TAGRA 2025

This article presents two complementary microcontroller-based platforms designed to enhance situational awareness and diagnostic capabilities in critical communication and energy infrastructures. The first system is an intelligent interruption detection unit that can distinguish between faults on the feed side and faults on the subscriber side in less than a second. The second system is a modular RF monitoring and active privacy simulation platform designed for portable spectrum analysis, signal direction prediction, and evaluating experimental hidden modes. Both platforms were constructed with cost-effective microcontroller circuit control methods, specifically Arduino Nano and ESP32. These control system topologies provide rapid development, flexible expansion, and seamless connection with sensors and wireless communication interfaces. Experimental results show that the interruption detection unit significantly reduces diagnosis time and operational uncertainty, providing measurable benefits for telecommunications and energy operators. The RF monitoring platform provides lightweight tools for spectrum mapping and fraud testing, which are typically only available with laboratory-grade SDR equipment. This skill opens up new research opportunities in the fields of wireless security, interference reduction, and electronic warfare training. The results indicate that embedded architectures have the potential to offer low-cost, field-deployable solutions for smart infrastructure, smart energy monitoring, and defense industry applications. Future research will focus on the large-scale integration of multi-layered network designs, machine learning-assisted diagnostic systems, and IoT and SCADA-based management frameworks to take measures against previously identified issues.In this context, the proposed platforms highlight the importance of accessible, scalable, and user-friendly embedded technologies that can be adapted to diverse operational environments. By bridging experimental research with real-world deployment needs, this work aims to contribute to more resilient and intelligent infrastructure systems capable of supporting evolving technological demands.