Efficient Energy Mechanism in Heterogeneous WSNs for Monitoring Applications in Underground Mining

PROJECT TITLE :

Efficient Energy Mechanism in Heterogeneous WSNs for Underground Mining Monitoring Applications

ABSTRACT:

Wireless Sensor Networks, also known as WSNs, are an essential component of several underground mining application systems. In particular, they assist in the collection of information through the use of sensors and provide monitoring of complex mine environments in order to avoid potential risks and effectively manage operations. Despite the significance of WSNs, they are plagued by the issue of excessive energy consumption as well as the challenge of effectively replacing the batteries that power the sensor nodes. The distributed energy-efficient aggregation protocol, also known as DEECP, contributes to the WSN's decreased reliance on external power sources. The lifespan of a WSN can be extended thanks to the implementation of this protocol. The DEECP algorithm makes use of the clustering concept and chooses cluster heads (CHs) in accordance with the election probability based on the ratio of each node's residual energy to the network average energy. On the other hand, due to the fact that it does not take into account the various sensor energy levels, this method does not produce the best possible solution. The effect of the distance between the base station and the sensor node that will most likely be chosen to become a CH is not taken into account by the algorithm, which is another drawback. Because of this, the performance of the WSN may be significantly impacted. This paper proposes an optimization threshold for CH selection that is based on three energy levels of a sensor, namely, low, high, and super, as well as the measurement of the distances between base stations and possible nodes to be selected as CHs in order to optimize the CH selection method. Additionally, this paper measures the distances between base stations and possible nodes to be selected as CHs. The proposed method is examined and contrasted with DEECP with regard to the number of dead nodes, the number of alive nodes, and the network throughput. According to the findings, the approach that was proposed is superior to DEECPs in terms of both the stability of the network and its lifetime.

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