Research on Multisensor Data Fusion Model for Monitoring Animal Breeding Environment

Abstract

A two-level multisensor data fusion model is proposed to monitor animal breeding environment. The effectiveness of various sensors is judged by the first level of analysis, and the data are screened by calculating the optimal fusion set. The probability distribution function is calculated using fuzzy membership degree and the final decision is obtained using an improved information fusion approach based on D-S evidence theory by the second level of analysis. Conflict allocation is more reasonable when using the improved D-S and the fusion effect is better. Therefore, the real state of the piggery environment can be obtained based on the fusion result, so as to perform corresponding operations on the field equipment.