Effat University Repository

Recent Submissions

  • Publication
    Airventra:
    (Effat University) Alawlaqi, Noor; Almashharawi, Maha; Alsalamah, Mashael; ElKafrawy, Passent; Computer Science
    Modern warehouses face growing pressure to operate e"ciently while maintaining inventory accuracy and minimizing human error. This project presents AirVentra, a smart warehouse management system designed to optimize batch storage location rec ommendation, automate inventory scanning, and streamline task delegation. The system integrates multiple AI-driven modules including computer vision, topic modeling, and real-time decision support. Barcode detection is achieved using a YOLOv11n-based model, which demonstrated superior accuracy (precision: 0.966, recall: 0.967, mAP50: 0.980) and faster inference time (0.9 ms) compared to earlier alternatives. For intelligent storage location recommendation, the system employs a BERTopic classification model that semantically categorizes batches based on their textual descriptions. BERTopic out performed LDA and NMF with an overall classification accuracy of 97% and an F1-score of 0.97 across categories. A dual-phase inventory scanning process enables employees to first verify batch placement and then assess shelf-level conditions such as overfill, un derfill, or expired items. Detected issues automatically trigger task assignments, with the system selecting the least-loaded employee to handle the resolution. To support future automation, we conducted experiments on drone path planning using several algorithms. The Genetic Algorithm produced the most e"cient route (584.77 meters), outperform ing Christofides, Nearest Neighbor, and Spanning Tree approaches in traversal time. A web-based system was developed using Laravel and Flask to manage scanning pipelines, user interfaces, and real-time alerts. Results demonstrate that combining machine learn ing, computer vision, and automation within a unified system can significantly improve warehouse reliability and reduce manual workload. Future work will expand toward full autonomous UAV-based scanning and adaptive retraining of models based on evolving batch metadata and operational patterns. This project is built upon the foundational work presented in our accepted paper A.1 at the International Symposium on Data Intelligence and Applications (ISDIA-2025). The paper, which outlines our initial methodology and experimental setup, is scheduled to appear in Springer’s Lecture Notes in Networks and Systems (LNNS) series by November 2025
  • Publication
    Sustainable IoT Security:
    (Effat University) Bajunaid, Leen; khan, Sohail; Computer Science
    As the Internet of Things (IoT) continues to grow, ensuring the security of interconnected devices becomes increasingly vital. Hythrmia is an advanced IoT security scanning tool developed to identify vulnerabilities in smart devices across multiple communication protocols, including WiFi, Bluetooth, Z-Wave, and Zigbee. The tool scans local networks to detect potential security risks, such as open ports, weak passwords, outdated firmware, and known vulnerabilities (CVEs). Currently, Hythrmia focuses on WiFi and Bluetooth devices, o↵ering real-time discovery and analysis of connected devices. The tool employs Nmap for port scanning and Hydra for brute-force testing to identify vulnerabilities like weak or default passwords. Additionally, it integrates the Vulners API to cross-reference detected devices with a database of known vulnerabilities, enabling users to quickly assess and mitigate security risks. Initial tests demonstrated show that Hythrmia’s WiFi and Bluetooth scanning capabilities e↵ectively detected devices with weak or default passwords. The tool successfully identified several common vulnerabilities, across a range of smart devices. For example, during a test involving several Dahua cameras, the tool was able to exploit weak passwords and gain unauthorized access to camera streams, highlighting significant security gaps in default configurations. These findings underscore the importance of securing IoT devices within local networks. Although the tool’s full potential includes support for Z-Wave and Zigbee, the current focus on WiFi and Bluetooth has already demonstrated Hythrmia’s significant contribution to enhancing network security. This project highlights the increasing demand for IoT security tools and demonstrates how Hythrmia serves as an accessible solution for users to proactively manage and secure their smart environments. Future work will aim to expand support for additional protocols, introduce automation features for continuous scanning, and enhance the overall e↵ectiveness of the tool as a comprehensive IoT security solution
  • Publication
    The Kingdom’s Pavilion EXPO 2030
    (Effat University) Turkistani, Rfal; Mohammed, Mohammed F. M.; Architecture
    This thesis is structured into five subsequent chapters. Chapter one introduces the thesis topic and provides a project proposal. Chapter two provides comprehensive case studies along with a detailed field study analysis. Chapter three selects a site for the proposed project based on several criteria relevant to the city. Chapter four develops a comprehensive site program and building program for the selected site. While the first four chapters include the pre-design documentation, chapter five includes the final design documents presented and discussed in the final jury.
  • Publication
    REHABILITATION CENTER FOR JUVENILE OFFENDERS
    (Effat University) Albaiti, Sara; Refaat, Ahmed Mohamed; Architecture
    This thesis presents the design and development of a Rehabilitation Center for Juvenile Offenders, also known as a Social Observation House, in alignment with Saudi Arabia’s Vision 2030. The project aims to address the growing need for specialized facilities that focus on the rehabilitation, education, and reintegration of youth involved in criminal behavior. Through comprehensive research and analysis, the thesis explores the social, psychological, and architectural dimensions of juvenile rehabilitation environments. The proposed center is designed to create a secure yet therapeutic space that supports emotional healing, behavioral correction, and personal development. Key components of the design include educational areas, therapeutic zones, recreational facilities, and secure accommodation units, all integrated to form a holistic and supportive environment.
  • Publication
    AI Enhanced Cyber Policy Assistant for IT Team
    (Effat University) Bazarah, Reem; Mahfouz, Sadeem; khan, Sohail; Computer Science
    Small and medium-sized companies (SMCs) in Saudi Arabia face growing cyber- security challenges due to limited in-house expertise, inadequate infrastructure, and the increasing complexity of digital threats. Unlike large enterprises with dedicated security teams, most SMCs rely on general IT sta↵ and lack the tools to e↵ectively manage risks such as data breaches, ransomware, and regulatory non-compliance. This project proposes a user-friendly, AI-powered web application specifically de- signed to support Saudi Arabia’s SMCs in navigating cybersecurity policies and practices. At its core is a chatbot that delivers personalized cybersecurity guid- ance, helping users understand and meet the requirements of national regulations particularly those set by the Saudi National Cybersecurity Authority (NCA)[10] while also supporting alignment with international standards.

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