sensor network

The application of intelligent sensors, network technologies, and machine learning in IoT and industry is increas- ingly widespread as a part of the development and implementation of Industry 4.0, Industry 5.0, and Smart City. It is necessary to review the fundamental principles of metrological support for production. This includes calibration, estimation of measurement uncertainty, traceability, and processing of large data sets to reproduce and compare the results of measurements of physical quan- tities remotely.

One of the main tasks of deploying sensor networks is determining the coordinates of nodes that are unknown at their initial placement. This problem is known as the localization problem of sensor networks. It can be solved if each node has a GPS receiver in its composition. However, such nodes are more expensive, and for networks of various purposes, for example, environmental monitoring, fixation of moving objects in a certain area, various types of IoT, and others, nodes without GPS can be used.

The article presents a simulation model and described appropriate software, to simulate the environment in an emergency situation (accidents on chemically hazardous objects) or free observation (no pre-defined procedures). Collection and processing of information made using a wireless sensor network.

In wireless sensor networks (WSN) is important task of self-organization networks. There are many different algorithms for self-organization of such networks. This choice determines the relevance of pre-emptive self-algorithm network with the additional information obtained from experts. In the article features practical application of the analytic hierarchy process to select a preferred algorithm for self-organization in wireless sensor networks.