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Content
As IoT and intelligent robotic systems evolve, real-time multimodal sensing and data fusion are essential for enabling robust perception and adaptive decision-making in dynamic environments. However, challenges such as sensor uncertainties, environmental noise, and real-time constraints limit the effectiveness of conventional data-driven AI methods. To address these issues, this workshop explores model-guided deep learning, which integrates physics-based models with AI techniques to enhance interpretability, generalization, and reliability in IoT-based sensing and perception systems.
Scope
This workshop focuses on advanced signal processing and learning-based approaches that improve multimodal sensor fusion, source localization, and real-time decision-making in IoT-enabled intelligent systems. It covers innovative methodologies for processing and integrating sensor data from radar, microphone arrays, vision systems, and IoT devices, ensuring more accurate and adaptive perception. A key focus is on hybrid AI models that combine traditional signal processing techniques-such as statistical estimation, covariance analysis, and array processing-with modern deep learning frameworks to improve system robustness. The workshop also highlights edge intelligence for real-time processing and explores applications in smart cities, intelligent transportation, and industrial automation.
Key Topics
Real-Time Signal Processing & Sensor Fusion - Techniques for combining multimodal sensor data to improve perception accuracy.
Model-Based Deep Learning for IoT - Integrating physics-aware models with AI for robust and interpretable learning.
Source Localization & Tracking - Advanced methods for accurate object detection in complex environments.
Edge Intelligence & Distributed Learning - Real-time, low-latency processing for IoT-enabled systems.
Applications in Smart Cities & Robotics - Use cases in urban mobility, infrastructure monitoring, and industrial automation.
This workshop provides a collaborative platform for researchers and practitioners in signal processing, AI, IoT, and robotics to discuss cutting-edge methodologies and advance the development of resilient, intelligent IoT systems.
Keywords: multimodal sensing, sensor fusion, model-guided learning, real-time signal processing, edge intelligence, source localization, robust perception, intelligent IoT systems, autonomous robotics
https://www.iotir.org/workshops-2025-2