A robust approach for WSN localization for underground coal mine monitoring using improved RSSI technique

Abstract

During last decade, wireless communication technologies have grown drastically and have been adopted widely for various real-time applications. Wireless sensor network based communication has attracted researchers' attention due to its significant nature of adaptability in diverse application. Wireless sensor networks are widely used in applications such as environment monitoring, military application, weather forecasting etc. However, numerous researches have been carried out in these monitoring systems. Recently, mining industries are also adopting WSN based communication for monitoring underground coal miners for worker safety purpose and better production. In order to achieve better convergence analysis of coal mine, a proper data transmission from sensor to the destination node is required, which is possible only if the accurate positions of sensor nodes are known. Finding the accurate position is a crucial task, which is also known as sensor node localization. In this study, we have focused on the underground coal mining monitoring, where first of all, we present a novel approach for sensor network localization to establish hassle free communication. According to proposed approach, initially a sensor network localization problem is formulated where node distance measurement and signal strength measurement models are developed. Later RSSI based signal strength model is developed, which is further improved by introducing a probability density function, which helps to reduce the distance error. Complete experimental study is carried out using MATLAB simulation tool where a scenario of underground coal mining is considered. Experimental study shows that proposed model outperforms Gaussian model and Statistical Mean Model by achieving average range error of 3.67, average localization error of 4.85 in terms of communication radius and average range error of 6.972 for varied number of nodes.