• BUSINESS & “INDUSTRY 4.0”

    OPPORTUNITIES OF IMPLEMENTATION OF “INDUSTRY 4.0” FOR DEVELOPMENT OF TRANSPORT INDUSTRY IN UKRAINE

    Industry 4.0, Vol. 3 (2018), Issue 2, pg(s) 94-96

    Due to intentions of Ukrainian economy to join European Union there are many threats and opportunities on the way. Ukraine has a number of industries producing goods, products and services needed in Europe. The growth of economic ties with EU makes Ukrainian manufactures stronger and has become a question of key importance during last decade. Meantime, Ukraine remains within rather tense conditions of technological lag but with some promising abilities in agriculture and food industries supplemented with a great potential in area of information technologies. This distinctive combination of abilities make it feasible for Ukraine both to become a strong partner for EU and to do a great leap of industrial progress within “Industry 4.0” concept. Nevertheless, one of crucial problems for Ukraine is to build an innovative infrastructure to meet requirements of intellectual transport system conforming to EU “Industry 4.0”. This research paper is focused on discussion of these new features of transport industry and opportunities for Ukraine to make its transport industry a leading advantage for the whole economy. Those drastic changes in Ukrainian transport would procure an excellence for other industries implementing “Industry 4.0”, the same as to become a test ground and an exclusive source of experience for EU on “Industry 4.0” implementation.

  • THEORETICAL FOUNDATIONS AND SPECIFICITY OF MATHEMATICAL MODELLING

    ABOUT THE PROBLEM OF DATA LOSSES IN REAL-TIME IOT BASED MONITORING SYSTEMS

    Mathematical Modeling, Vol. 1 (2017), Issue 3, pg(s) 121-122

    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.

  • TECHNOLOGICAL BASIS OF “INDUSTRY 4.0”

    BIG DATA AGGREGATION ALGORITHM FOR STORING OBSOLETE DATA

    Industry 4.0, Vol. 3 (2018), Issue 1, pg(s) 20-22

    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.