In order for automatic microinjection to serve biomedical and genetic research, we have designed and manufactured a PDMS-based sensor with a circular section channel using the microwire molding technique. For the very precise control of microfluidic transport, we developed a microfluidic pulse width modulation system (MPWM) for automatic microinjections at a picoliter level. By adding a computer-aided detection and tracking of fluid-specific elements in the microfluidic circuit, the PDMS microchannel sensor became the basic element in the automatic control of the microinjection sensor. With the PDMS microinjection sensor, we precise measured microfluidic volumes under visual detection, assisted by very precise computer equipment (with precision below 1 μm) based on image processing. The calibration of the MPWM system was performed to increase the reproducibility of the results and to detect and measure microfluidic volumes. The novel PDMS-based sensor system for MPWM measurements of microfluidic volumes contributes to the advancement of intelligent control methods and techniques, which could lead to new developments in the design, control, and in applications of real-time intelligent sensor system control.

Residential consumption represents one of the most important percentages of total electricity consumption. A considerable number of household appliances consume energy even when they are not in operation, i.e., they are in the so-called standby state, thus producing additional costs, which become significant over time. In this context, one method to solve this problem is to develop a smart system capable of severing the power connection to devices in standby mode, thereby conserving energy and reducing the energy costs. The first step in the design of this system consists of the identification and accurate measurement of the standby state, which was carried out for three of the most common household appliances. Then, by using an ESP32 microcontroller, a system was designed to manage the operation of a relay module based on the current consumption of the connected equipment. Control over the system was achieved through a web application that works across all devices equipped with a web browser, offering functionalities to adjust current value time delays and to manually switch the system on or off. Finally, the deployment of this system across the three appliances studied led to a reduction in the energy consumption in standby mode of 26.68 kWh per month.

In recent years, security systems have become a necessity for both companies and the residential sector. This is partly due to the growing national and international crime rate, and on the other hand to legislation in force at European Union level, which in some states goes as far as obliging the owner to implement a security system in order to make the reception of the built house. This paper aims to analyze the energy consumption of a security system for a residential house, reporting this consumption to the average national consumption of a household. For this analysis a common security system has been taken into account, as requested by the majority of beneficiaries. The sizing of the system to match most of the demands of residential homeowners has been carried out by the authors who are security systems specialists with more than 12 years of experience.

Standby power consumption in household electrical and electronic equipment remains a persistent source of energy waste worldwide. Despite regulatory measures and ongoing technological developments, a considerable amount of electricity is still consumed by devices in standby or “off-mode”, resulting in higher utility costs and carbon emissions. This review synthesizes the latest research to clarify the scale of standby energy consumption, discusses relevant policies and regulations, and explores intelligent technologies and behavioral strategies that minimize energy consumption. Starting from the theoretical analysis and modeling of equipment consumption in standby mode to the implementation of intelligent systems to reduce it, the paper highlights heuristic optimization methods, smart grid integration, and occupant-centered interventions, all of which demonstrate tangible energy savings. This research was carried out in close connection with current policies regarding energy consumption and sustainable development, respectively, with the implementation of new technologies. Thus, in accordance with the latest European directives, the intelligent systems used have reduced the energy consumption of some common household appliances by 26.68 kWh. Additionally, knowledge gaps, particularly regarding user behavior, data granularity, and the integration of advanced analytics that limit the efficacy of current solutions, are identified. Recommendations for future research, emphasizing the importance of harmonized policies, precise data measurement, and artificial-intelligence-driven approaches for further reducing standby loads, are finally presented.

The pandemic period was caused by COVID-19 and it has been an unprecedented event in the last 100 years of human history. Regarding universities, major changes have occurred both in the online method of education as well as in the patterns of their electrical consumption, respective of both students’ and teachers’ residential electrical consumption. The focus of this research is to conduct and assess a comparative analysis of universities’ electrical consumption during the pre- and pandemic periods. Polynomial regression is used to model the electrical consumption of four Romanian universities during the period 2019–2021. Also, this study proposes a method for predicting the electrical consumption of universities in three months of 2021, compared to that of the same months in 2020. The data analysis shows that the electrical consumption had decreased between 20.6% and 36.29% in the pandemic period of 2020 compared to that of 2019. Additionally, this study evaluates the electrical consumption of universities due to their use of computers, which represents an important percentage of the total consumption; this was between 11.28% and 60.5% in the pre-pandemic year 2019, but this was substantially reduced in 2020, to be between 57.13% and 77.27%. Based on the data that has been provided by students and teachers, the calculated values show that the electrical residential consumption increased by about 20 kWh per month and per computer unit during the pandemic.

A non-sinusoidal regime is commonly found in power grids and affects the nominal operation and performance of industrial equipment supplied by the electrical network. The non-sinusoidal regime is mainly caused by nonlinear circuit elements, especially power-electronic devices. In real industrial cases, the harmonic content of voltage and current varies; consequently, the RMS values can change significantly, influencing both power flow and power quality. To determine these variations, this article proposes a method for analyzing the dependence between the harmonic weights of voltage and current and the sensitivities of reactive and apparent powers. After introducing dependency relationships between real, reactive, and apparent powers and harmonic weights, the method uses these relationships to calculate sensitivities when one or more parameters are modified. A numerical algorithm is implemented in MATLAB/Simulink to determine the sensitivities in a real case. The values obtained are compared with those directly calculated from measured data, and the small errors demonstrate the accuracy of the proposed method.