in Riyadh, which focused on creating environmental solutions with cutting-edge technologies, further underscores my ability to tackle real-world problems with innovative solutions and collaborative teamwork. Eager to take on a challenging CO-OP position, I aim to delve deeper into the intersection of AI and cybersecurity, contributing to advanced projects and expanding my expertise in these dynamic fields.

• Real-time Vehicle Detection System

Engineered an advanced system using Raspberry Pi, YOLOv8, and OpenCV for real-time vehicle detection and parking occupancy monitoring, leading to improvement in parking management efficiency and space utilization. Overcome challenges related to real-time data processing and accuracy in diverse weather conditions, enhancing system reliability and performance.

• Smart Garage Door System

Engineered a universally compatible smart garage system using Raspberry Pi, YOLOv8, and OCR technologies, integrated with a robust networking framework to enable remote access and control via smartphones. Addressed challenges in network security and reliability, implementing robust protocols to ensure secure and seamless user interaction while enhancing vehicle recognition capabilities for efficient parking management.

• Conversational Summary Bot

Developed a sophisticated bot leveraging Large Language Models (LLMs) for efficient processing and summarization of spoken and written meeting content, using Voice‑to‑Text (VTT) and Text‑to‑Voice (TTV) technologies. Tackled the complexities of accurately processing diverse dialects and technical jargon, resulting in a reduction in meeting follow-up time and streamlined task management for professional teams.

• NASA Space Apps Challenge: Achieved 2nd Place and Global Nominee status in Riyadh for leading a pioneering project addressing fire prevention and desertification. My role involved orchestrating a team to develop an integrated solution using drones, AI, and satellite imagery. This project not only advanced environmental preservation efforts but also showcased my ability to navigate and synthesize complex data streams for real-time analytics and environmental monitoring, demonstrating innovative problem-solving and technical leadership.