-------- Weitergeleitete Nachricht -------- Betreff: IEEE Access Special section on Collaborative Intelligence for Internet of Vehicles Datum: Wed, 27 Jan 2021 17:37:46 +0100 (CET) Von: Sidi-Mohammed Senouci Sidi-Mohammed.Senouci@u-bourgogne.fr Antwort an: Sidi-Mohammed Senouci Sidi-Mohammed.Senouci@u-bourgogne.fr An: Sidi-Mohammed Senouci Sidi-Mohammed.Senouci@u-bourgogne.fr

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Announcing a Special Section in IEEE Access:  Collaborative Intelligence for Internet of Vehicles : https://ieeeaccess.ieee.org/open-special-sections/collaborative-intelligence... https://ieeeaccess.ieee.org/open-special-sections/collaborative-intelligence-for-internet-of-vehicles/

Submission Deadline:  *31 July 2021*

IEEE Access invites manuscript submissions in the area of Collaborative Intelligence for Internet of Vehicles.

Internet of vehicles (IoV) technology is one of the most important breakthroughs that can significantly support mobility systems toward achieving smart and sustainable societies. For example, cooperative driving features enabled by IoV can significantly decrease the risk of traffic accidents and reduce CO2 emissions, thus facilitating smarter transportation. Aerial vehicles, also known as drones, are useful for many applications, including environment and traffic monitoring, crowd mobility and gathering surveillance in pandemics, disaster recovery, and so on. Internet of underwater vehicles could enable many innovative maritime applications such as autonomous shipping, target detection, navigation, localization, and environmental pollution control. However, the development of IoV systems is dependent on overcoming the following two main challenges.

First, due to the heterogeneity of networking entities, strict application and data processing requirements, and limited resources in IoV environments, more advanced networking and computing technologies are required. Future IoV systems feature a larger number of devices and multi-access environments where different types of wireless spectrums should be efficiently utilized. At the same time, novel services, such as cooperative autonomous driving, IoV-based safety and traffic efficiency applications are emerging, and demand unprecedented high accuracy and reliability, ultra-low latency, and large bandwidth. This poses crucial challenges to the efficient use of the limited networking and computing resources.

Recently, to further explore the value of big data from IoV systems, artificial intelligence (AI)-based approaches have been attracting great interest in empowering computer systems. Some collaborative learning approaches, such as federated learning and multi-agent systems, have been used to reduce network traffic and improve the learning efficiency of some smartphone applications. For IoV systems, collaborative intelligence can be achieved via an efficient collaboration among heterogeneous entities, including vehicles, edge servers, and the cloud.

Second, in order to enable a smarter society, more research should be conducted on developing collaborative IoV frameworks and systems to expedite the applications of emerging IoV technologies. An efficient use of cross-domain big data should be discussed, and academic-industrial collaborations should be promoted to solve the existing problems toward a smarter society.

This Special Section focuses on the technical challenges for enabling collaborative IoV systems, and the applications of IoV technologies for a smarter society.

The topics of interest include, but are not limited to: - Collaboration among Space, Air, Ground, and Sea mobile networks - Collaborative intelligence based on cross-domain big data for IoV - Collaborative networking for IoV - Collaborative computing for IoV - Collaborative IoV for smart cities - Collaborative IoV for intelligent transportation systems - Collaborative IoV for energy-efficient sustainable cities - Collaborative electric vehicles - Collaborative unmanned aerial vehicles - Collaborative heterogeneous unmanned ground and aerial vehicles - Collaborative underwater vehicle technologies for smart ocean - Collaborative IoV for smarter society - Collaborative learning for IoV - Data driven collaborative intelligence for IoV - End-edge-cloud collaboration for IoV - New networking and computing architectures for Collaborative IoV - Security & privacy for IoV

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.

*Associate Editor:*  Celimuge Wu, The University of Electro-Communications, Japan

*Guest Editors:* - Soufiene Djahel, Manchester Metropolitan University, UK - Damla Turgut, University of Central Florida, USA - Sidi-Mohammed Senouci, University of Bourgogne, France - Lei Zhong, Toyota Motor Corporation, Japan

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