The global energy transition is characterized by the simultaneous challenges of decarbonization, digitalization, and decentralization [...]

Landslides pose a serious hazard worldwide, and monitoring their slow displacements is crucial for early warning and risk mitigation [1]. Global Navigation Satellite System (GNSS) sensors provide continuous 3D positioning in all weather, but conventional geodetic-grade GNSS are expensive and fragile in harsh terrain. Recent years have seen the rise of low-cost GNSS units that offer centimeter-level accuracy at a fraction of the cost [2]. This paper reviews technical innovations that enable such performance, focusing on real field deployments. Key advances include high-precision positioning techniques (RTK and Precise Point Positioning, PPP) and hybrid PPP-RTK corrections that speed up convergence, data-driven approaches like “Virtual RINEX” (VRINEX) to emulate reference observations [3] [4], and integration of inexpensive MEMS inertial sensors to suppress GNSS noise [5]. Open-source processing (e.g. RTKLIB-based workflows) and community tools now make low-cost GNSS monitoring more accessible. Field tests confirm that properly deployed dual-frequency low-cost GNSS stations can track subcentimeter displacements. We summarize 14 representative studies, compare their setups and results (Tables 1&2), and conclude that multi-constellation dual-frequency receivers, short baselines or VRINEX references, and hybrid processing are recommended for cost-effective landslide monitoring. Future work should emphasize long-term autonomous networks and real-time PPP-RTK services to further democratize GNSS hazard monitoring.

This paper explores the integration of control and monitoring systems within a graphical environment where factory (production line) simulations can be conducted. Gamification of simulators enables realistic testing of proposed solutions, allowing errors to be identified and resolved before equipment is installed in real factories. In this way, the 1-10-100 rule can be applied, where quality issues and costs grow rapidly depending on the stage at which they are detected. The most effective approach is to use simulators to verify design of factories before purchasing and installing components. For this reason, the new generation of gamified simulators can significantly reduce both costs and development time for new factories. When including components from different manufacturers and various types of equipment such as PLCs, robots, and CNC machines, gamified simulators can support rapid prototyping of industrial environments. The Simulator Factory I/O, in combination with TIA Portal, is recognized as an adequate environment for verifying the proposed design of an entire factory or a specific part of a production line

Monitoring landslide activity demands positioning systems that can operate continuously in difficult terrain while maintaining high accuracy. Traditional geodetic GNSS receivers provide excellent precision but are often too costly and delicate for large-scale deployments. Recent developments in affordable GNSS hardware have opened new opportunities for building dense monitoring networks at a fraction of the expense. This paper reviews the hardware components most critical to such systems, including receiver types, antennas, power solutions, and communication links. Low-cost single-frequency devices, such as u-blox modules, demonstrate promising results under favorable conditions, though they require longer convergence times. Dual-frequency receivers, such as the ZED-F9P, deliver faster initialization and more reliable precision, albeit with higher cost. Antenna configuration further influences performance, with geodetic-grade options ensuring stability and calibrated patch antennas offering practical compromises. Field deployments typically integrate solar panels with battery storage and rely on cellular or radio communication for real-time data transfer. With overall system costs ranging from €500 to €1500 per station, properly configured low-cost units have proven capable of tracking ground displacements with sufficient accuracy for landslide monitoring. The evidence suggests that careful hardware integration, balancing receiver choice, antenna performance, autonomous power supply, and connectivity is key to designing effective and resilient GNSS monitoring networks.

This article presents the design of an IoT communication gateway architecture aimed at collecting data from wireless sensor nodes, processing it using edge computing techniques, and distributing it to higher-level systems, such as cloud technologies. The architecture is tailored for long-term outdoor installations and incorporates a backup communication channel to enhance system reliability. The design prioritizes energy efficiency and resilience to harsh climatic conditions. To validate the system’s functionality and reliability, in-situ testing was conducted, allowing for real-world testing and generating valuable data for further system optimization.

This study describes a method for measuring flexion and extension motions in the hand, which is crucial for healing and restoring a complete range of motion following accidents. Precise control is essential because of the human hand's intricate anatomy, which consists of various bones and joints. The method replicates the trajectories of the five fingers, emphasizing their position, speed, acceleration, and torque at four crucial structural points: four fingers that stretch to 90 degrees and then return to 0 degrees, with the thumb creating a 20-degree angle, a crucial initial position for successful recovery. The ability to simulate these trajectories is essential for correctly tracking patients' progress and customizing rehabilitation treatments, both of which improve patient care and rehabilitation outcomes.

This paper presents a comprehensive comparative analysis of Golden Section Search (GSS), Artificial Neural Network (ANN), and Adaptive Neuro Fuzzy Inference System (ANFIS), alongside well-known Perturb and Observe and Incremental Conductance (INC) Maximum Power Point Tracking (MPPT) algorithms for Photovoltaic (PV) system. The methodology involves theoretical development, simulation, and real-time experimentation using Matlab/Simulink and the Humusoft MF 634 data-acquisition card. Real-time experiments validate algorithm effectiveness under real-world conditions, facilitated by precise control mechanisms using Taraz's power electronics converter modules. The results contribute to ongoing efforts in optimizing MPPT technology and advancing the efficiency of PV systems for renewable energy generation.

As the future electric power grid will be driven by distributed renewable energy sources, the deployment of grid-connected power converters will also grow to enable seamless grid and energy source interaction. To provide the reliable operation of these converters, the estimation of fundamental grid parameters is important. The most common estimation techniques are a phase-locked loops (PLL) and a frequency-locked loops (FLL). However, those techniques encounter challenges in conducting parameter estimation when the input signal is unbalanced due to DC-offset, harmonics, signal sags, and frequency and phase variations. This paper presents an enhanced FLL loop enriched with an additional loop for estimation and rejection of the DC-offset. Active and reactive power calculations in grid-connected microgrids by using the modified FLL loops with DC-offset rejection is a novel application introduced in this paper. Experimental verification has demonstrated that the enhanced FLL loop provides fast and reliable parameter estimation as well as stable and robust power calculations, even in the presence of a DC-offset.