The emergence of Explainable Artificial Intelligence (XAI) has enhanced the lives of humans
and envisioned the concept of smart cities using informed actions, enhanced user …

The proliferation of ubiquitous Internet of Things (IoT) sensors and smart devices in several
domains embracing healthcare, Industry 4.0, transportation and agriculture are giving rise to …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

In recent times, IoT has emerged as a new paradigm for the interconnection of
heterogeneous, resource-constrained, and communication-capable smart devices. It has …

In this constantly evolving landscape of urbanization, the relationship between technology
and automation, in regards to sustainability, holds immense significance. The intricate …

The chest lesion caused by COVID-19 infection pandemic is threatening the lives and well-
being of people all over the world. Artificial intelligence (AI)-based strategies are efficient …

Since its inception in 2016, federated learning has evolved into a highly promising decentral-
ized machine learning approach, facilitating collaborative model training across numerous …

Recent developments in the Internet of Things (IoT) and real‐time applications, have led to
the unprecedented growth in the connected devices and their generated data. Traditionally …

Ensuring the privacy and trustworthiness of smart city—Internet of Things (IoT) networks
have recently remained the central problem. Cyborg intelligence is one of the most popular …

Forecasting short-term residential energy consumption is critical in modern decentralized
power systems. Deep learning-based prediction methods that can handle the high variability …