One Approach of Approximation for Incoming Data Stream in IoT Based Monitoring System

IoT devices and platforms are a fast growing market. One can mention a number of businesses relying on easy opportunity to build real-time monitoring systems using modern software and IoT hardware solutions. However, the growth has revealed a number of complex problems. Many problems are in area of data processing and storing huge volumes of information. Due to wide use of different kinds of sensors, and even a sets of sensors within each single device, on one hand, practitioners discover unpleasant effects of data losses caused by data packages losses or delays while its transition from sensor to server. On the other hand, huge volumes of data require to use some big data approaches and many startup projects feel the problem of lack of resources. Many of them feel lack of data storage facilities or become unable to support huge data sets due to lack of finance. The paper is focused to research the problem approximation for incoming data stream to make it smaller the volume of data to be stored but to keep it possible to be used. A few approaches to use such data compression via its approximation are discussed with application to IoT based real-time monitoring system.