AI-Driven Advances in Communications, Localization and Sensing: Bridging Algorithms, Applications, and InnovationWorkshop Organizers Assoc. Prof. Wafa Njima, Isep Paris, France,wafa.njima@isep.fr Assoc. Prof. Iness Ahriz, CNAM Paris, France,iness.ahriz@cnam.fr Short Biographies Wafa Njima is an associate professor at Isep, Paris and member of LISITE laboratory, team ECoS. She served as TPC member and reviewer for many leading international conferences and journals. Her publications span several research areas, and her research interests are related to several topics including signal processing, wireless communications, sparse data, indoor localization,IoT and machine learning for communications. Iness Ahriz received the Ph.D. degree from Sorbonne University in Paris, France, in 2010. Since 2011, she has been an Associate Professor with the CEDRIC Research Laboratory of Conservatoire National des Arts et Métiers, Paris. Her research interest is to address the problems of missing data and relevant data related to indoor localization using machine learning algorithms. Scope and Topics The workshop aims to underscore the transformative role of artificial intelligence (AI) and machine learning (ML) in shaping the future of localization, sensing, and communication technologies. These fields are undergoing rapid convergence, spurred by the demands of next-generation wireless systems like 5G and 6G, as well as the rise of smart cities, autonomous systems, and the Internet of Things (IoT). This integration is critical for meeting the growing requirements of accuracy, scalability, adaptability, and energy efficiency in increasingly complex environments. AI-driven advancements provide innovative solutions to long-standing challenges, such as improving accuracy under non-line-of-sight (NLOS) or multipath propagation conditions, dynamically optimizing network resources, and ensuring real-time, low-latency responses in large-scale systems. These innovations also enable the design of intelligent and context-aware networks, where localization, sensing, and communication interoperate seamlessly to create novel applications across domains such as autonomous navigation, environmental monitoring, augmented reality, and smart manufacturing. The workshop offers a platform for researchers, industry leaders, and practitioners to: • Present groundbreaking research that leverages AI and ML to advance localization, sensing, and communication technologies. • Exchange insights on emerging trends, challenges, and opportunities in these converging fields. • Foster interdisciplinary collaboration to address the technical and practical hurdles in implementing AI- powered solutions at scale. By showcasing these advancements, the workshop aims to inspire novel research directions and highlight the transformative potential of AI and ML in driving the next wave of innovation in localization, sensing, and communication technologies. The present workshop aims to showcase cutting-edge research and foster discussions on leveraging ML methodologies in these fields. It seeks to attract contributions that delve into the following topics, among others: • AI-based indoor and outdoor localization techniques. • Multi-sensor fusion and integration for localization. • Context-aware and cooperative localization systems. • Localization using signals of opportunity (WiFi, Bluetooth, GNSS, etc.). • Ultra-wideband (UWB) and millimeter-wave localization. • Location-aware services for smart cities, IoT, and autonomous systems. • Simultaneous localization and mapping (SLAM) with AI enhancements. • Sensing across diverse frequency bands. • AI-driven signal processing for sensing and mapping. • Contextual sensing and environmental awareness. • Generalization and adaptability of ML-based models across domains. • Federated learning and distributed ML for integrated systems. • Resource-efficient AI/ML algorithms for real-time localization, sensing, and communication. • End-to-end learning for joint optimization of localization, sensing, and communication. • AI-driven solutions for integrated communication, localization, and sensing. • Location-aware beamforming and intelligent resource allocation. • Channel charting and radio environment mapping. • Distributed optimization and over-the-air computation for communication systems. • Energy-efficient and scalable localization, sensing, and communication systems. • Robust solutions for challenging environments (e.g., NLOS, multipath). • Validation and benchmarking with real-world datasets and testbeds. • Validation through experimental testbeds and real-world datasets. • Practical implementation of ML-based solutions in real-time systems. Technical Program Committee • Wafa Njima, Isep, France • Iness Ahriz, Le CNAM, France • Idowu Ajayi, Isep, France • Nasir Saeed, UAEU, UAE • Lounis Zerioul, Le CNAM, France • Ahmad Bazzi, NYUAD, UAE • Luan Chen, ENSEA, France • Fouzia Boukour, University of Gustave Eiffel, France Keynote Speaker Keynote 1: "AquaTech Unleashed: Communications, Localization and Sensing in Internet of Underwater Things," Important Dates: Workshop Paper Submission Due: 15 July 2025 Author Notification Due: 15 Sep 2025 Camera-ready Due: 30 Sep 2025 Registration Due: 10 Oct 2025 Conference Date: 17-20 Nov 2025 Workshop papers need to be prepared according to the IEEE format, and submitted in PDF format via the SmartIoT 2025 submission site: https://ieee-smartiot.org/submission.jsp, then can be submitted |
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