Lithium-ion batteries are widely utilized in various fields, including aerospace, new energy vehicles, energy storage systems, medical equipment, and security equipment, due to their high energy density, extended lifespan, and lightweight design. Precisely predicting the remaining useful life (RUL) of lithium batteries is crucial for ensuring the safe use of a device. In order to solve the problems of unstable prediction accuracy and difficultly modeling lithium-ion battery RUL with previous methods, this paper combines a channel attention (CA) mechanism and long short-term memory networks (LSTM) to propose a new hybrid CA-LSTM lithium-ion battery RUL prediction model. By incorporating a CA mechanism, the utilization of local features in situations where data are limited can be improved. Additionally, the CA mechanism can effectively mitigate the impact of battery capacity rebound on the model during lithium-ion battery charging and discharging cycles. In order to ensure the full valid... [more]

In recent years, cellular communication systems have continued to develop in the direction of intelligence. The demand for cellular networks is increasing as they meet the public’s pursuit of a better life. Accurate prediction of cellular network traffic can help operators avoid wasting resources and improve management efficiency. Traditional prediction methods can no longer perfectly cope with the highly complex spatiotemporal relationships of the current cellular networks, and prediction methods based on deep learning are constantly growing. In this paper, a spatial-temporal parallel prediction model based on graph convolution combined with long and short-term memory networks (STP-GLN) is proposed to effectively capture spatial-temporal characteristics and to obtain accurate prediction results. STP-GLN is mainly composed of a spatial module and temporal module. Among them, the spatial module designs dynamic graph data based on the principle of spatial distance and spatial correlation... [more]

In the Industry 4.0 environment, an ideal smart factory should be intelligent, green, and humanized, and the logistics transportation from raw materials to final products in the factory should be completed by smart logistics. In order to address the problems of low efficiency, poor workstation service satisfaction, high distribution costs, and non-greening during the logistics distribution processes in discrete smart manufacturing workshops are required. A mathematical model of optimized multi-objective green logistics distribution paths in a smart manufacturing workshop has been constructed in this study, with low costs, high efficiency, and workstation service satisfaction taken into consideration. Then, this mathematical model was solved with an improved ant colony optimization algorithm. A “time window span” was introduced in the basic ant colony optimization algorithm to prioritize the services to workstations with a relatively high urgency in material demand, with the aim of impr... [more]

Smart manufacturing has become a vital technique for increasing productivity and efficiency. Firms are following a smart manufacturing implementation system to compete in the market. Therefore, it is mandatory to find the crucial factors that enable the implementation of intelligent manufacturing in enterprises. This study proposes the framework for a new model factory based on the three-dimensional model that extends the product lifecycle layer. It also analyzes the significant attributes and interdependence relationships of causes and effects through the fuzzy DEMATEL approach for the selected small and medium enterprises discussed as a case study. The results show that the factors in Region 1 are significant attributes that need to be focused on for the development and establishment of small and medium enterprises under consideration. These attributes include design documentation (A11), intelligently management of small and medium enterprises (A3), visualization and monitoring of lo... [more]

In recent years, the accelerating climate change and intensifying natural disasters have called for more renewable, resilient, and reliable energy from more distributed sources to more diversified consumers, resulting in a pressing need for advanced situational awareness of modern smart distribution systems [...]

Wireless sensor networks have attracted much attention recently due to their various applications in many fields [...]

Because of the problems, such as the lack of an electric power diagram atlas under different working conditions and the difficulty in intelligent diagnosis of variable torqued pumping unit wells, this paper proposes a diagnosis model of working conditions based on feature recognition. The mathematical relationship model between the polished rod load and motor output power is derived based on the analysis of geometric structure, motion law, and process of energy transformation and transfer of the variable torque pumping unit. It can calculate the electric power diagram based on a dynamometer card. On this basis, the electric power diagram atlas is created, and the feature analysis and eigenvalue extraction of the electric power diagrams under different working conditions are carried out to realize the direct diagnosis of the working conditions in the variable torque pumping unit wells. The application and analysis of examples show that the electric power diagram atlas created in this pa... [more]

The aim of the study is to present the implemented “smart” solutions and the developed indicators of their measurement in the context of the city of Częstochowa (Poland), as well as a participant in the “Benchmarking—we are looking for the best smart city solutions”. In order to achieve the assumed goal, a traditional review of the literature on the subject in the field of “smart city” was carried out. Then, the methodological assumptions related to developing a model set of indicators for cities participating in the program have been presented. In addition, a comparative analysis of the obtained indicators values for cities, Częstochowa and Bydgoszcz, has been carried out in the scope of one exemplary measure. The proposed research procedure can be used to analyze and evaluate cities in the country, as well as to select alternative solutions in the context of other urban features. Due to the fact that other cities in Poland will also participate in the study, the significance of this... [more]

With the constant growth of requirements to the quality of infocommunication services, special attention is paid to the management of information transfer in wireless self-organizing networks. The clustering algorithm based on the Motley signal propagation model has been improved, resulting in cluster formation based on the criterion of shortest distance and maximum signal power value. It is shown that the use of the improved clustering algorithm compared to its classical version is more efficient for the route search process. Ant and simulated annealing algorithms are presented to perform route search in a wireless sensor network based on the value of the quality of service parameter. A comprehensive routing method based on finding the global extremum of an ordered random search with node addition/removal is proposed by using the presented ant and simulated annealing algorithms. It is shown that the integration of the proposed clustering and routing solutions can reduce the route sear... [more]

This study provides insights into the initial and post-adoption of cloud computing services by integrating information technology adoption, social influence, trust, security, and information systems quality theories. Social influence, hedonicity, and automaticity are hedonic predictors of user satisfaction with cloud computing services. Perceived risks, trust in the provider, and system quality are utilitarian predictors of user satisfaction with cloud computing services. The Partial Least Squares (PLS) was employed to test eight hypotheses on the causal relationships between the variables. Six out of eight hypotheses were supported. Hedonic factors appear to have more influence than the utilitarian factor of increasing user satisfaction with cloud computing services in the school setting. The findings lead to both theoretical and practical implications for improving the initial and post-adoption of cloud computing services.

This paper presents an intelligent system for the detection of non-technical losses of electrical energy associated with the fraudulent behaviors of system users. This proposal has three stages: a non-supervised clustering of consumption profiles based on a hybrid algorithm between self-organizing maps (SOM) and genetic algorithms (GA). A second stage for demand forecasting is based on ARIMA (autoregressive integrated moving average) models corrected intelligently through neural networks (ANN). The final stage is a classifier based on random forests for fraudulent user detection. The proposed intelligent approach was trained and tested with real data from the Colombian Caribbean region, where the utility reports energy losses of around 18% of the total energy purchased by the company during the five last years. The results show an average overall performance of 82.9% in the detection process of fraudulent users, significantly increasing the effectiveness compared to the approaches (68%... [more]

I4.0 promotes a future in which highly individualized goods are mass produced at a competitive price through autonomous, responsive manufacturing. In order to attain market competitiveness, organizations require proper integration of I4.0 technologies and manufacturing strategy outputs (MSOs). Implementing such a comprehensive integration relies on carefully selecting I4.0 technologies to meet industrial requirements. There is little clarity on the impact of I4.0 technologies on MSOs, and the literature provides little attention to this topic. This research investigates the influence of I4.0 technologies on MSOs by combining reliable MCDM methods. This research uses a combination of fuzzy DEMATEL and fuzzy TOPSIS to evaluate the impact of I4.0 technologies on MSOs. The fuzzy theory is implemented in DEMATEL and TOPSIS to deal with the uncertainty and vagueness of human judgment. The FDEMATEL was utilized to identify interrelationships and determine criterion a’s weights, while the fuzz... [more]

The article presents the problems of diagnostics of low-power solar power plants with the use of the three-valued (3VL) state assessment {2, 1, 0}. The 3VL diagnostics is developed on the basis of two-valued diagnostics (2VL), and it is elaborated on. In the (3VL) diagnostics, the range of changes in the values of the signals from the 2VL logic was accepted for the serviceability condition: state {12VL}. This range of signal value changes for logic (3VL) was divided into two signal value change sub-ranges, which were assigned two status values in the logic (3VL): {23VL}—serviceability condition and {13VL}—incomplete serviceability condition. The state of failure for both logics applied of the valence of states is interpreted equally for the same changes in the values of diagnostic signals, the possible changes of which exceed the ranges of their permissible changes. The DIAG 2 intelligent system based on an artificial neural network was used in diagnostic tests. For this purpose, the a... [more]

Cities have been struggling for many years with many transport problems, including the impact of carbon monoxide emitted by vehicles on the environment, traffic jams, high energy consumption, numerous accidents or high infrastructure costs. There is also a dynamic growth of vehicles on the roads, which is why an increasing number of cities are introducing intelligent transportation systems (ITS), which is part of the concept of smart cities. This paper proposes a new matrix to assess the effects of the ITS implementation in the context of a concept Smart City, which consists of five criteria: (1) movement speed; (2) safety; (3) environmental; (4) economic; (5) satisfaction and amenities for society/passengers. In this new approach the benchmark values of the indicators assigned to the criteria are involved and, therefore, it is possible to determine the level of effectiveness of the ITS in public transport that uses low-carbon energy. This research used literature studies to establish... [more]

Nowadays, one of the main sources of renewable energy is wind energy; therefore, a wind farm’s electricity system must be effective. As a result, wind farm (WF) equipment must continuously operate without failure or damage. To achieve this, it is necessary to regularly monitor and assess the reliability of WF systems at every point of their “life”, including design, implementation, and continued use. Three key goals are presented in the article. First, a theory of fundamental theoretical quantities that can be used in reliability and maintenance analysis is presented. The second is to put forth a theoretical reliability link between mean time to failure and WF system fitness probability (Mean Time to Failures (MTTF—Mean time between failures. MTTF = t1 + t2 + … + tn/m, where: m—the number of all failures at time T, ti—i—ty time to failure)). The third goal is to analyze the time to failure as a function of service life and to assess the dependability of the WF under consideration as a... [more]

This paper analyses innovative activities, including renewable energy sources (RES) in the housing market, the motivations for their introduction, effectiveness, benefits, limitations and management—which are open and current problems of Polish and international sustainable construction. This problem is part of a research gap concerning, among others, the role of developers and entities responsible for introducing energy innovations into housing construction. The aim of the paper is to analyse innovations, with particular emphasis on RES, introduced by residential developers in Poland in the context of global trends. The work is based on the results of surveys conducted among developers of the primary housing market. The research of 130 questionnaires received from entities such as multi-storey buildings and multi-family houses in Poland, was carried out on a nationwide sample using the CATI Computer Assisted Telephone Interview method. The results of the survey research were summarize... [more]

The drastic consequences of emergencies force us to look for ways to increase the stability of the device operation at overhead power transmission lines (OHPTL). It can be achieved by developing new algorithms for determining the protection operation setpoints and detecting the damage location. Fault detection at OHPTL of 10 kV and above is mainly carried out by the devices based on the measurement of emergency mode parameters. For fault detecting one should analyze the parameters of not only current and voltage at the accident time, but also of the overhead power line. Specific active resistance, specific reactance, specific active conductivity and specific reactive conductivity are used to characterize the overhead power transmission lines. As a rule, these parameters are normalized to the unit of length of the overhead line (OHL) and linear values are used in the calculations. When analyzing power lines, tabular approximate values of longitudinal and transversal parameters in equiva... [more]

The study of power load forecasting is gaining greater significance nowadays, particularly with the use and integration of renewable power sources and external power stations. Power forecasting is an important task in the planning, control, and operation of utility power systems. In addition, load forecasting (LF) aims to estimate the power or energy needed to meet the required power or energy to supply the specific load. In this article, we introduce, review and compare different power load forecasting techniques. Our goal is to help in the process of explaining the problem of power load forecasting via brief descriptions of the proposed methods applied in the last decade. The study reviews previous research that deals with the design of intelligent systems for power forecasting using various methods. The methods are organized into five groups—Artificial Neural Network (ANN), Support Vector Regression, Decision Tree (DT), Linear Regression (LR), and Fuzzy Sets (FS). This way, the revi... [more]

Buildings are one of the primary consumers of energy. In addition to the electricity grids, renewable energies can be used to supply the energy demand of buildings. Intelligent systems such as the Internet of Things (IoT) and wireless sensor technologies can also be applied to manage the energy consumption in buildings. Fortunately, integrating renewable energies with these intelligent systems enables creating nearly zero-energy buildings. In this paper, we present the results of our experimentation to demonstrate forming such a building and showing the benefits for building users and the society. We create a system by integrating photovoltaic (PV) technology with an IoT-based control mechanism to supply and consume energy. We further illustrate “how the integration of IoT and PV technology can bring added value to the users?”. To this end, we evaluate the performance of our system against conventional ways of energy supply and consumption for a lighting use case in a dairy store. We a... [more]

Sustainable development and the increasing demand for equitable energy use as well as the reduction of waste of energy are the author’s social and scientific motivations. This new paradigm is the selection of a pertinent methodology to evaluate the efficiency of habitat thermomodernization, which is one of the scientific tasks of the presented study. In order to meet the social and scientific requirements, 380 buildings from the end of the last century (made of large plate technology), which were thermally improved at the beginning of the XXI century, were designed for a comparative analysis of the predictive modelling of heating energy consumption. A specific set of important variables characterizing the examined buildings has been identified. Groups of variables were used to estimate the energy consumption in such a way as to achieve a compromise between the difficulty of obtaining them and the quality of forecast. To predict energy consumption, the six most appropriate neural method... [more]

In recent years, power-to-gas technologies have been gaining ground and are increasingly proving their reliability. The possibility of implementing long-term energy storage and that of being able to capture and utilize carbon dioxide are currently too important to be ignored. However, systems of this type are not yet experiencing extensive realization in practice. In this study, an overview of the experimental research projects and the research and development activities that are currently part of the power-to-gas research line is presented. By means of a bibliographical and sitographical analysis, it was possible to identify the characteristics of these projects and their distinctive points. In addition, the main research targets distinguishing these projects are presented. This provides an insight into the research direction in this regard, where a certain technological maturity has been achieved and where there is still work to be done. The projects found and analyzed amount to 87,... [more]

Corporate responsibility is an effective management strategy which, through conducting social dialogue at the local level, contributes to increasing the competitiveness of enterprises at a global level and simultaneously shaping favourable conditions for social and economic development. A review of the literature on the subject provided the theoretical motivation to undertake an emirical study of the implemented social innovations by the property manager and their reception by resource residents. The main aim of this study was to diagnose the attitudes of residents towards the implementation of social innovations by the municipal property manager. The research presented in the above article has been conducted in the first and second quarter of 2021 among residents of the Department of Housing “TBS” (ZGM TBS) in Częstochowa, Silesian voivoideship, Poland. The research was conducted using the survey method. The measurement instrument was a prepared questionnaire. The survey was completed... [more]

In industrial maintenance activity, very sophisticated technical and human factors are needed to achieve the great process or service that the company provides, with a large dose of knowledge based on the personal experience of maintenance technicians. However, the management and application of knowledge in this activity is often relegated to a third level (or simply forgotten). The aim of this study is to identify, classify and prioritize the different barriers and facilitators that can be found in maintenance organizations of the company in reference to knowledge management in strategic maintenance activities, and what competitive advantages could be used for their appropriate introduction in the company. For this, qualitative techniques have been used through a field study and observation, as well as semi-structured interviews between company directors and maintenance managers of first-level companies in various sectors (industrial or services), to draw conclusions on the applicatio... [more]

In this article, a description is presented of simulation investigations concerning the quality of regeneration effects of a technical object in an intelligent system with an artificial neural network. All repairable technical objects used are subject to a cyclic (random) process of damages and repairs in the time of their operation. A reduction of the parameters connected with the use of objects is the fundamental feature of this process. This results in the need of a regeneration (technical maintenance) of this object. Regeneration of an object in an intelligent system with an artificial neural network constitutes an effective approach to this problem. The problem of qualitative assessments of a maintenance process organized in this manner is the focus of this article. For this purpose, a program of simulation investigations is presented. The research program consists of a description of the models of the operation processes of technical objects, determination of the input data to th... [more]

Systematic failure analysis generally enhances the ability of engineering decision-makers to obtain a holistic view of the causal relationships that often exist within the systems they manage. Such analyses are made more difficult by uncertainties and organisational complexities associated with critical and inevitable industrial maintenance activities such as major overhauls, outages, shutdowns, and turnarounds (MoOSTs). This is perhaps due to the ratio of tasks-to-duration typically permitted. While core themes of MoOSTs including planning, contracts, costing, execution, etc., have been the focus of most research activities, it is worth noting that the ability to successfully transfer and retain MoOSTs knowledge is still under-investigated. Effectively implementing a case study-based approach for data collection, the current study explores the harmonisation of various risk assessments (i.e., fault tree analysis and reliability block diagrams) and multicriteria decision analysis (MCDA)... [more]