Methods for Processing of Heterogeneous Data in IoT Based Systems

The concept of the Internet of Things (IoT) is based on the idea of a permanent connection between the physical and digital world, which is now technologically feasible. The IoT can describe a scenario in which a large number of objects have built-in uniquely identifiable computing devices connected to the Internet that allow them to collect, store, share and analyze data and to be managed remotely via other devices with an Internet connection. It is important to provide adequate processing of the data to see what is behind it and to assess the situation. The lack of Reference Modelling IoT Architecture prevents a common approach to processing the generated data. The data from various sources has different nature, range, rate and volume. The need to retrieve and analyze this data from the IoT complex systems in real-time requires the application of wide scope of methods and tools. This paper discusses different approaches to process the data from various sources according to different goals: sensing, data analytics, and machine learning with hope that using of IoT will improve all aspects of our life.