Abstract
Mission-critical applications such as environmental sensing, battlefield monitoring, and disaster management are increasingly using wireless sensor networks, or WSNs. These networks rely on widely dispersed sensor nodes to monitor and transmit physical conditions in real time when connected to the Internet of Things (IoT). The overall reliability of the network can be impacted by issues like energy depletion, node failure, and environmental damage, which can lead to coverage gaps in places where communication or sensing is interfered with. A lattice-based coverage hole detection method based on a modified discrete computational geometry model is presented in this paper. The suggested approach accurately determines the precise nodes causing coverage holes and determines the size of each uncovered region with high spatial precision by arranging sensor nodes in a lattice configuration and using a triangulation-based detection algorithm. In comparison to traditional coverage hole detection techniques like Delaunay triangulation and simple grid-based methods, simulation results from a 1000-node network show that the suggested method achieves over 93% energy efficiency, extends network lifetime to over 95%, and reduces control packet overhead by more than 90%. These improvements guarantee more reliable data transfer and a longer running life, which makes the technique ideal for extensive, long-term WSN deployments in demanding and dynamic settings.
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