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Providing Sensor Services by Data Correlation: The # Smart ME Approach

机译:通过数据相关提供传感器服务:#智能我的方法

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In the current era Internet is the most used medium for sharing and retrieving the information for building applications which are commonly developed for enhancing the user experience in terms of comfort, communication. For this, the need of real-time sensor data gains importance. The data collected from the physical objects should be easily available for different applications. Semantic representation of the sensor data directly addresses the problem of storing it in logical, easily accessible and extensible manner. Our paper works towards converting the already collected sensor data of the #SmartME project into semantic format and also proposes real-time storage of semantically enriched sensor data. To build applications using these sensor data the authors consider mainly three kinds of sensors, i.e., Temperature, Humidity, Pressure. Predicting the observed value of any sensor data is the main aim of this work. The analysis leverages other sensors & environmental parameters such as Date, Time, Longitude, Latitude, Altitude etc. Correlation among these parameters and the accuracy of the predicted results showed the suitability of our proposed idea.
机译:在目前的时代,Internet是用于共享和检索建筑应用的信息的最常用的媒体,这些应用程序通常开发用于增强舒适性,通信方面的用户体验。为此,需要实时传感器数据增长重要性。从物理对象收集的数据应该很容易用于不同的应用程序。传感器数据的语义表示直接解决了逻辑,易于访问和可扩展的方式存储它的问题。我们的论文正在努力将#smartme项目的已收集的传感器数据转换为语义格式,并建议实时存储语义富集的传感器数据。使用这些传感器数据构建应用程序,作者主要考虑三种传感器,即温度,湿度,压力。预测任何传感器数据的观察值是这项工作的主要目的。分析利用其他传感器和环境参数,例如日期,时间,经度,纬度,高度等。这些参数之间的相关性和预测结果的准确性显示了我们提出的想法的适用性。

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