农业物联网监控管理系统设计与实现
发布时间：2019-03-16 20:43
【摘要】：物联网被称为继计算机和互联网后的第三次信息技术革命,是互联网的拓展与延伸,通过物物相联真正实现人们对世界的全面感知。农业物联网作为物联网主要应用的众多领域之一,其依赖传感器网络与信息技术推动现代农业发展,改变了依靠种植经验指导农业生产的传统模式,实现了通过传感器网络采集农田信息而科学指导农业生产的精确种植模式,提高了资源利用率与农业产品产量。传感器网络会采集大量的数据信息,如何实现即时查看,远程监控是实际应用中至关重要的一步;而且,农田环境下的传感器节点所处环境恶劣,加上自身损耗,自然会出现损毁情况,要想确保采集数据的准确可靠,节点故障检测也就显得尤为重要。针对以上问题,本文提出的农业物联网监控管理系统从数据处理、数据显示、故障检测等三个方面实现了对农田系统的监控与管理。应用服务程序通过建立SOCKET连接与传感器网络建立通信,接收并存储农田环境的温度、光照、湿度等数据;并以Web应用的形式对传感器网络采集的数据进行远程监控,方便用户查看节点采集数据与网络拓扑结构。在实现以上监控的基础上,还特别提出了基于时空相关性的传感器网络节点故障检测算法。时间相关检测复杂度低但准确度较差,空间相关检测准确率较高但复杂度高,本文综合利用时间相关检测和空间相关检测的特点,在保证检测准确度的前提下,提高了节点故障检测速率。同时,时间相关性检测不需要节点间交换数据,节省了网络的通信成本,在利用空间相关性时还根据聚类算法对空间节点进行分簇,提高相关节点间的空间相关性。
[Abstract]:Internet of things is called the third information technology revolution after the computer and the Internet. It is the expansion and extension of the Internet. It truly realizes people's all-round perception of the world through the connection of things and things. Agricultural Internet of things, as one of the main applications of the Internet of things, relies on sensor networks and information technology to promote the development of modern agriculture, and has changed the traditional mode of relying on planting experience to guide agricultural production. The precise planting mode of collecting farmland information through sensor network and guiding agricultural production scientifically has been realized, and the utilization rate of resources and the output of agricultural products have been improved. Sensor network will collect a large number of data information, how to realize real-time inspection, remote monitoring is a very important step in practical application; Moreover, the sensor node in the farmland environment is in a bad environment, coupled with its own loss, it will naturally occur damage. In order to ensure the accuracy and reliability of the collected data, node fault detection is particularly important. In view of the above problems, the monitoring and management system of agricultural Internet of things proposed in this paper realizes the monitoring and management of farmland system from three aspects: data processing, data display and fault detection. The application service program establishes the communication with the sensor network through the SOCKET connection, receives and stores the farmland environment temperature, the illumination, the humidity and so on data; The data collected in sensor network is monitored remotely in the form of Web application, which makes it convenient for users to view the collected data and network topology of nodes. On the basis of the above monitoring, a node fault detection algorithm based on spatio-temporal correlation is proposed. The complexity of temporal correlation detection is low but the accuracy is poor, the accuracy of spatial correlation detection is high but the complexity is high. This paper comprehensively utilizes the characteristics of time correlation detection and spatial correlation detection to ensure the detection accuracy under the premise of ensuring the detection accuracy. The speed of node fault detection is improved. At the same time, the temporal correlation detection does not need to exchange data between nodes, thus saving the communication cost of the network, and clustering the spatial nodes according to the clustering algorithm to improve the spatial correlation between the related nodes in the use of spatial correlation.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.44;TN929.5;TP311.52
[Abstract]:Internet of things is called the third information technology revolution after the computer and the Internet. It is the expansion and extension of the Internet. It truly realizes people's all-round perception of the world through the connection of things and things. Agricultural Internet of things, as one of the main applications of the Internet of things, relies on sensor networks and information technology to promote the development of modern agriculture, and has changed the traditional mode of relying on planting experience to guide agricultural production. The precise planting mode of collecting farmland information through sensor network and guiding agricultural production scientifically has been realized, and the utilization rate of resources and the output of agricultural products have been improved. Sensor network will collect a large number of data information, how to realize real-time inspection, remote monitoring is a very important step in practical application; Moreover, the sensor node in the farmland environment is in a bad environment, coupled with its own loss, it will naturally occur damage. In order to ensure the accuracy and reliability of the collected data, node fault detection is particularly important. In view of the above problems, the monitoring and management system of agricultural Internet of things proposed in this paper realizes the monitoring and management of farmland system from three aspects: data processing, data display and fault detection. The application service program establishes the communication with the sensor network through the SOCKET connection, receives and stores the farmland environment temperature, the illumination, the humidity and so on data; The data collected in sensor network is monitored remotely in the form of Web application, which makes it convenient for users to view the collected data and network topology of nodes. On the basis of the above monitoring, a node fault detection algorithm based on spatio-temporal correlation is proposed. The complexity of temporal correlation detection is low but the accuracy is poor, the accuracy of spatial correlation detection is high but the complexity is high. This paper comprehensively utilizes the characteristics of time correlation detection and spatial correlation detection to ensure the detection accuracy under the premise of ensuring the detection accuracy. The speed of node fault detection is improved. At the same time, the temporal correlation detection does not need to exchange data between nodes, thus saving the communication cost of the network, and clustering the spatial nodes according to the clustering algorithm to improve the spatial correlation between the related nodes in the use of spatial correlation.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.44;TN929.5;TP311.52
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