Real-Time Processing of Heterogeneous Data in Sensor-Based Systems

Andrei Dincu, E. Apostol, C. Leordeanu, M. Mocanu, Dan Huru
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Abstract

Nowadays the applications for real time processing of large amounts of data are encountered increasingly more frequently, as there are lots of system's types that can generate large comprehensive information in a relatively short time. In this paper we focus on sensor-based systems. Such systems may be found in several important domains, such as smart farming, medical field, water management, or smart cities. The proposed solution in this paper has the capacity to analyze data streams from different sensors but also considers historical data, in order to provide alerts or invoke different services. This is a new approach, as, to our knowledge, none of the existing stream-processing solutions support combining streaming with batch processing data. We tested our solution with data from sensors and actuators, using a smart farm test scenario.
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传感器系统中异构数据的实时处理
如今,实时处理大量数据的应用越来越频繁,因为有很多系统类型可以在相对较短的时间内生成大量全面的信息。本文主要研究基于传感器的系统。这样的系统可以在几个重要的领域中找到,例如智能农业,医疗领域,水管理或智能城市。本文提出的解决方案不仅能够分析来自不同传感器的数据流,而且还考虑了历史数据,以便提供警报或调用不同的服务。这是一种新方法,因为据我们所知,现有的流处理解决方案都不支持将流处理与批处理数据相结合。我们使用智能农场测试场景,通过传感器和执行器的数据测试我们的解决方案。
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