Key research themes
1. How can intelligent methods improve design, adaptability, and efficiency in embedded systems?
This research area explores the incorporation of intelligent algorithms—such as fuzzy logic controllers, multi-agent systems, biologically inspired methods, and AI models—into embedded system designs. The focus lies on enhancing system performance, adaptability to dynamic environments, self-configuration, optimization, and resilience while managing constraints like real-time requirements, limited hardware resources, and system complexity. Intelligent embedded systems support advanced capabilities including autonomous decision-making, self-learning, and fault tolerance, enabling applications across health monitoring, ambient intelligence, robotics, and autonomous vehicles.
2. What methodologies and frameworks enable effective development and optimization of embedded systems software and real-time operating systems?
Focusing on software development aspects, this research theme addresses methodologies to specify, generate, and optimize embedded system software and operating systems. Challenges include meeting stringent real-time constraints, memory and energy optimization, and providing maintainable and scalable software architectures. Techniques such as automatic RTOS generation from high-level specifications, project-based learning pedagogies, and software engineering standards facilitate efficient embedded software development tailored for diverse application needs.
3. How are embedded systems being applied in autonomous and ambient intelligent environments to enhance interaction and decision-making?
This research direction investigates application-driven development where embedded systems equipped with intelligent control and sensing enable automated and adaptive functionalities. Domains include ambient intelligence, autonomous vehicles, telemedicine, robotics, and novel user interfaces like voice over wireless sensor networks. The focus is on integrating sensing, communication, and computation to enable real-time decision-making, environmental awareness, and improved human-system interactions.