HNS-RE2SD
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Higher National School of Renewable Energies, Environment and Sustainable Development
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Item Chimie 1 : Structure de la matière(2022) CHABANI SoniaChemistry is considered an integral part of the history of science and the contemporary world. In general, chemistry is the science that studies the composition, reactions, and properties of matter by examining the atoms that make up matter and their interactions with each other. This course material is primarily intended for first-year preparatory class students. It complies with the new reform program that came into effect in 2015. It is a powerful educational tool for students of science and technology or other specialties such as materials science, medicine, pharmacy, and biology to learn general chemistry. This course covers theoretical developments and uses mathematical tools to understand certain concepts of structural chemistry.Item Fonctions électroniques 1(2025-06-01) Meddour FayçalThe objective of this course is to acquire basic theoretical knowledge of various electronic functions necessary for designing and implementing a transmission system. Topics covered include analog filters, amplitude, frequency, and phase modulation and demodulation, the impact of noise on the performance of these circuits, PLLs, etc.Item New Tree Quantum Key Agreement Protocol and its Impact on IOT Networks(2024-06-15) EMZIANE MalakThe Internet of Things is revolutionizing the way we interact with the world around us, creating a network of interconnected devices that communicate and share data easily. Quantum Key Agreement represents an exciting new area of cryptographic research, leveraging the principles of quantum mechanics to achieve secure communication. Unlike classical cryptographic methods, which rely on mathematical complexities, QKA utilizes the properties of quantum particles to ensure security. This makes QKA particularly resistant to the future improvements expected with the advent of quantum computing. In this dissertation, we explore the integration of a New Tree Multiparty Quantum Key Agreement within IoT networks. This protocol not only facilitates scalable key management but also enhances the overall security posture of IoT systems.Item Sustainable Water Monitoring - Harnessing IoT and AI for Real-time Leak Detection and Water Quality Prediction(2024-06-15) DJEGHABA Mohammed Baha Eddine; BENTAHROUR AbirWater is an essential resource that supports both ecological sustainability and human survival, necessitating robust management strategies to meet increasing global demands, address climate change, and tackle environmental challenges. This thesis investigates the evolution of water supply monitoring systems, transitioning from traditional manual methods to advanced technologies using the Internet of Things (IoT) and Artificial Intelligence (AI). The central focus is on developing QoW-Pro, an IoT-based system that enhances water quality assessments and leak detection through AI algorithms. This system enables real-time data collection, predictive modeling, and anomaly detection, improving water resource management decisions. By integrating IoT with AI, the research offers a scalable and adaptable solution for various environments, aiming to ensure sustainable water management and quality for future generations.Item Smart Electric Wheelchair for Real-time Obstacle Avoidance(2024-06-15) DIFALLAH FayrouzThe project involves developing a Smart Electric Wheelchair (SEW) to improve mobility and independence for individuals with physical disabilities. It uses a Raspberry Pi 4 Model B for processing, an L298 dual H-bridge motor driver, also ultrasonic sensors for obstacle detection, and servo motors for sensor positioning. Machine learning algorithms enhance real-time obstacle prediction and navigation safety. The system includes a robust communication subsystem and an Android application for user control.Item AI-Based Security System Using YOLO Algorithms(2024-06-15) CHAHI Kamel EddineThroughout the first chapter of this thesis, we have presented a comprehensive examination of security systems, addressing crucial considerations essential for designing robust solutions. We have highlighted key challenges faced by these systems, notably human errors leading to the oversight of significant events, the inherent complexity of system architecture, and the difficulties encountered during system extension and updates. This study offers an effective solution to the aforementioned challenges. By utilizing an AI card such as the Nvidia Jetson Nano, existing security camera systems can be transformed into intelligent and robust entities. This integration enhances their ability to process relevant events with high accuracy while potentially eliminating the need for additional equipment, replaced instead by the fusion of AI algorithms with the visual data captured by the cameras. The YOLOv8 model was trained using a large dataset downloaded from the Roboflow platform. Its images are labeled with seven classes: customer bagpack, null, product, product-picked, regular, shoplifting, and shopping cart. With a large configuration (43.7M parameters), we have obtained a good accuracy (0.9) and satisfactory convergence. However, during testing in different retail environments, challenges arose in accurately detecting certain products.Item AIoT Based Smart Energy Monitoring System(2024-06-15) BOUTELIS Moussaab; ABDERRAHMANI IssamThis project develops an AI-driven IoT-based Smart Energy Monitoring System to enhance energy efficiency in residential areas. Utilizing ESP32-CAM devices, it captures real-time images of utility meters and employs AI techniques like Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks to analyze and forecast energy consumption patterns. The system aims to help homeowners optimize resource use, minimize waste, and reduce expenses by providing immediate data insights and predictive analytics. It also improves utility companies’ data accuracy and customer trust through transparent reporting. The user-friendly web application is built on the Laravel framework, facilitating interactive data visualization. This initiative not only pushes technological boundaries but also promotes resource efficiency and scalability. Looking ahead, the project plans to integrate advanced machine learning algorithms, expand IoT capabilities for a fully connected home, and bolster security features, all contributing significantly to global sustainability objectives.Item IIoT-Driven AI for Electrifcation Automation(2024-06-15) BOUTAA AliIn the midst of the AI era, the industrial domain is witnessing the increasing prominence of AI. This project aims to integrate AI into the Siemens system, taking a significant step towards Industry 4.0. By harnessing the power of AI, we will revolutionize electricity consumption prediction, enabling organizations to make informed decisions and optimize their energy usage. Our strategic approach includes analyzing unique business needs, preparing data, developing AI models, deploying them seamlessly, and continuously monitoring and improving their performance. We will leverage AI techniques such as artificial neural networks, genetic algorithms, and expert systems to transform the energy sector and support the growth and stability of Industry 4.0. This integration will empower organizations to make informed decisions, reduce their carbon footprint, and optimize energy usage, ultimately contributing to a more sustainable future. This project will enhance operational performance and productivity, increase competitiveness in the Industry 4.0 landscape, and pave the way for a more sustainable and technologically advanced industrial sector by streamlining decision-making processes and improving energy efficiency.Item Intelligent Road Violation Management System(2024-06-15) BERGHOUT Imene; TERCHI ChaimaThe development and implementation of an intelligent road infrastructure management system raises the question of practices in the field of artificial intelligence, because of its intrinsic ability to adapt to current issues, which can make a major contribution to a preventive strategy aimed at reducing accident rates and offences, improving road safety and promoting responsible driving practices. This dissertation has answered these questions and objectives by: • Drawing up an intelligent system for integrating all the processes required as innovative and sustainable solutions in the field of transport; • Implementing the system based on appropriate programming for the adoption of innovative solutions based on case studies. At the end of this research, it was shown that the exploration of the system developed offers, on the one hand, local authorities intelligent management of road user offences thanks to the integration of the central web platform and, on the other hand, facilitates administrative procedures for users via the development of a user-friendly mobile application. In addition, the modular and scalable system design allows for future integration of emerging technologies, such as smart city infrastructure, autonomous vehicles, and advanced traffic management systems, ensuring relevance and adaptability in an ever-changing technological landscape. Finally, the successful implementation of this intelligent road infrastructure management system offers the potential to significantly reduce the human and economic cost of road accidents, promote compliance with traffic laws and contribute to a safer, more sustainable transport ecosystem.Item AIoT Based Green Road System for Smart Cities(2024-06-15) BENGUESSOUM Ahmed Rached; BOUNAAS YacineIn the last few years, Algerian cities have been facing increasing traffic congestion due to rapid urbanization and population growth. This congestion translates into severe delays, accidents, and environmental pollution, as present traffic management systems are not capable of coping with the increase in the number of vehicles. In our work, we proposed a smart traffic control system with the help of AI and IoT technology to regulate and dynamically optimize the flow. In this study, with the cooperation of the municipalities, smart cameras were placed at important intersections to take a real-time traffic flow image. We, therefore, employ the YOLOv8 object detection model for vehicle detection and classification. Bytetracker tracking helps to count and trace the vehicles, and that way, the movements can be calculated accurately. The processing is done on Nvidia Jetson Nano devices, which allows real-time optimization of the traffic light and gives priority to emergency vehicles. A solution to achieve reduced congestion, improved road safety, and a lower carbon footprint is. Upon preliminary deployments, promising results have shown that this can be effectively scaled and adapted for broader traffic management improvements across Algerian cities.