RSSI Based Localization System for Outdoor Wireless Sensor Networks

Abstract

The most important components of Wireless Sensor Networks is localization. In situations when there are a lot of randomly placed sensor nodes, pinpointing the exact cause of any emerging problem becomes crucial. A contrasting analysis of the Free Space Propagation Model (FSPM) and the 2-Slope 2-Ray Model (2S2R), two popular propagation models, which have been modified to increase their efficiency using Recieved Signal Strength Indicator (RSSI) has been stated. To assess these models’ performance in an area of forest while taking into account crucial variables as path loss, attenuation, environmental effects, path loss exponent, and accuracy. The FSPM, which is based on the inverse square law, makes the idealised assumption that there are no obstacles or reflections in the open space environment. This model is suitable for line-of-sight scenarios and open space deployments. It might not, however, adequately depict the effects of reflections and obstructions in actual surroundings. The 2S2R Model, on the other hand, takes both multi-path propagation and free space path loss into account. It provides a more accurate illustration of signal transmission by taking environmental reflections and obstructions into account. The 2S2R Model gives increased accuracy in reflective conditions and can offer insightful information for deployments in a forested area. This study aids in choosing an acceptable model for wireless communication in a forest environment and advances our understanding of propagation models. The comparison anal- ysis provides information on the precision, dependability, and applicability of the 2S2R Model and the FSPM, facilitating well- informed decisions for the deployment of wireless communication systems in forest areas.