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

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 the quest to meet the escalating demands of citizens, future smart cities emerge as crucial
entities. Their role becomes even more vital given the current challenges posed by rapid …

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

Abstract The integration of Federated Learning (FL) into the realm of smart transport systems
offers a nuanced perspective that extends beyond technological innovation, exploring the …

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 …

Energy load estimation is critical for the smooth functioning of several activities, such as
reliable supply, reduced wastage, decision making and generation planning tasks. So far …