An adaptive iterative weighted fusion algorithm based on pig farm environment detection

The traditional way of information collection in pigsty environment often results in uneven distribution of collected information due to sensor distribution, environmental noise and other problems, and the statistical results are biased, thus affecting the final decision-making. Based on this problem, in order to improve the accuracy of piggery environmental information collection, this paper proposes an adaptive iterative weighted fusion algorithm to improve piggery environmental monitoring. The experimental results show that the fusion variance obtained by using the simple arithmetic mean method is larger, and the variance obtained by using the adaptive weighted fusion algorithm is about 2 times lower than that obtained by using the simple arithmetic mean method, but the adaptive weighted fusion algorithm will have the problem of variance value ossification, which is solved by using the adaptive iterative weighted fusion algorithm, and the pig house environment is improved monitoring effect.