摘要
对物联网技术在农业领域的应用研究进行了调查。结果显示,国内物联网技术在农业领域的应用一直处于示范阶段,仍然存在各种各样的问题。为解决物联网传统数据融合算法的低鲁棒性和数据冗余浪费等问题,在已有数据融合算法的基础上进行了算法优化,并根据农业具体生产环境和科研项目需求,在已有的数据融合算法的基础上提出了限幅滤波平均算法和品质因数法。两算法具有低复杂度和易于实现等特点,可以良好的支持前端采集单片机,使农业生产环境信息数据及时有效的提交到后台数据库中,为上层决策处理系统提供了良好的数据支持。
We first conducted an investigation on the application of IOT （the internet of things） in agricul- tural field. The findings indicated that the domestic application of IOT in agricultural field is still at the demonstration stage with various problems. This article is focused on resolving the problems of low robustness and data redundancy ＆ waste in traditional IOT data fusion algorithms. Furthermore, the article performed algorithm optimization study based on existing data fusion algorithm. Meanwhile, limiting filte- ring average algorithm and quality factor method were proposed on the base of existing data fusion algo- rithm according to the requirements of specific production environment and scientific research in agricul- ture. Both of these two established algorithms had properties such as low complexity and easy-to-be-accomplished, etc, which made the support for front-end acquisition chip properly. So that the environmen- tal information data of agricultural production could be submitted to background database timely and effectively, meanwhile, a proper data support was provided to the upper level decision processing system.
出处
《青岛农业大学学报（自然科学版）》
2016年第1期57-60,67,共5页
Journal of Qingdao Agricultural University(Natural Science)
