Application of wireless sensor network for environmental monitoring in underground coal mines: A systematic review

The increasing in the demand for Wireless Sensor Networks (WSNs) has intensified studies which are dedicated to obtain more energy-efficient solutions, since the energy storage limitation is critical in those systems. Additionally, there are other aspects which usually must be ensured in order to get an acceptable performance of WSNs, such as area coverage and network connectivity. This paper proposes a procedure for enhancing the performance of WSNs: a multiobjective hybrid optimization algorithm is employed for solving the Dynamic Coverage and Connectivity Problem (DCCP) in flat WSNs subjected to node failures. This method combines a multiobjective global on-demand algorithm (MGoDA), which improves the current DCCP solution using a Genetic Algorithm, with a local on line algorithm (LoA), which is intended to restore the network coverage soon after any failure. The proposed approach is compared with an Integer Linear Programming (ILP)-based approach and a similar mono-objective approach with regard to coverage, network lifetime and required running time for achieving the optimal solution provided by each method. Results achieved for a test instance show that the hybrid approach presented can improve the performance of the WSN obtaining good solutions with a considerably smaller computational time than ILP. The multiobjective approach still provides a feasible method for extending WSNs lifetime with slight decreasing in the network mean coverage.

A Hybrid Multiobjective Evolutionary Approach for Improving the Performance of Wireless Sensor Networks

Applications of wireless sensor networks to improve occupational safety and health in underground mines.

Study on an improved real-time monitoring and fusion prewarning method for water inrush in tunnels

In multiview video (MVV) transmission over wireless multimedia sensor networks (WMSNs), a highly compressed video stream is very susceptible to whole-frame losses due to wireless channel errors Currently, most frame concealment methods can only handle 2-D video or 3-D video with depth, since a lost motion vector can be recovered utilizing the relationship between the color frames and their corresponding depth map However, depth generation is infeasible in the scenario of WMSNs due to energy constraints and computational limitations of low-power video sensor nodes In this paper, we tackle the problem of concealing lost whole frames for multiview 3-D video transmission over WMSNs We propose a new technique, which is capable of dealing with this important problem without the aid of depth map Experimental results are presented to demonstrate that the proposed algorithm is able to effectively conceal frames of MVV and significantly outperforms other techniques in both objective and subjective quality measurements

Frame Loss Concealment for Multiview Video Transmission Over Wireless Multimedia Sensor Networks

Wireless sensor network (WSN) is considered here for remote monitoring of mine tunnels. Since mine transport and exploiting plane monitoring are the complex tasks that require video monitoring, a major challenge of remote mine tunnel monitoring is the multipath and diffraction effect due to unreliable channel and limited capacity. We propose here a braided cooperative reliable transport (BCRT) algorithm for reliable video transmission within mine tunnel. BCRT maintains one-hop reliability to ensure end-to-end reliability so that it is robust to path breaks. In addition, the BCRT-based WSN uses three consecutive forward neighbors to adjust the data rate to improve the sensing reliability. The proposed WSN is implemented in a real-life mine tunnel. And it is demonstrated to be able to enhance the reliability of the end-to-end monitoring of mine tunnels.

A Reliable and High-Bandwidth Multihop Wireless Sensor Network for Mine Tunnel Monitoring

Vehicular Ad hoc Network (VANET), as a subclass of mobile Ad hoc Networks (MANETs), is a promising approach for traffic security, mobile internet and V2V communication. While the packet loss estimation of VANET impacts routing protocol and transmission control algorithm, it turns out to be an important issue. In this paper, we propose an estimation algorithm for packet loss on VANET, RPLE (Real time packet loss estimation), which uses few probe packets and enhance the estimation accuracy than traditional methods for packet loss on wireless networks. Due to node motion and complex radio environment, packet loss estimation in VANET is a hard problem. However, packet loss estimation impacts routing protocol and transmission control algorithm of VANET, so it is an important issue. Based on mass on-road measurements, we have obtained the general statistical principals of packet loss rate (PLR) by distances on VANET, and we use Gaussian Mixture Model (GMM) to present PLR probability density. In that case, to get real-time PLR by sending a few probe packets, RPLE use maximum a posteriori probability method to estimate the current PLR based on the GMM of PLR probability density and the probing result. In real urban road scenario, the experiment results indicate that RPLE can get more accurate PLR estimation by few probe packets immediately.

Estimation of Packet Loss Rate at Wireless Link of VANET--RPLE

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A Reliable and High-Bandwidth Multihop Wireless Sensor Network for Mine Tunnel Monitoring

Estimation of Packet Loss Rate at Wireless Link of VANET--RPLE