Special Session on Intelligent Mobility & Beyond: "AI-Driven Sensing, Autonomy, and Edge Intelligence from Vehicles to Everyday Life"

Chairs:

• Dr.-Ing. Nikolaos Athanasios Anagnostopoulos, Universität Passau
• Dr.-Ing. Mayukh Bhattacharyya, Onsemi
• Dr. Mohamed Faragalla, NXP Semiconductors
• Dr.-Ing. Tolga Arul, Barkhausen Institute

In collaboration with the Germany Section Chapters of the IEEE Solid-State Circuits Society (SSCS – LinkedIn), the IEEE Vehicular Technology Society (VTS – LinkedIn), and the IEEE Consumer Technology Society (CTSoc – LinkedIn).

This special session explores the rapidly evolving intersection of artificial intelligence and next-generation mobility systems, with a primary focus on automotive technologies and autonomous platforms. As vehicles, drones, and intelligent machines become increasingly autonomous, advances in AI-driven sensing, perception, and decision-making are redefining how systems interact with the physical world.

The session highlights cutting-edge developments in signal processing, radar and LiDAR technologies, sensor fusion, and edge AI, enabling robust perception in complex and dynamic environments. Beyond automotive applications, the session extends to emerging domains such as smart homes, wearable devices, IoT ecosystems, and human-centric sensing, showcasing how innovations in mobility are influencing, and are being influenced by, broader consumer and industrial technologies.

We welcome contributions that push the boundaries of intelligent systems, including real-time embedded AI, energy-efficient edge computing, quantum-enhanced algorithms, and novel sensing paradigms. This session aims to bring together researchers and practitioners from academia and industry to discuss transformative ideas shaping the future of autonomous systems and connected intelligent environments.

Our Special Session's tagline is: "From self-driving cars to intelligent living spaces – shaping a seamlessly autonomous future."

Peer Reviewed Technical Paper Submissions

We invite submissions of original, unpublished papers addressing topics including, but not limited to:

• AI for Autonomous Vehicles & Intelligent Mobility
  • End-to-end learning for autonomous driving
  • Generative AI for simulation and scenario generation
  • Foundation models for driving intelligence
  • AI safety, explainability, and validation in AVs
  • Multi-agent coordination (vehicle-to-vehicle, swarm intelligence)
  • Reconfigurable AI & embedded computing platforms (inc. FPGA designs) for intelligent transportation
  • Privacy-preserving AI and secure data analytics for intelligent mobility
• Advanced Sensing and Connectivity: Radar, LiDAR, and Beyond
  • AI-enhanced radar perception (4D radar, imaging radar)
  • LiDAR processing, compression, and semantic understanding
  • Sensor fusion (camera + radar + LiDAR + ultrasonic)
  • Robust perception under adverse conditions (fog, rain, night)
  • Event-based and neuromorphic sensors
  • 5G/6G, V2X, and wireless connectivity technologies for intelligent mobility
• Signal Processing and Multimedia for Intelligent Systems
  • Deep learning for signal interpretation and reconstruction
  • Sparse sensing and compressed sensing in mobility
  • Real-time signal processing on embedded platforms
  • Multimodal data fusion and temporal modeling
  • Edge signal intelligence for low-latency decisions
  • Audio/Video systems & multimedia signal processing for mobility
  • Immersive in-cabin entertainment & digital experiences
  • Smart cockpit, human–machine interaction & personalized mobility experiences
  • Entertainment, gaming & immersive media for future mobility
• Edge AI and Embedded Intelligence
  • TinyML and ultra-low-power AI for vehicles and IoT
  • On-device learning and federated learning
  • Hardware-software co-design for AI acceleration
  • AI on automotive-grade chips and edge processors
  • Real-time inference under strict latency constraints
  • Neuromorphic, in-memory & edge AI computing for real-time intelligent mobility
  • Heterogeneous integration & chiplet architectures for AI in intelligent mobility
• Drones, Robotics, and Autonomous Systems
  • AI for UAV navigation and obstacle avoidance
  • Swarm intelligence for drones and robotic fleets
  • Autonomous delivery and aerial sensing systems
  • Cross-domain autonomy (air, land, sea vehicles)
  • Simulation-to-real transfer for robotics
  • Sustainable, energy-efficient & green consumer electronics for mobility
• AI for Smart Homes, Consumer IoT, and Connected Mobility Ecosystems
  • Context-aware intelligence in smart environments
  • AI-powered home automation and predictive systems
  • Edge AI for privacy-preserving IoT applications
  • Sensor networks for ambient intelligence
  • Interoperability and intelligent orchestration of devices
  • AI-driven consumer mobility services & data analytics
  • Smart infrastructure & cooperative intelligent transportation systems
  • Power electronics, battery management & EV charging technologies
  • Intelligent transportation systems (ITS) and smart mobility ecosystems
• Wearables, Human-Centric AI, and Sensing
  • AI for health monitoring and biometric sensing
  • Smart wearables integrated with mobility ecosystems
  • Human-in-the-loop AI systems
  • Brain-computer interfaces and implantable devices
  • Personalized AI assistants through multimodal sensing
  • Wearables, XR & personal consumer devices for intelligent mobility
  • Smartphone integration & cross-device mobility experiences
• Emerging & Disruptive Technologies
  • Quantum computing for AI and optimization in mobility
  • Digital twins for vehicles and smart environments
  • AI for sustainable and energy-efficient mobility
  • Cybersecurity in autonomous and connected systems
  • Ethical, regulatory, and societal implications of AI systems
  • Cloud-native mobility platforms, mobility-as-a-service (MaaS), and edge intelligence
  • AI-enabled automotive SoC & ASIC design
  • Functional safety and reliable AI for autonomous mobility
  • Hardware security and trusted AI for connected mobility