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Cloud-based service for time series analysis and visualisation in Farm Management System

机译:基于云的时间序列分析和农业管理系统可视化服务

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Nowadays, the use of Internet of Things (IoT) makes more and more devices be capable of producing large amount of data over a short period of time. Sensors started to be used more often which makes them become one of the main sources of structured data that is measured every minute for dozens of environmental parameters, as well as one of the main problems faced by the systems that store, process and analyze this large amount of information. Using IoT there were implemented solutions which imply monitoring different types of environments. Smart cities analyze the measured values for specific parameters to optimize the life quality of the population, smart farms process the data reported by sensors to make an efficient use of resources and traffic applications rely on the collected data from the drivers' smartphones to avoid traffic congestion. This paper describes a solution for large scale time series visualization, offering a generic architecture that can be used in any system that works with structured data and shows how this architecture can be used in a certain system like Smart farms. We present a Cloud-based solution for time series data gathering, the workflow of visualization services and the integration with Farm History and Farm Analytics applications. The performance evaluation of proposed services proves that the solution makes an efficient analysis of data, using both raw data and statistics, depending on the type of visualization.
机译:如今,使用Internet(IoT)使得越来越多的设备能够在短时间内产生大量数据。更频繁地使用传感器使它们成为结构化数据的主要来源之一,这些数据是数十个环境参数的每分钟测量,以及存储,过程和分析这一大的系统所面临的主要问题之一信息量。使用IoT的实施解决方案意味着监视不同类型的环境。智能城市分析了特定参数的测量值,以优化人口的生活质量,智能农场处理传感器报告的数据,以便有效利用资源和流量应用程序依赖于驱动程序智能手机的收集数据来避免交通拥堵。本文介绍了大规模时间序列可视化的解决方案,提供了一种通用架构,可在任何与结构化数据配合使用的系统中使用的通用架构,并显示如何在智能场等系统中使用该架构。我们为时间序列数据收集,可视化服务的工作流程提供了基于云的解决方案,以及与农场历史和农场分析应用程序的集成。拟议服务的性能评估证明,解决方案利用原始数据和统计数据的数据分析,具体取决于可视化的类型。

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