Prof. Suresh Sankaranarayanan; SMIEEE
Department of Computer Science
College of Computer Science and Information Technology
King Faisal University
Al Hofuf
Kingdom of Saudi Arabia
E-mail: ssuresh@kfu.edu.sa


Prof. Pascal Lorenz; SMIEEE
University of Haute Alsace
Colmar, France
E-mail: pascal.lorenz@uha.fr

Artificial Intelligence has been around for decades towards solving problems in science and industry. Another fast-growing technology is Internet of Things (IoT) which interconnect billions of things that continuously produce data at high volumes and velocity. This have been pushing towards a new paradigm called edge computing. Edge computing which is an extension of Cloud in IoT based system process the data near the devices like sensors, objects, actuators where data is generated rather than cloud. This ultimately is towards performing real time analysis for quick action with low latency, high scalability, High security and energy efficiency, in addition to producing less network traffic load.

Nevertheless, with the development of various IoT applications (e.g., smart home, smart city, industrial automation, connected vehicles), there is need to have intelligence at the Edge towards heterogenous environment where data is generated for different solutions. The usage of Artificial Intelligence at the Edge would require optimized usage of power, memory, processing power due to resource constrained nature for performing intelligent analysis and prediction Therefore, Artificial Intelligence along with its algorithms and application has provided a wide spectrum of promising solutions to empower edge computing for IoT. The EIIOT 2023 Special Session at the 14th International Conference on Computational Collective Intelligence (ICCCI 2023) is devoted to the Artificial Intelligence techniques and methodologies at Edge/Fog for their optimized resource usage for different IoT applications like Agriculture, Energy, Water, Healthcare and many more. We want to offer an opportunity for researchers and practitioners to identify new promising research directions as well as to publish recent advances in this area. The scope of the EIIOT 2023 includes, but is not limited to the following topics:

• Resource Management for Edge Intelligence
• Security and Privacy Issues for IoT Edge Intelligence
• Deep learning for IoT Edge Intelligence
• Machine learning for IoT Edge Intelligence
• Explainable AI for IoT Edge Intelligence
• Multi Agents for IoT Edge Intelligence
• Evolutionary Algorithm for IoT Edge Intelligence
• Meta-heuristics Algorithms for IoT Edge Intelligence
• Swarm Intelligence for IoT Edge Intelligence
• Hybrid intelligent systems for IoT Edge Intelligence