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.
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REFERENCES
Xie, Q.J., Su, Z.B., and Ping, Z., Multi-sensor data fusion based on fuzzy neural network and its application in piggery environmental control strategies, J. Inf. Comput. Sci., 2014, vol. 11, no. 15, pp. 5407–5418. https://doi.org/10.12733/jics20104770
Yang, G.N., Feng, X.F., and Fan, L.J., Multi-sensor data fusion algorithm based on optimal fusion set, J. Software, 2012, vol. 23, pp. 134–140.
Sun, R., Huang, H.-Zh., and Miao, Q., Improved information fusion approach based on D-S evidence theory, J. Mech. Sci. Technol., 2008, vol. 22, no. 12, pp. 2417–2425. https://doi.org/10.1007/s12206-008-0801-2
Teng, C.F., Zhao, D.A., and Zhao, J.B., Application of multi-sensor data fusion in piggery environment, Transducer Microsyst. Technol., 2009, no. 12, pp. 109–112.
Li, D., Shen, C., Dai, X., Zhu, X., Luo, J., Li, X., Chen, H., and Liang, Z., Research on data fusion of adaptive weighted multi-source sensor, Comput., Mater. Continua, 2019, vol. 61, no. 3, pp. 1217–1231. https://doi.org/10.32604/cmc.2019.06354
Xia, S., Nan, X., Cai, X., and Lu, X., Data fusion based wireless temperature monitoring system applied to intelligent greenhouse, Comput. Electron. Agric., 2022, vol. 192, p. 106576. https://doi.org/10.1016/j.compag.2021.106576
Zhao, G., Chen, A., Lu, G., and Liu, W., Data fusion algorithm based on fuzzy sets and D-S theory of evidence, Tsinghua Sci. Technol., 2020, vol. 25, no. 1, pp. 12–19. https://doi.org/10.26599/tst.2018.9010138
Chen, Y.L. and Wang, J.J., An improved method of D-S evidential reasoning, J. Syst. Simul., 2004, vol. 16, no. 1, pp. 28–30.
Xing, X.C., Cai, Y.W., and Li, Y., An improved measure factor of evidence of conflict, Telecommun. Eng., 2015, vol. 55, no. 11, pp. 1225–1331.
Liu, Zh.-G., Dezert, J., Pan, Q., and Mercier, G., Combination of sources of evidence with different discounting factors based on a new dissimilarity measure, Decision Support Syst., 2011, vol. 52, no. 1, pp. 133–141. https://doi.org/10.1016/j.dss.2011.06.002
Funding
This work is supported partially by the Special Guidance Foundation for Agricultural Science of Yancheng City, China under grant no. YKN2015024 and the Six Talent Peaks Project in Jiangsu Province, China under grant no. 2015-XNYQC-006.
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Hanhua Yang Research on Multisensor Data Fusion Model for Monitoring Animal Breeding Environment. Aut. Control Comp. Sci. 58, 23–32 (2024). https://doi.org/10.3103/S0146411624010103
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DOI: https://doi.org/10.3103/S0146411624010103