Session organizers

• Imen WERDA, Tunisia
• Amina KESSENTINI, Tunisia
• Fatma BELGHITH, Tunisia
• Taheni DAMAK, Tunisia

Brief Description of the session thematic

Signals in embedded systems play a crucial role in enabling communication, control, and interaction between different components, allowing the system to perform its intended functions effectively. Embedded systems find applications across a wide range of industries and domains due to their versatility, efficiency, and ability to perform specific tasks reliably. Real-time embedded systems play a crucial role in ensuring safety, reliability, and efficiency in various domains where timing constraints are paramount. As technology continues to advance, the scope and complexity of embedded system applications are expected to expand further. AI embedded systems represent a growing field at the intersection of AI and embedded systems, enabling intelligent capabilities in a wide range of edge devices and applications.

Topics and Keywords

Video coding, medical devices and home automation are just a few examples of the diverse range of applications where embedded systems play a crucial role. In addition, designing AI embedded systems involves addressing challenges such as hardware-software co-design, power efficiency, real-time performance, security, robustness to environmental conditions, and scalability across different deployment scenarios. VVC, 3D-Video, Medical Device, Smart Home, IA, real time, co-design.

All regular contributions to ICAIGE24 must be submitted online, in electronic format to : https://icaige.tn/submission/ 

Session organizers

• Inès ABDELLAZIZ, Tunisia 
• Ferid CHAFFAR AKKARI, Tunisia

Brief Description of the session thematic

This special session focuses on the latest advancements in new materials for photovoltaic technologies and associated sensors. It provides an overview to discuss current challenges, opportunities, and breakthroughs in designing innovative materials to enhance energy efficiency and sustainability in photovoltaic systems and sensors.

 Topics and Keywords

1. Advanced Semiconductor Materials/Innovative Photovoltaic Materials.
2. Nanostructured Materials.
3. Transparent and Conductive Materials.
4. Innovation in coating Materials.
5. Durable and Recyclable Materials/Materials Durability and Sustainability.
6. Innovations in Manufacturing Technologies.

All regular contributions to ICAIGE24 must be submitted online, in electronic format to : https://icaige.tn/submission/ 

Session organizers

• Imed KHABBOUCHI, Tunisia
• Uwe RITSCHEL, Germany

Brief Description of the session thematic

In recent years, we witness an extensive use and implementation of wind power to reduce the fuel based power generations and to meet the net zero goal by 2050. At the same time, in order to optimize the manufacturing, implementation and use of wind energy there had been an extensive use of Artificial Intelligence (AI) and Machine learning (ML) to achieve those goals. 

The content of this special session will include the presentation of work on the latest development and use of ML in the field of Wind Energy. This session includes the main aspects and applications of ML in the wind energy sector such as power forecasting, design optimization, and maintenance planning.  

Special focus will be made on recent development and innovation techniques in digital transformation and applications of ML to ensure reliable and safe wind energy transition. 

Authors should contribute to the latest state-of-the art development of ML and AI based technologies to ensure more affordable and consistent wind power generation for carbon free and environmental friendly power generation.

 Topics and Keywords

• Wind Energy Sector
• Wind power and wind speed forecasting
• Fault detection
• Design optimization
• Concept drift and data drift in ML models
• Optimal control
• Maintenance planning
• Digital transition of wind energy
• Digital Twin.

All regular contributions to ICAIGE24 must be submitted online, in electronic format to : https://icaige.tn/submission/ 

Session organizers

• Fraj ECHOUCHENE, Tunisia
• Sameh KAZIZ, Tunisia
• Houcine BARHOUMI, Tunisia

Brief Description of the session thematic

This special session is dedicated to presenting and exploring recent advances in sensor devices and energy production. Under the theme "Sensor Devices," the session will explore the functionality and potential of biosensors, as well as modeling, simulation, and optimization techniques suitable for current and future applications. More specifically, it will highlight the integration of artificial intelligence to anticipate sensor responses and improve overall performance. 

At the same time, the session addresses the promising area of "hydrogen production" as a sustainable energy solution for the environment. Artificial intelligence and optimization methods play an indispensable role in advancing hydrogen production to improve efficiency and sustainability. In addition, predictive modeling enables real-time operational improvements, making hydrogen production technologies more economically viable, environmentally sound, and scalable for various applications in transportation, industry, and energy storage.

Topics and Keywords

Topics:

• Innovations in detection technology
• Sensors and their applications
• Sustainable energy solutions
• Artificial Intelligence Applications
• Optimization Strategies

Keywords: 

Artificial Intelligence; Biosensors; Detection Technology; Hydrogen Production; Optimization; Predictive Modeling; Sustainable Energy.

All regular contributions to ICAIGE24 must be submitted online, in electronic format to : https://icaige.tn/submission/ 

Session organizers

• Monia BOUZID, Tunisia
• Sondes SKANDER MUSTAPHA, Tunisia

Brief Description of the session thematic

Hybrid renewable energy systems (HRES) integrate multiple renewable energy sources, including solar, wind, hydro, geothermal, and biomass, alongside energy storage systems to enhance electricity generation efficiency and reliability.

HRES may be autonomous as standalone units or may be interfaced with the grid. The increasing adoption of HRES is due to their ability to offer stable and sustainable energy alternatives, particularly in remote areas with limited access to traditional power sources, thereby aiding global decarbonization efforts by curbing greenhouse gas emissions.

The management and optimization of these dynamic energy systems is a challenging issue, essentially regarding the balance between supply and demand.

This special session is dedicated to fostering knowledge exchange and progress in hybrid renewable energy systems, including the integration of Electric Vehicle Energy Management Systems (EVEMS). EVEMS play a crucial role in enhancing grid stability, accommodating vehicle charging demand, and leveraging vehicle-to-grid (V2G) capabilities for bidirectional energy flow. By integrating EVEMS, hybrid renewable energy systems can achieve higher levels of efficiency and resilience in managing energy resources.

•  Optimization methods for hybrid energy systems
•  Intelligent hybrid energy management systems
•  Management of hybrid energy storage
•  Sizing and dimensioning of hybrid systems
•  Forecasting hybrid renewable energy generation
•  Hybrid integration of Electric Vehicle Energy Management Systems

Topics and Keywords 

Hybrid renewable energy systems, Solar energy; wind energy; Hybrid Renewable energy integration; battery energy storage; energy management; Optimization, Forecasting, Grid integration, Micro grids, Hybrid Intelligent energy systems, Electric vehicle integration, Demand-side management.

All regular contributions to ICAIGE24 must be submitted online, in electronic format to : https://icaige.tn/submission/ 

Session organizers

• Wajdi ELHAMZI, Saudi Arabia

• Mohamed EL-HADEDY, USA

• Kamel MESSAOUDI, Algeria

Brief Description of the session thematic

Field-Programmable Gate Arrays (FPGAs) are versatile hardware platforms capable of being reprogrammed to address a broad spectrum of tasks, making them ideal for Internet of Things (IoT) and Artificial Intelligence (AI) applications. These devices excel in facilitating rapid development and enhanced performance of AI-driven tasks. Within the realm of IoT and AI, FPGA designers leverage these adaptable chips to prototype and refine various algorithms swiftly, enabling the efficient testing and optimization of designs before committing to a fixed hardware setup. Today, there are several applications in which AI plays an offensive or defensive role in hardware security and a crucial role in predictive modeling for VLSI designs. The use of artificial intelligence techniques, such as machine learning (ML) and deep learning (DL), to build countermeasures against hardware threats. One of the most notable benefits of ML techniques is the automation of the attack detection process. AI approaches, like genetic algorithms and evolutionary learning, can be applied to improve different elements of VLSI architecture. Furthermore, AI aids in identifying important routes and reducing power usage in VLSI. AI can help improve approaches such as frequency scaling and dynamic voltage. Indeed, AI can automate tasks such as datapath optimization and resource allocation. As a result, ML algorithms can understand design specifications, performance targets, and so on, which aids in the optimization of register transfer level (RTL). 

Topics and Keywords 

• FPGA design for Machine Learning and Artificial Intelligence  
• FPGA design for IoT and Smart Systems  
• AI based Hardware Security  
• AI based VLSI Circuits Design 

All regular contributions to ICAIGE24 must be submitted online, in electronic format to : https://icaige.tn/submission/