Earthing and short-circuit devices are part of the category of equipment and means of electric shock protection, and their purpose is to protect workers in the event of an accidental voltage in the work area while doing electrical installation work. The purpose of this study is to convey the findings of research into the level of safety that these devices must provide, not only in terms of electrodynamic and electro thermal consequences that occur during a short-circuit, but also in terms of mechanical, chemical, and environmental aspects. The study's risk analysis of safety performance provides critical information for earthing and shortcircuiting device manufacturers to ensure the safety function throughout their use, as well as for workers to pick, use, and maintain.

The transition toward active distribution networks requires advanced control solutions capable of handling the rapid dynamics of distributed energy resources. This paper proposes a low-cost, intelligent IoT architecture designed for the real-time optimization and analysis of energy systems within low-voltage networks. Unlike centralized monitoring approaches constrained by communication latency, the proposed solution leverages Intelligent Edge Processing (IEP) implemented on ESP32 embedded nodes to optimize data flow and decision-making. This architecture executes stability assessments directly at the network edge, calculating critical analysis indicators such as the Voltage Deviation Index (VDI) and Rate of Change of Frequency (RoCoF). The system was validated on the CIGRE European LV benchmark under severe stress scenarios, including rapid solar transients and voltage sags. The results demonstrate that the proposed architecture effectively coordinates storage interventions, ensuring voltage recovery within 300 ms and maintaining power quality within EN 50160 limits even during severe voltage sags. The study validates the feasibility of using industrial IoT edge computing as a resilient, non-wire alternative for modernizing complex energy systems.

The rapid proliferation of single-phase non-linear loads, such as LED lighting and IT equipment, in modern Smart Buildings has introduced significant power quality challenges in low-voltage electrical installations. A critical but often underestimated consequence is the severe overloading of the neutral conductor caused by triplen harmonics (particularly the 3rd harmonic), which sum algebraically even in balanced three-phase systems. This paper analyzes the electrical and thermal impact of these distortions using a detailed MATLAB/Simulink model of a 400/230 V (3P + N) network. The simulation results demonstrate that under highly distorted conditions (Scenario S3), the neutral current can reach 180% of the nominal phase current (18 A vs. 10 A). Furthermore, the Joule losses analysis reveals a thermal stress more than three times higher on the neutral conductor (peak ~65 W) compared to the phase conductor (~20 W), challenging the traditional design practice of neutral undersizing. To address these safety issues, this study proposes a novel neutral-to-phase current ratio index (k_N) and a proactive decision matrix for Building Management Systems (BMS). Unlike traditional mitigation strategies that rely on static hardware oversizing, passive filters, or specialized transformers, the proposed approach offers a dynamic, cost-effective, and software-driven solution that can be easily integrated into the existing automation infrastructure of modern Smart Buildings. The model identifies a critical tipping point at a 3rd harmonic content of 35.3%, where k_N ≥ 1. By continuously monitoring the k_N parameter, the proposed algorithm enables a transition from passive protection to active power management, triggering automated responses to prevent insulation degradation and mitigate fire hazards.

This paper focuses on the interdisciplinary research on the design of a smart gateway for managing the dynamic error code testing collected and generated by the Electronic Control Unit (ECU) from the automotive industry. The techniques used to exchange information between the ECU code errors and knowledge bases, based on data fusion methods, allowed us to consolidate and ensure data reliability, and then to optimize processed data in our distributed electronic systems, as the basic state for Industry 4.0 standards. At the same time, they offered optimized data packets when the gateway was tested as a service integrator for ECU maintenance. The embedded programming solutions offered us safe, reliable, and flexible data packet management results on both communication systems (Transmission Control Protocol/Internet Provider (TCP/IP) and Controller Area Network (CAN) Bus) on the Electronic Control Unit (ECU) tested for diesel, high-pressure common rail engines. The main goal of this paper is to provide a solution for a smart, hardware–software, Industry-4.0-ready gateway applicable in the automotive industry.