Effat University Repository
Effat University Institutional Repository
Welcome to the Effat University Repository, a service of Effat Library and Cultural Museum. This repository provides global and open access to scholarship and research output created by Effat University faculty, graduate and undergraduate students.
While the University Repository is accessible to the public, submission is limited to Effat University community.
If you have any questions, please email us at repository@effatuniversity.edu.sa
Recent Submissions
Publication Drone-Based AI System for Real-Time Hazard Detection and Crowd Safety During Hajj and Umrah(Effat University)Mass gatherings like Hajj and Umrah, which draw millions of pilgrims annually to Mecca, present complex safety challenges due to extreme crowd density, high temperatures, and rapidly evolving risk environ ments. Traditional surveillance methods, like CCTV and manual monitoring, are generally inadequate for real-time response. In this report, we present the development and evaluation of an AI-powered drone system selected to detect threats and improve crowd safety during Hajj and Umrah. Integrat ing drone-based live monitoring and deep learning algorithms is proposed to identify critical threats like overcrowding, associated heat stress, and medical emergencies. We developed a custom application to perform real-time hazard classification, emergency alerting, and centralized data visualization. We trained an augmented dataset of Hajj-related images with real and synthetic images using the deep learning model that includes YOLOv5 for object detection, U-Net for segmentation, and ResNet50 for severity analysis in the developed Android application. With edge deployment using Raspberry Pi and NVIDIA Jetson Nano, the system operated for its accuracy promise in low-connectivity, high-density en vironments, with a latency of less than two seconds. Experimental results demonstrated high accuracy: Fire hazards, crowd congestion, and medical emergencies were 92.3%, 88.7%, and 90.1%, respectively. It consists of a scalable backend, a mobile dashboard, and an alert notification system for ease of use and operational reliability for emergency responders and drone operators. The project fills significant gaps in existing surveillance systems by adding real-time responsiveness, AI-based prediction, and inte gration with ground crews. This system aligns with Saudi Vision 2030’s aspiration to improve the safety of pilgrimage and achieves a new benchmark in large-scale event safety management. Further research includes extending hazard categories, including swarm drone intelligence, and increasing compatibility between platforms for deployment on a larger scale internationally at mass gatherings.Publication DOES IT HURT TOO BAD TO LOOK AT ME?(Effat University)"Does It Hurt Too Bad to Look at Me?" is a 10-15 minute drama fiction short film film that delves into the intricate dynamics of love, identity, and familial influence. The narrative unfolds as Merna, a 22-year-old woman, embarks on a transformative road trip with her fiancé, Amr, to visit his family out of city. The journey serves as a metaphorical exploration of Merna's internal struggles, shaped profoundly by her connection with her father.Merna's father, a symbol of strength and guidance, stands in contrast to Amr's indecisive and weak personality, setting the stage for a heartfelt examination of the impact of paternal influence on romantic relationships. The film intricately navigates the complexities of Merna's psyche, revealing her apprehension about losing herself in the union with Amr, who, in his pursuit of acceptance from his mother, seeks to mold Merna into someone she is not. As the road trip unfolds, Merna grapples with the tension between her father's encouragement of independence and self-discovery and Amr's desire for conformity. The film skillfully captures the emotional distance between the characters, emphasizing their struggles to connect and communicate intimately. Merna, a dominant force in their conversations, wrestles with the idea of ending the relationship, creating an atmosphere of uncertainty that permeates the journey.Publication Smart Multifunctional Kitchen Appliance(Effat University)Publication Tayaqn(Effat University)Diabetes has become a significant global health concern, demanding innovative solutions for early detection and effective management. Traditional machine learning models typically rely on centralized data aggregation, raising substantial privacy issues and compliance risks. This project, Tayaqn: An AI-Driven Diabetes Prediction System Using Federated Learning Architecture, introduces a novel framework that employs Federated Learning (FL) to overcome these challenges. FL allows for secure, decentralized model training, ensuring sensitive health data remains local while enabling collaborative learning across diverse datasets. The system integrates advanced machine learning and deep learning techniques with robust privacy-preserving mechanisms, achieving high predictive accuracy while safeguarding data security. By combining scalability, regulatory adherence, and user-friendly design, this project provides a transformative solution for enhancing early diagnosis and personalized diabetes management, equipping both patients and clinicians with actionable insights for better healthcare decision-making.Publication The Role of REITs in Saudi Arabia's Real Estate Sector:(Effat University)This paper examines the critical role of Real Estate Investment Trusts (REITs) in Saudi Arabia’s rapidly evolving real estate sector within the framework of Vision 2030. Introduced in 2016, REITs have transformed the investment landscape by democratizing access to real estate assets, aligning with the Kingdom’s broader goals of economic diversification and modernization. The study highlights the contributions of REITs to market growth, particularly in enhancing investment accessibility, liquidity, and regulatory transparency, while providing steady income streams to investors. It also addresses significant challenges such as asset concentration, regulatory constraints, and market volatility. The research conducts two performance analyses of Saudi REITs to assess their contributions to the real estate market and economic growth. The first analysis evaluates key financial metrics such as NAV, dividend yields, and occupancy rates, providing a comprehensive view of REIT performance. The second employs research-based models, including Sharpe, Treynor, and Jensen's ratios, to measure risk-adjusted returns, portfolio efficiency, and performance against expected market returns. Findings indicate a mixed performance, with certain REITs excelling in income generation and portfolio resilience, while others struggle with inefficiencies and external pressures. By aligning with Vision 2030 goals, REITs are positioned to contribute significantly to economic stability and infrastructure development, despite needing improved diversification and risk management strategies. This research underscores the strategic importance of REITs in fostering sustainable economic growth in Saudi Arabia’s dynamic real estate sector.
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