In order to improve the coverage of Lora gateway communication, taking the coverage of Lora gateway as the maximum target, an improved firefly algorithm based gateway coverage optimization method (IFA) was proposed. Firstly, the Lora gateway communication coverage model is constructed according to the coverage area and the number of the gateway. Secondly, based on the firefly algorithm, particle swarm optimization algorithm is applied to improve the location of the gateway node during its movement, which can effectively improve the coverage uniformity of the gateway, and the coverage of the gateway area can be achieved by simulating the number of Lora gateways through the number of fireflies. Finally, the coverage area of the gateway can be maximized by the improved firefly algorithm. The simulation results show that compared with the basic firefly algorithm and genetic algorithm, the proposed algorithm can consume less resources to achieve better optimization effect, and the coverage rate is improved by 22.54% compared with the previous algorithm, and the coverage rate of gateway nodes is improved better.
In response to sudden water pollution incidents in rivers and canals, a pollution source tracing algorithm is proposed, employing the Markov Chain Monte Carlo (MCMC) method for rapid identification. This algorithm converts the traceability problem into a Bayesian estimation issue and utilizes the Metropolis-Hastings (M-H) sampling algorithm to sample the posterior probability density function. Consequently, it provides probability distributions for the location, time, and mass of pollutants in river canals.
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