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

机译:用于农场管理系统中时间序列分析和可视化的基于云的服务

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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,物联网(IoT)的使用使越来越多的设备能够在短时间内产生大量数据。传感器开始被越来越频繁地使用,这使其成为对数十个环境参数每分钟进行测量的结构化数据的主要来源之一,同时也是存储,处理和分析如此庞大的系统所面临的主要问题之一。信息量。通过使用物联网,已实现的解决方案暗示了监视不同类型的环境。智慧城市分析特定参数的测量值以优化人口的生活质量,智慧农场处理传感器报告的数据以有效利用资源,交通应用依靠驾驶员智能手机收集的数据来避免交通拥堵。本文介绍了用于大规模时间序列可视化的解决方案,提供了可在任何使用结构化数据的系统中使用的通用体系结构,并说明了如何在诸如Smart farms的某些系统中使用此体系结构。我们提供了一种基于云的解决方案,用于时间序列数据收集,可视化服务的工作流程以及与“农场历史”和“农场分析”应用程序的集成。对提议服务的性能评估证明,该解决方案可以根据可视化类型使用原始数据和统计数据对数据进行有效的分析。

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