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This article presents novel research on the utilization of a neural-network-based time control system for microwave oven heating of food items within a solar-powered vending machine. The research aims to explore the control of heating time for various food products, considering multiple variables. The neural network controller is calibrated through extensive experimentation, allowing it to accurately predict optimal heating times based on input parameters such as food type, weight, initial temperature, water content, and desired doneness level. The results demonstrate that the neural-network-controlled microwave oven achieves precise and desirable heating durations, mitigating the risk of overheating and ensuring superior food quality and taste. Moreover, the solar-powered vending machine showcases a commitment to sustainable energy sources, effectively reducing dependence on non-renewable energy and minimizing greenhouse gas emissions. To maintain food quality and freshness, a food refrigeration unit is integrated into the vending machine, employing load-balancing technology to control the refrigeration chamber’s temperature effectively. Energy efficiency is prioritized in both the refrigeration unit and the microwave oven through intelligent algorithms and system optimization. The combination of a neural-network-controlled microwave oven, a solar-powered vending machine, and a food refrigeration unit introduces a novel and sustainable approach to food preparation and energy management.

The management of construction equipment on a construction site is particularly important for increasing productivity on construction sites. High productivity has financial implications for the economics of construction projects and leads to reduced energy consumption. Reducing energy consumption in construction machinery has an impact on reducing greenhouse gase emissions. Monitoring construction equipment and optimizing movement trajectories is a challenge on a construction site and is possible in real ti me with drone photogrammetry technology. Using this technology, we can track the construction machines and the progress of the works in real time, and later, by using AI technology, the management of equipment on construction sites can be improved in real time.

Escalators are an important piece of equipment used for vertical transportation of people in buildings. In today’s context, when the reduction of greenhouse gas emissions is a global challenge, the energetic efficiency of escalators in operation becomes a priority. The research aims to identify possibilities to reduce the energy consumption of this category of equipment. In this respect, we have undertaken a series of tests to establish a correlation between passenger traffic and electrical energy consumption. The tests were carried out for an existing escalator and represent the first step in developing solutions to optimize the operation of such equipment. The energetic efficiency of escalators in operation needs to be customized for each model and involves finding parameters that can be modelled to reduce electrical energy consumption.

This study carries out a literature review on artificial intelligence techniques used in building services for energy economy while maintaining the comfort of the occupants. The building services in which artificial intelligence techniques are used the most are: lighting systems, HVAC (heating, ventilation and air conditioning) systems, heating systems which use radiators and we also decided to include dynamic shading systems in here. The artificial intelligence techniques which are used the most in the recent years in building services are: fuzzy logic, artificial neural networks and for optimization problems, genetic algorithms are used. These techniques are utilized in many occasions to build predictive models or occupancy-based models.

This study carries out a literature review on artificial intelligence techniques used in building services for energy economy while maintaining the comfort of the occupants. The building services in which artificial intelligence techniques are used the most are: lighting systems, HVAC (heating, ventilation and air conditioning) systems, heating systems which use radiators and we also decided to include dynamic shading systems in here. The artificial intelligence techniques which are used the most in the recent years in building services are: fuzzy logic, artificial neural networks and for optimization problems, genetic algorithms are used. These techniques are utilized in many occasions to build predictive models or occupancy-based models.

In the current energetical context, there is a need to diversify energetically independent applications. The presence of energetically independent vending systems is necessary in the smart cities of the future and beyond. Energetically independent vending equipment must ensure the delivery of cold or hot products with low energy consumption. Reduced energy consumption and the use of environmentally friendly sources lead to reduced greenhouse gas emissions and at the same time to higher energy autonomy. The paper presents the results obtained from testing the innovative experimental sales system developed to study the energetic efficiency of this equipment. The innovative sales system is a complex system that integrates energy production and storage, cooling and heating systems. The fully automated system allows cold storage of products and their subsequent delivery, cold or hot, on demand. The vending system was powered by electrical energy from an array of photovoltaic panels. The results obtained, summarized in the paper, lead to the possibility of developing stand-alone vending equipment with significant reduction of greenhouse gas emissions in urban agglomerations.

The unbalanced operation of the three-phase grid has a large number of negative consequences. The solution to this problem of unbalance, problem that appears whenever an unbalanced or single-phase load is connected to the network can be based either on conversion, or on compensation. Compensation based methods are capable of compensating not only the unbalanced operations, but also the non-sinusoidal and reactive operations. Former papers of the authors study the compensations methods. In this paper there is developed a Lab View virtual instrument capable to calculate the unbalance factor of the grid and to control the active power filter used for compensation. The developed virtual instrument enables the activation of the compensation depending on the values of the measured and calculated unbalance factor. The method compensates the nonsinusoidal, reactive and unbalanced operations of the three-phase grid. Measurements prove the instrument s efficient operation and the method s viability.

This paper intends to present the differences appearing between the pervasive systems and other usual systems regarding the tuning of the fuzzy controllers. For the pervasive systems used in the intelligent buildings, the emphasize is on the building's occupant and the used equipment is to be engineered so that the occupant will be as less perturbed by its presence or settings. For the fuzzy controllers used in non-pervasive systems - although the occupants are not working with physical quantities, but with language described variables, the definition of the inputs' and outputs' domain values can be modified only by reprogramming. The result generated by the research work that lays at the basis of the present paper is the tuning of the fuzzy controllers used in pervasive systems. The occupants role is to describe the sensation they have in the very moment, the sensation they would like to have, and the fuzzy controllers' inputs and outputs will be automatically modified based on different parameters regarding the occupants, for example the clothes worn. The tuning of the fuzzy controllers for the pervasive systems has not been treated before, the authors intending to make a detailed and deep research in this field.

The experts of the pervasive systems do say that these systems will be developed in two steps: a first step comprising of relatively small applications and a second step comprising in the engineering of a complex system. This paper can be included in the research work related to the first step. The proposed idea is intending to allow for the aged people to remain a longer time in their own homes, having meanwhile the benefits of proper assistance. The proposed method has been engineered in order to ensure the aged peoples' intimacy, by replacing the human surveillance by continuous sensor based surveillance. Whenever there is an accident or an unusual event or activity in the monitored home, the system will transmit alerts directly to the set mobile phones. The result generated by the research work that lays at the basis of the present paper is the realization of a pervasive system in order to monitor the home of one or more aged people and to transmit alerts to mobile phones when an unusual behavior is detected. Although this pervasive system supposes the use of a lot of sensors, its advantages for the aged people do recommend its use.