The sensors employed in the wireless sensor network are battery-powered which are
prepared with a limited energy supply. Most of the applications in the field of wireless sensor …

This paper explores the transformative integration of deep learning applications in the
deployment of Wireless Sensor Networks (WSNs). As WSNs continue to play a pivotal role in …

The energy efficiency in wireless sensor networks (WSNs) is a significant challenge. A
clustering-based approach is an energy-saving approach in WSN. The practical clustering …

The nodes in the wireless sensor network are furnished with restricted and irreplaceable
battery power. The continuous sensing, computation, and communication drain out the …

Maximizing network lifetime is the main goal of designing a wireless sensor network.
Clustering and routing can effectively balance network energy consumption and prolong …

Optimization approaches in machine learning (ML) are essential for training models to
obtain high performance across numerous domains. The article provides a comprehensive …

Emergence of applications of wireless sensor networks in various fields over time requires to
acknowledge existing solutions which have been proposed in history to overcome various …

Energy management is considered as a challenging task for applications related to the
wireless sensor network. The cluster-based networks are among the most effective solutions …

Abstract Artificial Intelligence (AI) realizes Wireless Sensor Networks (WSNs) as a dynamic
environment of battery-powered sensor nodes. These nodes are carefully built to monitor …

In order to meet the growing needs for wireless communication in dynamic and diverse
circumstances, Cognitive Radio Networks (CRNs) have evolved as a transformational …