The Application Study Of Smart Agriculture Big Data Server

Networking technology combined with the depth of traditional agriculture,such as data acquisition,remote transmission,automatic monitoring and other functions as representatives of the agricultural systems increasingly popular wisdom.With the agricultural modernization process forward,the number of users growing rapidly wisdom of agricultural systems,thus causing heavy service system pressure,single-server architecture in a highly concurrent load is difficult to meet system requirements.At the same time,agricultural data with large capacity,multi-species,diversified structure and other characteristics of the traditional mode of data storage there is poor reliability,low efficiency in the use of data and other defects,resulting in data storage,data analysis and other issues have become increasingly prominent.To solve the above problem,this paper designed the wisdom of agricultural monitoring system solutions realized data acquisition,display,analysis and device control functions.According to the actual situation of agricultural data storage,combining the characteristics of a distributed framework,the use of distributed load balancing and related technologies,build agricultural data server running platform based on distributed architecture,to provide security for high-performance concurrent applications,and to meet the massive agricultural data reliable and efficient use of storage needs.How to extract useful information from vast amounts of data acquired in the production process guidance,wisdom is key to maximizing the benefits of agricultural systems can be realized.According to agricultural applications,it is proposed based on agricultural data K-Means anomaly detection methods.The combination of analyzing environmental data sample sets,explore the sample set of outliers,can quickly identify undesirable local area,and anomalous data point information in the Web interface alarm display for the timely and efficient agricultural producers to adjust crop growth environment provides more good decision support,improve the yield and quality of crops.Combining the wisdom of agricultural monitoring system designed for distributed agricultural data server running platform and data analysis to ensure system performance and reliability for modern agriculture information,intelligence development provides a viable solution,with better prospects and reference value.