Artificial Internet of Things: Future Research Application & Dimensions

Dear Colleagues:

The advancement in hardware technologies has enabled everything to be connected using the concept of Internet of Things (IoT). The intelligence in these devices has begun a new era towards reducing size, cost, and robustness.

Machine learning (ML) and artificial intelligence (AI)-based IoT devices collect a huge amount of data using wireless applications. These applications are intended to improve human life by collecting huge volumes of data. AI-based big data analytics is performed on this data to predict patterns. It is globally accepted that ML-enabled IoT is the driving force behind a plethora of innovative applications. It is expected that the number of IoT devices will increase to 200 billion by end of 2023. This will also bring several challenges in terms of generating a huge amount of data, which is very challenging to handle by extracting valuable data and ignoring the rest. Therefore, the research community needs to focus on developing advanced machine learning for data extraction to manage and utilize the data accurately and effectively.

The advancement in hardware technologies has enabled everything to be connected using the concept of Internet of Things (IoT). The intelligence in these devices has begun a new era towards reducing size, cost, and robustness.

Machine learning (ML) and artificial intelligence (AI)-based IoT devices collect a huge amount of data using wireless applications. These applications are intended to improve human life by collecting huge volumes of data. AI-based big data analytics is performed on this data to predict patterns. It is globally accepted that ML-enabled IoT is the driving force behind a plethora of innovative applications. It is expected that the number of IoT devices will increase to 200 billion by end of 2023. This will also bring several challenges in terms of generating a huge amount of data, which is very challenging to handle by extracting valuable data and ignoring the rest. Therefore, the research community needs to focus on developing advanced machine learning for data extraction to manage and utilize the data accurately and effectively.

This Special Issue will focus on novel contributions that integrate IoT with ML techniques that provide solutions to the big data paradigm. More specifically, it accepts solutions to the widely known challenges that are created due to the integration of IoT, AI, and ML from data analytics to its efficient utilization. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

·       ML techniques for Precise navigation in IoT applications.

·       Resource optimization by using ML algorithms in IoT applications.

·       Hybrid optimization models for real-world Communication applications of IoT and big data analytics.

·       Virtual Tree Applications in Artificial Modern Life Style.

·       Architectures and models for IoT networks using ML techniques.

·       ML-based data management approaches for circumventing issues in IoT applications.

·       Innovative communications technologies and protocols for IoT applications.

·       Authentication and access control for AI-enabled IoT.

·       AI-enabled big data analytics using IoT and fog computing.

·       Healthcare data analytics using IoT and ML techniques.

·       IOT for Future Business Model and Applications.

·       Industrial Security System using AIOT & Block Chain Technologyes.

·       Green Engineering for Intelligent Business Models.

Guest Editor

Dr. Kanta Prasad Sharma