International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

Fast growing market of IoT devices revealed a number of complex problems. Among these problems, there is a problem of data losses caused by data package losses or delays while its transition from sensor to server. As anticipated, there are a number of businesses relying on easy opportunity to build real-time monitoring systems using modern software and IoT hardware solutions. Although the growing reliability of contemporary communication networks one can find the problem of making decision about lost or delayed data packages. Current research is dedicated to building an algorithm for compensation of gaps in data series to support real-time monitoring systems with appropriate artificially generated values. Cases of applicability of the algorithm were also studied and discussed.

Many contemporary IoT systems do produce a large scale of data. While a new portions of data come to data storage (database etc.) all the previously stored data become obsolete. Most of such obsolete data become excessive and can be needed only to see general trends or anomalies. This research offers an algorithm of data aggregation to minimize the amount of stored obsolete data according to defined business rules. Some modifications of algorithm are discussed to fit different kind of business requirements. There is also a comparison of two methods of data merge in algorithm, quantization and clustering, was made.