Special Issue on intelligent anomaly/novelty detection to enhance IoT and AIoT

Due to the Covid-19 pandemic, people's work and lifestyles are undergoing unprecedented changes. More and more smart services are connected to the internet through edge devices with intelligent computing capabilities, e.g., wearable computing, smart grid decisions and diverse Internet of Things (IoT) applications. While these changes bring speed and convenience, they also flood the edge network with IoT data, which existing models cannot effectively analyse. Artificial intelligence (AI) technology applications can help to work out the true intention of this IoT data, however, there are still challenges; for example, data originating from unknown classes, also known as an anomalies or novelties. These noisy data cause unexpected perturbations when training AI models in edge and IoT devices. The goal of this special issue is to spur further research and development of anomaly/novelty detection.

Topics covered:

We are interested in submissions that consider intelligent anomaly/novelty detection for IoT and AIoT from the perspective of:

• Supporting efficient communications in IoT
• Smart systems, e.g., transportation, healthcare, manufacturing, home and ocean
• Assisting in the training of lightweight AI models in IoT and AIoT
• Privacy and security mechanisms between edge and fog computing
• Emotion computing using IoT or AIoT
• IoT-based smart systems, e.g., transportation, healthcare, manufacturing, home and ocean
• AI-based computation offloading in IoT and edge computing
• AI-based service mitigation strategy for diverse applications of IoT or AIoT
• AI-based resource management in IoT or AIoT
• AI-based real-time computing leveraging IoT and edge computing

Important dates:

• Submission deadline: 15 December 2022
• First revision due: 31 January 2023
• Second revision due: 30 March 2023
• Final manuscript due: 30 June 2023
• Publication date: July 2023

Submission instructions:

Please read the Guide for Authors before submitting. All articles should be submitted online via the editorial management system by selecting “SI-IAD” under the “Select Article Type” tab.

Guest editors:

• Joel J.P.C. Rodrigues, Senac Faculty of Ceará, Fortaleza-CE, Brazil; Instituto de Telecomunicações, Portugal
• Arun Kumar Sangaiah, Vellore Institute of Technology, India.
• Marek R. Ogiela, AGH University of Science and Technology, Poland.
• Al-Sakib Khan Pathan, United International University, Bangladesh.
• Fa Zhu, Nanjing Forestry University, P. R. China.