<![CDATA[Effective marine environmental monitoring is critical for ensuring navigational safety, with LoRa technology emerging as a promising solution due to its long-range, low-power capabilities. However, the performance of LoRa networks heavily depends on strategic gateway placement, a task often performed manually, leading to suboptimal coverage. This study addresses this challenge by implementing and validating a Particle Swarm Optimization (PSO) algorithm to determine the optimal placement of gateways for a real-world network of 157 marine buoys in the Madura Strait. The PSO algorithm, configured with 30 particles and 100 iterations, was benchmarked against a baseline manual selection method based on geographic centrality. Results demonstrate a significant performance gain: the PSO-optimized configuration achieved 100% network coverage (157 buoys), a 34.2% increase over the 117 buoys covered by the manual method. These findings confirm that employing PSO for gateway placement substantially enhances network efficiency and data reliability, highlighting its value for creating robust and scalable marine IoT applications.]]>
Copyrights © 2025
