The Internet of Things (IoT) is shaping the evolution of the future Internet by connecting people anytime and everywhere, as well as inanimate objects. By providing objects with embedded communication capabilities and a common addressing scheme, a highly distributed and ubiquitous network of seamlessly connected heterogeneous devices is formed, which can be fully integrated into the current Internet and mobile networks, thus allowing for the development of new intelligent services available anytime, anywhere, by anyone and anything. This year we want to shed light on the use of machine learning tools to support services and perform resource management in intelligent IoT scenarios.

The aim of this workshop is to bring together practitioners and researchers from both academia and industry in order to have a forum for discussion and technical presentations on the recent advances in theory, application, and implementation of the Internet of Things concept with a specific focus on the use of machine learning and/or artificial intelligence techniques on technologies, protocols, algorithms, and services.

Many applications with high social and business impact fall under the IoT umbrella, including personal healthcare, smart grid, surveillance, home automation, intelligent transportation, while it is expected that new ones will emerge once the enabling technologies reach a stable state. Topics of interest include, but are not limited to:

• Novel ML/AI for IoT devices and services: applications, services, business processes, and enabling standards and technologies
• ML/AI techniques for devices with limited capabilities in terms of computation, memory, storage, connectivity or energy, e.g., compressed models and federated learning
• Distributed cloud technologies and algorithms; in-network computing
• System architectures and reference platforms enabling intelligent things and services
• Modeling and simulation of large-scale scenarios of IoT devices and services with embedded intelligence
• Testbeds, prototypes, and pilots for evaluation of intelligent things and services in a realistic environment
• Solutions to increases trust in IoT devices and services: security, privacy, governance, ownership, and accuracy of data and interactions
• Ethical issues with regard to the increasing intelligence of IoT devices and services and their large-scale adoption
• Flexible and dynamic distribution of intelligence in the thing-to-cloud continuum
• System architectures for the IoT
• Protocols and mechanisms for seamless IoT communications
• Modeling and simulation of large-scale IoT scenarios
• Enabling standards and technologies for the IoT
• Service platforms for IoT applications
• Business models and processes for IoT applications
• Energy optimization and sustainable operation of IoT devices
• Access network issues including mobility management, data dissemination and routing
• Testbeds for the IoT
• Security, privacy and trust in the IoT context
• Experimental IoT system prototypes and pilots
• Novel and emerging IoT applications; including eHealth/mHealth, Smart Grid/Smart Metering, Intelligent Transportation Systems, Smart House/Neighborhood/Cities
• Industrial use cases showing gaps to be filled by future research
• Ethical issues in the IoT applications
• Optimized and robust dynamic spectrum access on IoT
• Integration of IoT with Cloud and Fog computing
• Emerging communication technologies for IoT, e.g. Low Power WAN and D2D
• Protocols and architectures for Industrial IoT
• System architectures for massive IoT

Submissions may be up to 6 pages in length (including figures and references), formatted in two-column IEEE conference style with font size 10 point or greater.
For the camera-ready of the accepted papers, authors can buy one additional page, for a total length of up to 7 pages.

Papers must be submitted electronically to EDAS by March 1, 2021. The submission page can be found at this link.

For guidelines regarding formatting, please refer to the IEEE Manuscript Templates for Conference Proceedings.

• Ashwin Rao, University of Helsinki
• Atakan Aral, Vienna University of Technology
• Chuan Xu, Inria
• Gianluca Rizzo, HES SO Valais
• Gürkan Solmaz, NEC Laboratories Europe
• Hoon Lee, Pukyong National University
• Howard Yang, ZJU-UIUC Institute
• Kashinath Basu, Oxford Brookes University
• Liang Xiao, Xiamen University
• Makram Bouzid, NOKIA Bell Labs
• Marilia Curado, University of Coimbra
• Nitinder Mohan, Technical University Munich
• Osvaldo Simeone, King's College London
• Paweł Sroka, Poznan University of Technology
• Richard Vidal, Accenture Technology Labs
• Robert Birke, ABB Corporate Research