Abstract

This article analyzes and characterizes various aspects of constructing an information system for monitoring physical parameters based on Internet of Things (IoT) technology. The key components of such systems are thoroughly examined, including sensor utilization, selection of network technologies, and specialized IoT platforms. An analysis of modern LPWAN (Low-Power Wide Area Network) technologies such as LoRaWAN, Sigfox, and NB-IoT is conducted, outlining their main characteristics and features, including data transmission speed, network coverage range, and energy consumption levels. The structure and components of these network types are analyzed, and schematic representations highlighting their key differences are provided. Additionally, an analysis of available IoT platforms that facilitate data collection, processing, and analysis from sensors is carried out. The functional and integration capabilities of these platforms with LPWAN technologies are assessed. Expert evaluation criteria essential for comparing and selecting optimal technologies, protocols, and platforms are examined. The results are systematized into a weighted overall optimality criterion and tables with expert assessments for each type of LPWAN network technology. The problem of determining the optimal technology is formalized as a linear programming task. The automated solution to this problem is implemented using Python and the PuLP library. Examples of solving the task and selecting technologies for building an information system for monitoring physical parameters based on IoT technology under various conditions are presented. The results of the practical implementation of a temperature monitoring system in a scientific laboratory, developed using the findings of this article, are described. The main scientific achievement of this research is an improved method for multicriteria selection of optimal network technologies and IoT platforms for building an information system for monitoring physical parameters based on IoT technology. The practical value of the obtained results lies in the ability to construct an efficient monitoring information system that is optimal across multiple criteria. The obtained results enable an informed selection of LPWAN network technology and IoT platforms based on specific system requirements and needs. The developed Python code solution provides a practical tool for optimizing technology selection.

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