Abstract Machine learning is one of the emerging technologies that has grabbed the
attention of academicians and industrialists, and is expected to evolve in the near future …

Fueled by the availability of more data and computing power, recent breakthroughs in cloud-
based machine learning (ML) have transformed every aspect of our lives from face …

The cloud-based solutions are becoming inefficient due to considerably large time delays,
high power consumption, and security and privacy concerns caused by billions of connected …

We are living in an era where the Artificial Intelligence (AI) is becoming a global platform for
the computation and interaction between machines and smart objects in real-time …

Artificial intelligence (AI) and machine learning (ML) techniques have huge potential to
efficiently manage the automated operation of the internet of things (IoT) nodes deployed in …

New technological advancements in wireless networks have enlarged the number of
connected devices. The unprecedented surge of data volume in wireless systems …

Federated learning can be a promising solution for enabling IoT cybersecurity (ie, anomaly
detection in the IoT environment) while preserving data privacy and mitigating the high …

The number of Internet of Things (IoT) devices to be connected via the Internet is
overgrowing. The heterogeneity and complexity of the IoT in terms of dynamism and …

For a seamless deployment of the Internet of Things (IoT), there is a need for self-organizing
solutions to overcome key IoT challenges that include data processing, resource …

Billions of IoT devices will be deployed in the near future, taking advantage of faster Internet
speed and the possibility of orders of magnitude more endpoints brought by 5G/6G. With the …