A bibliometric analysis review: the emerging technology of artificial intelligence for non-bio inspired and bio-inspired algorithm of wireless sensor network from 2005–2022

Abstract

Rapid developments in technology, business, and social norms have been observed in the twenty-first century. The fourth industrial revolution has been brought about by most industries moving toward automation and reducing human intervention. Wireless sensor networks are incredibly important to the fourth industrial revolution since they help with modernization. WSNs are networks of sensor and routing nodes that can be integrated into a variety of control systems, such as those used for home automation, electric-power automation, and environmental monitoring. A key problem that typically afflicts wireless sensor networks is node localization (WSNs). As a result, several algorithms, to ameliorate the challenges WSNs confront, both bio-inspired and non-bio-inspired solutions have been presented. From 2005 through 2022, the Scopus database was searched for publications. WSNs are used in published research paper statistical analysis, Microsoft Excel 365, VOSviewer, RStudio, and Biblioshiny packages were used. For this seventeen-year study period, a total of 36,377 published documents were in the Scopus database. 765 papers in all were examined following the implementation of the exclusion criteria. This study highlights the global research production of bio-inspired and non-bioinspired algorithms in wireless sensor networks, together with their status and tendencies. It can assist IoT and wireless sensor network researchers in gaining a thorough understanding of the most advanced algorithms in this area