Prototypes of Intelligent Security and Infrastructure Management Systems Based on IoT Platforms

Abstract

In modern engineering projects, the development of intelligent security and infrastructure management systems is becoming increasingly important due to growing demands for efficiency, reliability, and adaptability of engineering solutions in technologically complex environments. Rapid urbanization, increased traffic flows, and the growing complexity of building architectures require the implementation of advanced monitoring and control technologies. In this context, the integration of the Internet of Things (IoT) concept, software platforms, and algorithmic data processing methods is key to creating next-generation comprehensive engineering solutions. The research focuses on developing a hardware–software complex that combines sensor devices, communication protocols, and data processing algorithms. Particular attention is given to the development of methods for real-time data collection, analysis, and interpretation, enabling effective engineering decision-making. An analysis of Ukrainian studies has shown that existing systems are mainly focused on specific aspects—such as energy efficiency of sensor networks, routing algorithms, or local IoT device protection—and often lack comprehensive validation. This highlights the need for integrated solutions that provide real-time data stream processing, multi-level information protection, scalability, and system reliability. The experimental part includes a prototype system for room monitoring and parking management using sensors and cameras, where data are aggregated and processed by artificial intelligence algorithms. System performance is evaluated based on detection accuracy, processing latency, data stream throughput, average energy consumption, and reliability. The construction of synchronized datasets with timestamps and unique identifiers ensures data coherence and allows optimization of the balance between reaction speed and energy efficiency. Future research prospects include expanding the sensor network, integrating various data types, implementing adaptive load-balancing algorithms, and developing AI models for anomaly prediction and automatic system configuration, which will enhance the reliability and efficiency of IoT solutions in critical and long-term operational scenarios