aspg-18-3038-1792025600 20261015005320 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Intelligent Systems and Internet of Things JISIoT 2769-786X 2690-6791 2024 13 2 Krishna Kumar .N Associate Professor, Dept. of CSE, Gurunanak Institutions Technical Campus, Ibrahimpatnam, Hyderabad, Telangana, India Surya Kiran Chebrolu Professor, Dept. of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India R. Manikandan Professor, Dept. of ECE, Panimalar Engineering College, Chennai, TN, India Aby K Thomas Professor, Dept. of ECE, Alliance College of Engineering and Design, Alliance University, Bengaluru, Karnataka, India Peruri Venkata Anusha Assistant Professor, Dept. of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India Hari Prasad Bhupathi Application Software Supervisor, Stellantis NV, FCA Technology Centre, 1000 Chrysler Dr, Auburn Hills, MI, USA Localization is an extremely important component of applications that make use of wireless sensor networks. It has a substantial impact on academics as well as real-time sensor deployment applications in the aim of lowering the amount of energy that is used while simultaneously locating unknown nodes. The process of obtaining the coordinates along an axis that represent the locations of the sensor nodes is referred to as localization. The accuracy of locating the positions of the nodes varies depending on the environmental conditions, the type of nodes, the type of application, and the type of localization methods used. A standard localization method known as distance vector hop (DV-hop) localization will be able to determine the positions of unknown nodes with typical accuracy with the assistance of beacon nodes based on Internet of things. The DV-hop and improved weighted centroid localization algorithms, in addition to the suggested boosted weight centroid-based localization approach, are both addressed in this article. The suggested boosted weight centroid localization technique is utilized to find nodes in the remote area of the WSN while conserving energy. This is accomplished with the assistance of measurements involving both the nodes and the centroid. The modified weight metric is utilized in the process of carrying out the task of localisation of an unknown node. The performance of BWCLA is evaluated based on a number of different metrics, including accuracy in localization, average localization error, total packets utilized, and energy usage. 2024 223 230 3038 https://creativecommons.org/licenses/by/4.0/ 10.54216/JISIoT.130218 https://americaspg.com/journal/18/article/3038 https://americaspg.com/storage/01720993690.pdf