Increase Energy Efficiency Research Articles

Innovative Transitions: Exploring Demand for Smart City Development in Novi Sad as a European Capital of Culture

This study investigates the factors influencing the acceptance and implementation of smart city solutions, with a particular focus on smart mobility and digital services in Novi Sad, one of the leading urban centers in Serbia. Employing a quantitative methodology, the research encompasses citizens’ perceptions of the benefits of smart technologies, their level of awareness regarding smart solutions, the degree of engagement in using digital services, and their interest in smart mobility. The results indicate that these factors are crucial for the successful integration of smart technologies. Notably, awareness of smart city initiatives and the perceived benefits, such as improved mobility, reduced traffic congestion, increased energy efficiency, and enhanced quality of life, are highlighted as key prerequisites for the adoption of these solutions. Novi Sad, as the European Capital of Culture in 2022, presents a unique opportunity for the implementation of these technologies. Our findings point to the need for strategic campaigns aimed at educating and raising public awareness. The practical implications of this study could contribute to shaping policies that encourage the development of smart cities, not only in Novi Sad but also in other urban areas across Serbia and the region. This study confirms the importance of citizen engagement and technological literacy in the transformation of urban environments through smart solutions, underscoring the potential of these technologies to improve everyday life and achieve sustainable urban development.

The nexus of industrial employment, financial development, urbanization, and human capital in promoting environmental sustainability in E7 economies

ABSTRACT Financial development supports economic growth, reduces unemployment, ensures justice, and has an impact on the environment. Human development significantly supports E-7 countries in achieving the goal of stable and qualified economic development in the next decade. This factor affects people’s ability to manage environmental problems and increases their productivity by contributing to people’s industrial and production processes. It can be a guide for states to choose technologies that take into account the clean environment and increase energy efficiency in areas where energy is constantly used. Increasing urbanization encourages various development activities. This study aims to investigate the impact of financial development, human development, urbanization, and industrial employment on environmental quality for E-7 countries with regularized common correlated effects and the Augmented Mean Group long-run estimators. Another important aim of the study is to achieve Sustainable Development Goals 4, 8, 9, 11 and 13. Increasing financial development improves environmental quality in Russia and India, according to robust results from long-run estimators. Increasing human development in China increases environmental pollution. While the expansion of urbanization increases environmental quality in Brazil, it decreases it in China. The increase in employment in the industry increases the load capacity factor in the panel group, Brazil, China, Indonesia, and India. In addition to these results, the current article presents policy recommendations for governments to increase environmental quality on a country basis and provides feasible solutions on how to use the independent variables in the study as environmental tools.

THIN FILM METHANE SENSOR BASED ON CARBON COMPOSITE

Today, with the oil and gas industry playing a key role in the global energy sector, issues related to the effective control and detection of methane leaks are becoming an integral part of the strategic tasks of the industry. The article is devoted to the research and development of a thin-film sensor for detecting methane in the air using a carbon composite. The technical result of this study is the creation of a highly sensitive and energy efficient sensor for measuring methane concentration. The basis for the sensitive element is a thin film of a carbon composite, consisting of a polymer, single-wall carbon nanotubes and graphene oxide, with aluminum electrodes. The sensor has a number of advantages, including responding to the presence of methane without the need for heating, the simplicity of the sensitive material preparation process, and low cost. The ability to quickly start small-scale production, simplified manufacturing due to the use of only one pair of electrodes, as well as increased energy efficiency due to the absence of the need for heating are also positive characteristics of this device. The study presents the results of manufacturing the sensor, including the steps of cleaning the surface of the substrate, creating a shadow mask, spraying electrodes, forming a thin film of the composite by centrifugation, as well as analyzing the microstructure of the sensor using an atomic force microscope. Also presented are data on obtaining multilayer structures of thin-film resistive sensors based on a polymer matrix nanocomposite, single-wall carbon nanotubes and graphene oxide, including the process of creating electrodes. This study is important for the development of methane monitoring methods in the oil and gas industry and other industrial areas, offering promising technical solutions to ensure environmental and economic sustainability of production.

Corporate social responsibility and energy efficiency: Empirical evidence from the manufacturing sector of India

AbstractThe strategic business firm manages today's profitability and tomorrow's sustainability to achieve a comparative advantage in the emerging market economy. Considering India's ambitious emission reduction target and rapid economic development, this study explores the potential relationship between corporate social responsibility (CSR) and the energy efficiency of manufacturing firms in India. Using firm‐level data, the panel fixed effects model shows that CSR negatively explains energy intensity (EI). We observed a consistent negative relationship between CSR and EI for all models, with and without controlled firm‐specific variables. Firms that manufacture chemical and chemical products, pharmaceuticals, medical chemicals and botanical products are energy intensive without CSR; however, CSR activities helped these firms become energy efficient. Our result confirms that voluntary CSR is less efficient than mandatory CSR in contributing to environmental and energy‐related indicators at the firm level. Our empirical results indicate several policy implications: (1) CSR should also focus on sustainable business models related to energy efficiency and reduction in carbon emissions; (2) firms should be encouraged to use CSR related to environmentally friendly innovations. We conclude that CSR spending and environmental expenses will increase energy efficiency at the firm level, which will help achieve net‐zero targets and sustainable industrial development.

Social factors influence on energy efficiency management and development of renewable energy sources

Current issues of increasing energy efficiency in the conditions of new industrialization are considered. The article analyzes social factors that affect the effectiveness of energy efficiency management and the development of renewable energy sources, including social awareness of the population, state support, the role of business and social responsibility of enterprises. The study shows that social aspects play a critical role in the implementation of energy-saving technologies and the achievement of sustainable development goals. A comprehensive approach was used, which includes theoretical analysis, questionnaires, expert interviews and statistical analysis to identify key social factors and their impact on energy efficiency management. The results of the study can be useful for developing recommendations for improving energy efficiency management systems taking into account social aspects, as well as for forming a strategy for the development of renewable energy sources in Ukraine and a hydrogen strategy.In the process of researching the impact of social factors on energy efficiency management and the development of renewable energy sources, several unresolved aspects were identified that require additional analysis. Firstly, the insufficiency of research that would reveal the relationship between the social awareness of the population regarding energy efficiency and the level of implementation of energysaving technologies and energy storage technologies using hydrogen was revealed.Sociocultural factors such as educational attainment, cultural stereotypes and values remain understudied. Secondly, the role of social responsibility of business in the implementation of energy-efficient solutions needs a deeper study, since questions about the impact of social initiatives on these processes still remain open. Thirdly, the study of the impact of public policy on the social aspects of energy efficiency is also an underdeveloped direction, particularly in the context of how public programs take into account social factors, such as the adoption of new technologies by the population and the impact on social groups with different income levels.And fourthly, how does Ukraine maintain the level of awareness and understanding of hydrogen technologies. These aspects require further scientific analysis to improve the efficiency of energy efficiency management and the development of renewable energy sources.

Nordic environmental resilience: balancing air quality and energy efficiency by applying artificial neural network

Maintaining public health and environmental safety in the Nordic nations calls for a strict plan to define exact benchmarks on air quality and energy efficiency. This study investigates the complicated interaction of decentralized energy production (DEP) with energy efficiency, and air quality index in the Nordic nations from 1990 to 2022 using System GMM and Artificial Neural Network (ANN) approach. Our research explored positive role of decentralized energy production and technological advancement to propel notable increases in energy efficiency, hence lowering pollution expressed as PM2.5 level. Our research indicates, however, that although international trade, GDP and urbanization assist to enhance energy efficiency, they also contribute to pollution by raising PM2.5 Level by higher energy usage. Furthermore damaging to environmental quality is the persistent link shown by economic disparity and the energy price index with increased degrees of pollution and less energy efficiency. Policy frameworks must devised sustainable development policy (decentralized energy production) to significantly improve energy efficiency and lower the amount of pollution. This calls for proper urban planning and a close observation of the possible drawbacks of growing GDP, trade, economic disparity, and energy expenses.

Smart Grids: Integrating AI for Efficient Renewable Energy Utilization

The urgent global shift from fossil fuels to renewable energy sources necessitates innovative solutions to address energy system management challenges. Smart grids, equipped with sophisticated infrastructures, play a crucial role in this transition. This study integrates Artificial Intelligence (AI) into smart grids to enhance their efficiency and reliability, directly supporting the United Nations Sustainable Development Goals (SDGs), particularly SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 11 (Sustainable Cities and Communities). Employing a mixed-methods approach, the research utilizes historical and real-time data, applying machine learning algorithms such as Linear Regression, Support Vector Regression (SVR), Recurrent Neural Networks (RNN), and Long ShortxTerm Memory (LSTM) for predictive accuracy in energy management. Optimization techniques like Genetic Algorithms and Particle Swarm Optimization (PSO) are also implemented for resource scheduling and grid balancing. The results demonstrate significant improvements, with an 11.76% increase in energy efficiency and grid stability, a 66.67% reduction in prediction errors, and a 20% decrease in operational costs compared to conventional systems. These enhancements highlight the transformative potential of AI in smart grids, promoting more efficient and sustainable energy utilization. The study concludes that AI-driven smart grids are pivotal in achieving the SDGs by providing scalable and efficient solutions for renewable energy integration, thereby fostering sustainable development and reducing environmental impacts.

Path tracking and energy efficiency coordination control strategy for skid-steering unmanned ground vehicle

The skid steering unmanned ground vehicle (SUGV) plays an important role in extremely harsh environments. Improving the autonomous control capability and energy efficiency of SUGV is urgently needed. This article presents a skid steering-based path tracking control strategy. In the upper controller, an improved model-free sliding mode controller (APMS) is used to calculate the yaw moment for tracking control. On the lower controller, the Snow Ablation Optimizer (SAO) is used to distribute the output torque of the drive motors, taking longitudinal force, yaw moment and energy consumption into account. Finally, the designed controller is validated through simulation under different operating conditions. The results show that the proposed coordination controller achieves good control performance, increases energy efficiency and at the same time ensures tracking accuracy.

Technical evaluation and life-cycle assessment of solid oxide co-electrolysis integration in biomass-to-liquid processes for sustainable aviation fuel production

Building upon prior research, this paper integrates solid oxide electrolysis (SOEL) into a Biomass-to-Liquid (BtL) process, facilitating the production of sustainable aviation fuel (SAF) through gasification, co-electrolysis, and Fischer-Tropsch synthesis. Two different integration concepts are developed: An inline integration resulting in a directly electrified-Biomass-to-Liquid (eBtL) process and a parallel integration for a Power-and-Biomass-to-Liquid (PBtL) process. To maximize process efficiency, the SOEL is operated under endothermic conditions with heat supply from syngas cooling after gasification. The developed processes allow for an increase in carbon efficiency up to about 61% to 94%. The electrolysis power required corresponds to electrification ratios of 0.32 to 0.83MWel/MWth. Compared to the conventional H2 addition in PBtL processes, electricity demand can be reduced by 13% to 29% when using co-electrolysis instead of water electrolysis. The resulting increase in energy yield and energy efficiency is because up to 17% of the SOEL’s energy demand can be substituted with heat in the electrified BtL processes. A life cycle analysis shows the absolute requirement to operate the process with renewable electricity to reduce indirect greenhouse gas emissions. A critical evaluation of the technological feasibility indicates further development requirements for the SOEL and the gasification heat recovery technology to enable the integration approach.

Comprehensive analysis of a novel sustainable photovoltaic/thermal assisted ground source heat pump system with energy storage

The imbalance of soil heat is a significant issue hindering the sustainable operation of ground source heat pump (GSHP) systems, especially under single-mode heating conditions. To address this challenge and develop a more energy-efficient, economical, and sustainable heating system, this paper proposes a novel PV/T-GSHP-PCM (photovoltaic/thermal-ground source heat pump-phase change material) system. A simulation model of the system was developed, and its performance was thoroughly analyzed. Furthermore, the comprehensive performance of four different system coupling configurations was compared. The study concluded that the PV/T-GSHP-PCM system increases energy efficiency by 13 % and reduces operating costs by 32 % compared to conventional GSHP systems. Furthermore, the PV/T-GSHP-PCM system achieves zero energy consumption, zero operational cost, and zero carbon dioxide emissions. After 10 years of continuous operation under single-mode heating, the soil heat imbalance rate stabilized at around 7 %, the heating coefficient of performance of the system decreased by only 0.04. This system demonstrates sustainable and efficient green heating. This study provides valuable insights for advancing research on sustainable and renewable energy-based heating systems.

Analysis of methods for reducing the signal PAPR under the influence of the Doppler effect in hybrid communication networks

Background. For further development of communication networks, it is planned to use hybrid satellite networks for traffic transmission. However, satellite communication channels have features such as distortion caused by the Doppler effect and increased energy efficiency requirements. Aim of this study is to analyze variants of orthogonal frequency multiplexing methods and modulation methods in order to choose the most stable technology, taking into account destabilizing factors. Method. Comparing different signal processing technologies and studying their resistance to bit errors is the imitation modeling of the communication channel in the Matlab environment. This approach allows creating a model of the communication network, taking into account the main parameters of communication channels, such as the Doppler effect, energy deficiency and destabilizing factors. Results. The distribution of the bit error coefficient for various signal processing technologies, depending on the signal-to-noise ratio, is compared. The method of frequency multiplexing is defined, providing the minimum peak factor and the most resistant to bit error. It is also noted that the effectiveness of all the studied technologies depends on the spacing and modulation constellations, and that it is necessary to adjust the characteristics of the system for each case. Conclusion. The results of this study can be used to improve the quality of communication in difficult interference conditions of hybrid mobile networks of 5 and 6 generations using the satellite segment.

Human short-latency reflexes show precise short-term gain adaptation after prior motion.

The central nervous system adapts the gain of short-latency reflex loops to changing conditions. Experiments on biomimetic robots showed that reflex modulation could substantially increase energy efficiency and stability of periodic motions if, unlike known mechanisms, the reflex modulation both acted precisely on the muscles involved and lasted after the motion. This study tests the presence of such a mechanism by having participants repeatedly rotate either their right elbow or shoulder joint, before perturbing either joint. The results demonstrate a mechanism that modulates short-latency reflex gains after prior motion with joint-specific precision. Enhanced gains were observed hundreds of milliseconds after movement cessation, a time scale well-suited to quickly adapt overall periodic motion cycles. A serotonin antagonist significantly decreased these post-movement gains diffusely across joints. But blocking serotonin did not affect the joint-specificity of the gain scaling more than a placebo, suggesting that serotonin sets the overall reflex gain across joints after movement by an effect that is modulated in a joint-specific manner by an unidentified neural circuit. These results confirm the existence of a new, joint-specific, fast, persistent adaptation of short-latency reflex loops induced by motion in human arms.

Control Structures for Combined H2/Electricity from Offshore Wind Turbines

Wind energy proves to be a highly favourable choice for electricity generation due to its clean and renewable nature, and is playing a significant role in reducing global greenhouse gas emissions. Offshore wind turbine systems have gained widespread popularity as they can capitalise on elevated and consistent wind speeds surpassing those found in onshore locations, resulting in increased energy efficiency. Furthermore, offshore wind power possesses the potential to emerge as a significant electricity source for the production of green hydrogen. As water electrolysis technology for hydrogen production continues to advance, utilizing offshore wind power for hydrogen generation is becoming more economically viable and practical. Offshore wind power with higher wind speeds in combination with efficient control structures presents an attractive option for electricity generation and hydrogen co-production. This paper aims to present and evaluate four different production structures for combined H2/energy generation from offshore wind turbines. Previous research studies in this area often overlook control structures and lack information on power converter operations. In contrast, this article studies control structures that enable proper functionality and ensure adequate interoperability, enhancing the reliability of renewable energy integration. Each structure, including both wind turbines and electrolyser, is described in detail, along with the corresponding controllers. Simulation results are presented for each structure and controller to demonstrate their effective operation.

Energy efficiency in middle-income countries with DEA: An approach for Latin America

Latin America and Caribbean countries are focused on meeting their 2030 sustainable development goals, with the promotion of actions that increase energy efficiency being a key pillar. Recent studies have applied various data envelopment analysis (DEA) models to this end, but few include Latin American countries. This study assesses energy efficiency in 18 middle-income Latin American countries from 2008 to 2019 using two super-efficient DEA radial models that are particularly adept at distinguishing between highly efficient units. The analysis incorporates a broader set of countries through clustering techniques to ensure homogeneity. From this analysis, the production function, the technical efficiency, the total energy efficiency factor and their respective correlation coefficients versus the per capita income variable are obtained for each country. Costa Rica and Argentina stand out among the Latin American middle-income countries with the highest energy efficiency within quintile Q1 and Q2, whereas Paraguay and Chile obtain the lowest efficiency within quintile Q5 and Q3. For the 18 countries studied, a higher level of income is not significantly related to a higher level of energy efficiency. This study provides policymakers an alternative indicator for effective monitoring of energy efficiency.

Retrofit of green architecture through adaptive reuse of heritage buildings in sustainable tourism management

ABSTRACT The adaptive reuse of cultural heritage buildings as tourist attractions is a growing trend. From an architectural point of view, this concept can be optimized with green architectural retrofit strategies, which help minimize construction waste and encourage environmental conservation. The challenge lies in technically implementing green architectural strategies to transform cultural heritage buildings to ensure safe and comfortable use as tourist destinations. This research uses method in-depth observations of several case studies to identify the subject’s strengths and weaknesses through SWOT analysis. The findings from this analysis are used to develop strategies for managing cultural heritage buildings through green retrofit architecture. The research results provide detailed insights into the effectiveness of management practices based on previous research, addressing issues such as limited awareness and capacity, challenges in interpreting and managing cultural heritage, data management, costs, and inadequate knowledge. Research recommends applying green retrofit techniques such as energy efficiency, water and waste management, landscaping, building material, and indoor air quality to cultural heritage buildings. This approach aims to optimize and increase energy efficiency by revitalizing buildings through landscape designs that consider environmental conservation and climate change.

Contributing to healthier populations by reducing energy poverty via innovative financial models

Abstract Issue/problem Energy poverty is a major challenge affecting 9.3% of the EU population (EUROSTAT 2022). Health problems attributable to energy poverty include respiratory diseases, heart attacks, stroke, and mental disorders. Governments must act quickly and intervene with policies and programmes that reduce energy poverty and promote citizens' health and well-being. Description of the problem We propose Social Impact Bonds (SIBs), a new family of instruments that address serious social challenges, to finance interventions targeting energy poverty,improving the health and well-being of households in a context of limited public resources. For this purpose, data from interventions to increase energy efficiency and combat energy poverty implemented during one year in 6 pilot sites in the framework of the EU project WELLBASED are used. First, a compliance check will be carried out, followed by an estimation of the costs, savings, and benefits of the application of SIBs to finance energy poverty reduction interventions with an impact on health. Results The results of the analysis will show whether the intervention to reduce energy poverty meets the necessary characteristics for a SIB to be implemented. In addition, the possible key actors that could lead its implementation are identified. Lessons If the interventions for the reduction of energy poverty carried out under the WELLBASED project are successful, SIBs could be considered as a valuable alternative to finance interventions that combat energy poverty and increase the well-being of citizens. Key knowledge on how to apply SIBs makers to tackle a serious social issue with important consequences on health will be at disposal of (EU and worldwide) local authorities and policy. Key messages • Energy poverty is a public health issue, requiring urgent support measures. • SIBs fund interventions via public-private collaboration to fight energy poverty and boost citizen wellbeing.

Method for Increasing the Energy Efficiency of the Gear Teeth Cutting Process by Smoothing the Cutting Force Variation

The energy efficiency in metal cutting is, sometimes, very low. Recent studies show that the energy consumed for detaching chips represents only about 15% of the total energy involved in material machining. The available solutions for energy optimization in cutting processes mentioned are the improvement of manufacturing equipment, the optimization of processes, and appropriate production scheduling. Already-performed research shows that to increase energy efficiency, the cutting force must be reduced, for example, by reducing the depth of the cut and by increasing the feed rate. However, this is applicable when the cutting force is quasi-constant during the process, which is not the case for gear teeth cutting when the cutting force significantly varies. The present paper proposes a new solution for energy efficiency increase in gear teeth cutting, namely, the smoothing of the cutting force variation during the machining process, by keeping the area of the detached chip section quasi-constant during the cutting process. This can be reached by replacing the constant rolling feed, currently used in gear teeth cutting, with a rolling feed that varies after an appropriate law. An algorithm dedicated to implementing this solution has been developed. It uses graphical modeling in CATIA to find the variation in the detached chip area. Original MatLab R2018a applications were developed (i) to identify the analytical form of the law that approximates this variation and (ii) to find the variation law of the feed during the rolling motion, if imposing a constant area of the detached chip. The algorithm was successfully applied in the cases of toothing with a rack tool (by slotting) and with a pinion cutter (by slotting and turning). A technical solution for method implementation in practice is also presented.

Digital Twins for Reducing Energy Consumption in Buildings: A Review

This research investigates the use of digital twin (DT) technology to improve building energy management and analyse occupant behaviour. DTs perform the function of acting as virtual replicas of physical assets, which facilitates real-time monitoring, predictive maintenance, and data-driven decision-making. Consequently, energy performance and occupant comfort can be enhanced. This study evaluates the efficiency of DTs in optimising energy usage by a mix of a systematic literature review and scientometric analysis of 466 articles from the Scopus database. Among the main obstacles noted are interoperability issues, privacy and data quality difficulties, and the requirement for a more thorough integration of digital and physical interactions. The results highlight the necessity of standardised frameworks to direct DT implementations and suggest areas for further study, especially in the areas of improving cybersecurity and incorporating occupant behaviour into DT models. This research makes practical recommendations for using DT technology to increase energy efficiency and sustainability in the built environment.

The effect of failure on energy efficiency in maritime vessels autopilot systems

The increasing demands for energy efficiency and environmental sustainability in the maritime industry have underscored the critical importance of optimizing autopilot systems, which, despite their significance, are often overlooked in ship energy efficiency management. The objective of this study is to enhance the energy efficiency of ships by focusing on the efficiency of autopilot systems, which play a significant role in the management of energy efficiency. The research emphasizes the need for effective decision support systems for ship operators, not only for optimizing ship speeds but also for making informed operational decisions. By utilizing Fuzzy Fault Tree Analysis (FFTA), the study identifies and prioritizes the causes of efficiency losses in autopilot systems and examines their frequency. Based on expert opinions, the research delves into the complexity of autopilot systems and the interactions among various components. Notably, the study highlights the impact of multiple factors on the efficiency of complex autopilot systems, elucidating their relationships through Minimum Cut Sets (MCS) analysis. Furthermore, attention was drawn to the “Improper Alarm Input” event caused by insufficient knowledge and awareness among ship operators, which hinders the effective use of autopilot systems. The findings demonstrate that decision support systems can increase energy efficiency and contribute to the reduction of operational errors by reducing the human factor, which is 99% effective on the “Inefficient Heading Control System”. Additionally, proper utilization of autopilot systems can lead to a decrease in a ship's carbon footprint and operating costs. Overall, the results can affect strategic decisions in ship energy efficiency management and encourage significant steps toward achieving International Maritime Organization's (IMO) sustainability objectives.

FMORT: The Meta-Heuristic routing method by integrating index parameters to optimize energy consumption and real execution time using FANET

Decreasing energy consumption in Unmanned Aerial Vehicles (UAVs) while simultaneously enhancing their reliability and processing capabilities is considered a fundamental challenge. The routing mechanisms employed in Flying Ad Hoc Networks (FANETs) are more complex compared to those in Mobile Ad Hoc Networks (MANETs) and Vehicular Ad Hoc Networks (VANETs), a challenge addressed by the FMORT method. To tackle these complex routing challenges, clustering techniques that utilize hybrid Meta-heuristic algorithms can be applied. Data analysis within the FMORT framework identified factors influencing service integration, leading to a reduction in redundant request transmissions and overall redundancy in the proposed method. The identification of food sources in the hybrid Meta-heuristic algorithm of the FMORT method is achieved through the integration of the Sparrow and Dragonfly algorithms. These algorithms work simultaneously to increase energy efficiency and increase network lifetime. This strategy optimizes information exchange by selecting an intelligent threshold detector and categorizing inputs, thereby minimizing node mobility. As a result, it improves performance metrics and decreases delivery costs, energy consumption, and delays. In the proposed method, a balanced performance is achieved by comparing existing methods in terms of transmission delay, Packet Delivery Ratio( PDR), throughput, and energy consumption. Simulation results show that the FMORT approach provides effective and stable outcomes in terms of reliability, decreased delays, and improved packet delivery rates. The FMORT framework includes principles for neighbor selection, determining suitable cluster heads, and scoring based on the average Euclidean distance. Additionally, it manages topology access, ensures proper distribution, guarantees data connectivity, and accurately categorizes inputs. By optimizing the sensitivity rate, this method minimizes the average delays and meekly values input data through effective load balancing. Key parameters considered for real time optimization of overall performance include the number of cluster heads during re-clustering, the ratio of request-to-acknowledgment packet transmission, node, and network lifetime, end-to-end delay, and energy consumption. Ultimately, the simulation results show that compared to the MWCRSF algorithm, the average optimization of index parameters,% 0.73 decrease in energy consumption,% 2.23 network lifetime, 1.35 re-cluster construction time and also% 0.11 re-cluster lifetime has increased.