In the high-pressure setting of ambulance-based care, conventional methods relying on verbal communication or identification documents often lead to errors and delays. To address these challenges, our proposal involves integrating biometric identification techniques using fingerprint scanning to retrieve patient data. The application ensures seamless integration with healthcare providers’ systems, guaranteeing rapid and secure access to essential patient data, particularly emphasizing its utility within the time-sensitive ambulance environment. This project is motivated by the urgent need to streamline patient data retrieval during medical emergencies, particularly for unconscious individuals. Existing systems are fragmented, causing delays and impeding healthcare providers from delivering timely and suitable treatment. By leveraging biometric technology, our goal is to significantly enhance response times and elevate patient care, ultimately saving lives. The significance of this project aligns with Saudi Arabia’s Vision 2030 goals of transforming the Kingdom’s healthcare system. It is also in harmony with the United Nations’ Sustainable Development Goals, particularly SDG 3, which seeks to ensure healthy lives and promote well-being for all. Anticipated outcomes of this project include the development of an advanced ambu lance application for efficient patient data retrieval during emergency medical care. This is expected to improve response times, enhance patient data security and privacy, and provide practical recommendations for real-world implementation.

The Internet of Things (IoT), which has blended into modern society and revolutionized how we engage with technology in theoretical and practical contexts, has become an integral part of our daily lives. It has become a key player, actively helping to protect our devices and ensure their best performance. Our project intends to create a cutting-edge IoT-based security management system in response to the current issues in smart houses. Innovative solutions are required because protecting expensive equipment and the environment is becoming increasingly important. In this project, we embrace a wide range of solutions that make use of specialized tech nologies, such as visual monitoring systems, fire warning mechanisms, gas detection systems, water leak detection systems, and detecting sensors. These technologies col lectively contribute to creating a secure and responsive environment. The integrated system will include several crucial parts, including an embedded system, a database system, a thorough log system, and a flexible control program. Data collection for important factors including temperature, humidity, motion, smoke, the presence of water, and voltage fluctuations will be entrusted to a network of sensors. The data will then be processed and examined to guarantee the highest level of security and effectiveness. To further enhance the system’s responsiveness, we will implement an alert notification system to keep owners updated on any anomalies or potential dangers through email alerts and SMS messaging. It will enable prompt action to mitigate risks and preserve the integrity of the smart houses Our innovative IoT-based security management system for smart houses is being developed in line with the goal of fostering the global transition to smart homes by designing and developing sustainable, high-tech living environments. Achieving Sustainable Development Goal 11 (SDG 11), which is to make cities and human settlements inclusive, safe, resilient, and sustainable, is directly impacted by our work. Our goal is to create intelligent ii and secure living environments that foster harmony and well-being by leveraging IoT technologies to increase efficiency and security. Through the implementation of eco-friendly and energy-efficient solutions, our initiative also indirectly supports a number of other SDGs, including SDG 13 (climate action) and SDG 7 (affordable and clean energy). By guaranteeing the responsible use of resources in smart home opera tions, we also contribute to SDG 12 (responsible consumption and production).Our initiative directly contributes to Vision 2030’s objective of enhancing Saudi Arabia’s technological capabilities in the field of innovation and technology. By integrating IoT technologies into smart homes, we help achieve the vision’s objective of establish ing the nation as a center of innovation and a pioneer in cutting-edge technologies. Essentially, our creative strategy makes use of Internet of Things technology to offer smart homes a safe, secure, and intelligently controlled environment. In keeping with the vision of smarter and more resilient living spaces, we seek to improve the general quality of life for individuals and families in a sustainable and technologically advanced manner by protecting valuable assets and maximizing resource utilization.

The increasing prevalence of SMS spam poses a significant challenge as mobile devices have become integral to daily life. Spam messages target individuals and can lead to high impacts, as they can evolve into phishing attacks or even social engineering. Our project holds significance in contributing to the safety of the community by reducing the number of spam victims. It aims to improve existing spam filtering solutions to provide a safer and more user-friendly experience, thereby reducing the vulnerability of users to spam and phishing attacks. Through state-of-the-art analysis, we identified a common gap: the lack of real-world application testing. In our methodology, we utilized the TensorFlow Lite Model Maker library to simplify the adaptation and deployment of an NLP neural network model text classification model on mobile devices. Our result is a meticulously designed user-friendly application that flags spam messages in real-time, o ering a safer messaging experience.

The study of password-cracking techniques remains a fundamental pursuit within the realm of information security, primarily due to the ever-present threat posed by weak passwords. This project introduces cutting-edge approaches and methodologies aimed at improving password-cracking precision. It explores various techniques, including brute force, dictionary attacks, machine learning, and contextual word lists, with the primary objective of enhancing the e - ciency and precision of password bypassing. Specific goals include evaluating the performance of di↵erent cracking methods and technologies. The project outlines novel methodologies and approaches for password ex- ploitation, discusses their implementation, and provides insights from experi- mental results. The research addresses the pressing need for improved password security measures and contributes to digital forensics and criminal investiga- tions by enhancing password-cracking techniques. The findings of this study have practical implications for strengthening password security across various applications and platforms. By synthesizing insights from existing research and proposing innovative methods, this project aims to advance the state of the art in password cracking, ultimately leading to more robust security measures and better protection of sensitive information.

This capstone project proposes a 10 pages screenplay about a fiction story of a Saudi young girl who went through a struggle with her inner self. We see how she surrounded herself with a routine life to ignore the pain that she feels, but one day something inside her embodied in real life to tell her that she has to find the right path and get ready for it. Also, we are going to see how the death of her father was the main reason that makes her give up on her dreams and lose the passion. This project will include the first draft of the script. The thesis consists of the introduction, a brief history about the main character and what distinguishes her; a discussion about the project stages and the story, the logline, tagline and outline, synopsis, structure, storyboard, treatment and script.

The importance of companies taking proactive steps to defend their web applications is growing as the number of web-based threats rises. Utilizing web application firewalls (WAFs) is one such measure. In this study, we investigate the possible advantages of integrating Shadow Daemon into the design of regional start-up businesses to enhance their cybersecurity defence. We start by giving a general review of Shadow Daemon and its features, emphasizing its capacity to recognize and stop typical web application threats like SQL injection, XSS, and LFI. The significance of web application security and the possible repercussions of a successful attack are then covered. Then, we look at the current state of web application security in local start-up businesses, including frequent security flaws and the difficulties they encounter in putting in place workable security measures. Following that, describing the crucial processes required in the implementation process, we suggest a framework for incorporating Shadow Daemon into the architectural design of regional start-up businesses. We also talk about how employing Shadow Daemon might enhance security, lower the chance of data breaches, and boost customer confidence. Finally, we emphasize the value of proactive web application security and the part Shadow Daemon may play in assisting regional start-up businesses to defend their web apps against attacks as we draw to a close. We suggest implementing Shadow Daemon can improve cybersecurity defences and reduce potential security risks for nearby start-up businesses in an efficient and cost-efficient manner.

Nowadays, cellphones are a big part of our daily lives thanks to technology. Today's cellphones can swiftly and simply resolve the majority of issues. Everybody's life has been simpler and easier because of the many social apps, business apps, problem-solving apps, educational apps, and marketing apps, among others. The study intended a solution to deal with a difficulty with recording attendance after the technology. The suggested system is an application that uses QR codes to track employee attendance. Employees must scan their unique QR code to verify their attendance; they are not permitted to share or screenshot this code. The system's identity verification process is covered in the paper in order to prevent bogus registrations. The system handles the monitoring and assessment of every employee's attendance. Each person will receive a QR code in their application to scan when they enter the organization. This is a first effort to assess the system's suitability for application in various settings, including offices, classrooms, and laboratories. Based on the findings and data collecting, it can be concluded that the testbed development for the creation of a smart security attendance system using a QR code has been successful.

Sentiment analysis is critical for comprehending people’s opinions and attitudes regarding fi- nancial applications. The study offered a thorough approach to sentiment analysis utilizing machine learning and deep learning models in this research. Data pretreatment procedures, model imple- mentation, and evaluation are all part of the process. Using the Keras and TensorFlow frameworks, we constructed numerous machine learning and deep learning models such as Naive Bayes, SVM, Decision Tree, BERT, and RNN. The accuracy and F1 score measures were used to evaluate the performance of these models. A thematic analysis was also performed to uncover common themes and subjects in financial application reviews. The findings show that sentiment analysis is useful in analyzing user sentiments and providing insights for improving user experience

With the rapid growth of technology, the world is in hunger for more data, connection, intelligence, and speed. The solution of LoRaWAN sensors promotes the infrastructure of the Internet of Things (IoT). To emphasize, LoRaWAN is a “point-to-multipoint networking protocol” requiring low-power to connect end-devices and manage communication through network gates. This study aims to assess and build a fulfilled system using LoRaWAN sensors to improve the wireless network experience for users in smart cities, specifically tackling agriculture as a testing medium for evaluating data accuracy and more effective transmission of data packets. The method used in this research is based on applying an experiment of a LoRaWAN model using nodemcu (esp32) applied in smart agriculture. Results show that LoRaWAN is a promising technology that can be implemented in several fields and effectiveness over current technologies like Wi-Fi and Zigbee. The study presents a prototype that addresses both strengths and limitations and issues with a plan for multiple industries to immediately put the technology in action in helping existing areas in utilizing the technology. While using cloud computing to transfer data and have accessible, secure and up to date data. Cloud computing is the sharing of data, resources, and software as the Internet serves as an unseen thread that links everything.