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@article{178537,
        author = {Sudha H.Thimmaiah and Vidya Honguntikar and Yamuna Devi C.R},
        title = {RSSI Method:Estimation & Analysis of Communication Range Parameter for Localization in WSNs.},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {3887-3892},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178537},
        abstract = {Presently, Wireless Sensor Networks (WSNs) have notably emerged as one of the forefront areas of technical research because of the diverse applications of WSNs includes monitoring, controlling, navigation and surveillance. Essentially, a WSN consists of numerous tiny sensor nodes that are randomly distributed across a designated area. These nodes are capable of collecting and transmitting data to a sink node. The performance efficiency of a WSN in the aforementioned applications largely hinges on several key parameters: the Number of Nodes (NN) or Node Density, Communication Range (CR) and Anchor Nodes (AN). In this research paper, we aim to minimize errors in a WSN by calculating the communication range estimates between sensor nodes using Root Mean Square Error (RMSE) simulation analysis. This analysis for varying communication ranges is conducted using the Received Signal Strength Indicator (RSSI) method in MATLAB.},
        keywords = {AN-Anchor Nodes, CR-Communication Range, NN-Number of Nodes, RSSI-Received Signal Strength Indicator, RMSE-Root Mean Square Error. WSNs-Wireless Sensor Networks,},
        month = {May},
        }