Analysis of the key models, methods, and means of data collection in the Internet of Things

Abstract

The rapid development of mobile technologies and the technological revolution are contributing to the active implementation of the Internet of Things, leading to an increase in the number of physical devices connected to the Internet. However, along with the advantages of the Internet of Things, there are also growing disadvantages, including cyber threats, privacy violations, and risks of unauthorised data collection. In this regard, research into the challenges and security measures in the field of the Internet of Things is necessary to ensure the safe implementation of these technologies. The purpose of the present study was to analyse key models, methods, and tools for data collection in the Internet of Things environment. The methodological framework of this study included a systematic approach, which allowed presenting public policy in the field of the Internet of Things as a complex, structurally organised system that requires improvement and development. The study employed general scientific and specific methods (systemic, abstraction and comparison, formalisation, institutional analysis, historical-genetic, logical-semantic, classification, generalisation, analysis, formalisation, and comparison), as well as statistical data, which was used extensively and consistently. The study found that among the existing data collection technologies, sensor networks and cloud computing are the most widely used, but they do not cover all the requirements of mobile Internet of Things systems, specifically in terms of energy efficiency, throughput, and security. It was found that modern architectural solutions (including social architectures of the Internet of Things) allow scaling the system and connecting various devices, but have limitations related to deployment complexity and bandwidth. The study also found that the major security threats arise at all levels of mobile Internet of Things networks, from devices to cloud infrastructure, confirming the need for a comprehensive approach to their protection. It was shown that most existing solutions do not simultaneously meet the requirements for low power consumption, speed of data collection and processing in networks with dynamic topology, as well as the requirements for reliability and confidentiality. The proposed developments complemented existing methods, enhancing the flexibility and resilience of the data collection process and laying the foundation for the development of new energy- efficient and secure tools in the Internet of Things