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The tremendous development in the field of communications is derived from the increasing demand for fast transmission and processing of huge amounts of data. The non-orthogonal multiple access (NOMA) system was proposed to increase spectral efficiency (SE) and improve energy efficiency (EE) as well as contribute to preserving the environment and reducing pollution. In the NOMA system, a user may be considered as a relay to the others that support the coverage area based on adopting the reuse of the frequency technique. This cooperation enhances the spectral efficiency, however, in the cell, there are other users that may affect the spectral allocation that should be taken into consideration. Therefore, this paper is conducted to analyze the case when three users are available to play as relies upon. The analyses are performed in terms of the transmitted power allocation in a fair manner, and the system's performance is analyzed using the achievable data rates and the probability of an outage. The results showed an improvement in throughputs for the second and third users, as its value ranged from 7.57 bps/Hz to 12.55 bps/Hz for the second user and a quasi-fixed value of 1,292 bps/Hz for the third user at the transmitted power ranging from zero to 30 dBm. [ABSTRACT FROM AUTHOR]

Network virtualization is a technology proven to be a key enabling a family of strategies in different targets, such as energy efficiency, economic revenue, network usage, adaptability or failure protection. Network virtualization allows us to adapt the needs of a network to new circumstances, resulting in greater flexibility. The allocation decisions of the demands onto the physical network resources impact the costs and the benefits. Therefore it is one of the major current problems, called virtual network embedding (VNE). Many algorithms have been proposed recently in the literature to solve the VNE problem for different targets. Due to the current successful rise of artificial intelligence, it has been widely used recently to solve technological problems. In this context, this paper investigates the requirements and analyses the use of the Q-learning algorithm for energy-efficient VNE. The results achieved validate the strategy and show clear improvements in terms of cost/revenue and energy savings, compared to traditional algorithms. [ABSTRACT FROM AUTHOR]

Sustainability and resilience are major challenges for the building sector in order to meet energy efficiency and low carbon emissions goals. Based on the defined and quantified targets of the EU climate change policy, Renewable Energy Systems (RESs) are among the top-priority measures for accomplishing the target of decarbonization in buildings. Nevertheless, the choice of the type of RES is not a one-dimensional problem, and the optimal combination may not be unique. The aim of this paper is the energy and environmental evaluation of renewable energy technologies with emphasis on biomass and solar thermal systems for heating applications in residential buildings. More specifically, and aiming at the maximum possible contribution of renewable energy sources in the total final energy consumption for the needs of zero energy buildings, different scenarios are presented based on a Life Cycle Energy Analysis (LCEA) approach. The methodology is based on quantifying the environmental impacts (midpoint analysis), as well as endpoint analysis, in order to define the impact on human health, ecosystem damage, and resource depletion. The LCEA has been conducted, supported by the SimaPro tool, ensuring the environmental impact assessment result. A combination of RES technologies based on solar and biomass are examined and compared to conventional fossil fuel heating systems according to technical, energy, and environmental criteria. Finally, the energy system technologies were compared in correlation to a building's thermal insulation level. The first set of simulations fulfilled the minimum thermal insulation requirements, according to the national energy performance regulation, whilst the second set of simulations was based on increased levels of insulation. The point of this analysis was to correlate the impact of thermal insulation to RES technologies' contribution. The results determined that the best available energy solution, focusing on technical and environmental criteria, is the combination of biomass and solar thermal systems for covering the heating processes in residential buildings. More specifically, the combined biomass–solar system has a lower overall environmental impact, due to the reduction in gaseous pollutant emissions, as well as the reduction in the amount of used fuel. The reduction in the total environmental impact amounts to a percentage of approximately 43%. [ABSTRACT FROM AUTHOR]

LoRaWAN has imposed itself as a promising and suitable technology for massive machine-type communications. With the acceleration of deployment, improving the energy efficiency of LoRaWAN networks has become paramount, especially with the limitations of throughput and battery resources. However, LoRaWAN suffers from the Aloha access scheme, which leads to a high probability of collision at large scales, especially in dense environments such as cities. In this paper, we propose EE-LoRa, an algorithm to improve the energy efficiency of LoRaWAN networks with multiple gateways via spreading factor selection and power control. We proceed in two steps, where we first optimize the energy efficiency of the network, defined as the ratio between the throughput and consumed energy. Solving this problem involves determining the optimal node distribution among different spreading factors. Then, in the second step, power control is applied to minimize the transmission power at nodes without jeopardizing the reliability of communications. The simulation results show that our proposed algorithm greatly improves the energy efficiency of LoRaWAN networks compared to legacy LoRaWAN and relevant state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

Security is one of the major concerns while designing robust protocols for underwater sensor networks (UWSNs). The underwater sensor node (USN) is an example of medium access control (MAC) that should control underwater UWSN, and underwater vehicles (UV) combined. Therefore, our proposed method, in this research, investigates UWSN combined with UV optimized as an underwater vehicular wireless network (UVWSN) that can completely detect malicious node attacks (MNA) from the network. Thus, MNA that engages the USN channel and launches MNA is resolved by our proposed protocol through SDAA (secure data aggregation and authentication) protocol deployed in UVWSN. SDAA protocol plays a significant role in secure data communication, as the cluster-based network design (CBND) network organization creates a concise, stable, and energy-efficient network. This paper introduces SDAA optimized network known as UVWSN. In this proposed SDAA protocol, the cluster head (CH) is authenticated through the gateway (GW) and the base station (BS) to guarantee that a legitimate USN oversees all clusters deployed in the UVWSN are securely established for providing trustworthiness/privacy. Furthermore, the communicated data in the UVWSN network guarantee that data transmission is secure due to the optimized SDAA models in the network. Thus, the USNs deployed in the UVWSN are securely confirmed to maintain secure data communication in CBND for energy efficiency. The proposed method is implemented and validated on the UVWSN for measuring reliability, delay, and energy efficiency in the network. The proposed method is utilized for monitoring scenarios for inspecting vehicles or ship structures in the ocean. Based on the testing results, the proposed SDAA protocol methods improve energy efficiency and reduce network delay compared to other standard secure MAC methods. [ABSTRACT FROM AUTHOR]

With the emergence of various Internet of Things (IoT) technologies, energy-saving schemes for IoT devices have been rapidly developed. To enhance the energy efficiency of IoT devices in crowded environments with multiple overlapping cells, the selection of access points (APs) for IoT devices should consider energy conservation by reducing unnecessary packet transmission activities caused by collisions. Therefore, in this paper, we present a novel energy-efficient AP selection scheme using reinforcement learning to address the problem of unbalanced load that arises from biased AP connections. Our proposed method utilizes the Energy and Latency Reinforcement Learning (EL-RL) model for energy-efficient AP selection that takes into account the average energy consumption and the average latency of IoT devices. In the EL-RL model, we analyze the collision probability in Wi-Fi networks to reduce the number of retransmissions that induces more energy consumption and higher latency. According to the simulation, the proposed method achieves a maximum improvement of 53 % in energy efficiency, 50 % in uplink latency, and a 2.1 -times longer expected lifespan of IoT devices compared to the conventional AP selection scheme. [ABSTRACT FROM AUTHOR]

This paper presents a systematic approach for solving complex prediction problems with a focus on energy efficiency. The approach involves using neural networks, specifically recurrent and sequential networks, as the main tool for prediction. In order to test the methodology, a case study was conducted in the telecommunications industry to address the problem of energy efficiency in data centers. The case study involved comparing four recurrent and sequential neural networks, including recurrent neural networks (RNNs), long short-term memory (LSTM), gated recurrent units (GRUs), and online sequential extreme learning machine (OS-ELM), to determine the best network in terms of prediction accuracy and computational time. The results show that OS-ELM outperformed the other networks in both accuracy and computational efficiency. The simulation was applied to real traffic data and showed potential energy savings of up to 12.2% in a single day. This highlights the importance of energy efficiency and the potential for the methodology to be applied to other industries. The methodology can be further developed as technology and data continue to advance, making it a promising solution for a wide range of prediction problems. [ABSTRACT FROM AUTHOR]

Internet of Things technologies open up new applications for remote monitoring of forests, fields, etc. These networks require autonomous operation: combining ultra-long-range connectivity with low energy consumption. While typical low-power wide-area networks offer long-range characteristics, they fall short in providing coverage for environmental tracking in ultra-remote areas spanning hundreds of square kilometers. This paper presents a multi-hop protocol to extend the sensor's range, whilst still enabling low-power operation: maximizing sleep time by employing prolonged preamble sampling, and minimizing the transmit energy per actual payload bit through forwarded data aggregation. Real-life experiments, as well as large-scale simulations, prove the capabilities of the proposed multi-hop network protocol. By employing prolonged preamble sampling a node's lifespan can be increased to up to 4 years when transmitting packages every 6 h, a significant improvement compared to only 2 days when continuously listening for incoming packages. By aggregating forwarded data, a node is able to further reduce its energy consumption by up to 61%. The reliability of the network is proven: 90% of nodes achieve a packet delivery ratio of at least 70%. The employed hardware platform, network protocol stack and simulation framework for optimization are released in open access. [ABSTRACT FROM AUTHOR]

The present paper proposes a steel industry case study focused on a reheating furnace and a rolling mill. Hardware and software innovations were successfully combined in order to obtain process control and energy efficiency improvement. The reheating furnace at study is pusher type and processes billets. The hardware innovation is related to the installation of an insulated tunnel at the end of the reheating furnace, in order to guarantee a higher heat retention of the billets before their path along the rolling mill stands. The software innovation refers to the design and the installation of an Advanced Process Control system which manipulates the gas flow rate and the stoichiometric ratio of the furnace zones in order to satisfy the control specifications on billets and furnace variables. The control system is based on Model Predictive Control strategy and on a virtual sensor which tracks and estimates the billet features inside/outside the furnace. The designed controller was commissioned on the real plant, providing significant performances in terms of service factor, process control, and energy efficiency. [ABSTRACT FROM AUTHOR]

The problem of energy optimization for Internet of Things (IoT) devices is crucial for two reasons. Firstly, IoT devices powered by renewable energy sources have limited energy resources. Secondly, the aggregate energy requirement for these small and low-powered devices is translated into significant energy consumption. Existing works show that a significant portion of an IoT device's energy is consumed by the radio sub-system. With the emerging sixth generation (6G), energy efficiency is a major design criterion for significantly increasing the IoT network's performance. To solve this issue, this paper focuses on maximizing the energy efficiency of the radio sub-system. In wireless communications, the channel plays a major role in determining energy requirements. Therefore, a mixed-integer nonlinear programming problem is formulated to jointly optimize power allocation, sub-channel allocation, user selection, and the activated remote radio units (RRUs) in a combinatorial approach according to the channel conditions. Although it is an NP-hard problem, the optimization problem is solved through fractional programming properties, converting it into an equivalent tractable and parametric form. The resulting problem is then solved optimally by using the Lagrangian decomposition method and an improved Kuhn–Munkres algorithm. The results show that the proposed technique significantly improves the energy efficiency of IoT systems as compared to the state-of-the-art work. [ABSTRACT FROM AUTHOR]

Public buildings are energy-intensive users, especially when energy management is lacking. More than ever, the use of energy efficiency strategies and renewable energy sources (RES) in buildings are a national priority for Morocco in order to improve energy self-sufficiency, replace fossil fuel use and lower energy bills and greenhouse gas emissions. Relating to the exemplarity of the Moroccan government in terms of energy efficiency and sustainable development, the study support that aim and presents results of a deep energy performance analysis of more than 20 university campuses across Morocco, which has concluded that around 80% of the energy consumed in the university campuses is designated for lightning and hot water for sanitary use. Later, this study examined the potential for energy saving and the environmental benefits of implementing actions to reduce energy demand from the grid, considering the use of on-site solar energy. Thereafter, the study aimed to analyze the impact of RES integration in public university campuses, namely the photovoltaic (ESM1) for electricity output and solar thermal system for hot water use (ESM2), to assess the techno-economic-environmental performance on building energy consumption reduction. Hence, the paper reported a detailed energetic-economic and environmental (3E) analysis simulation for campuses by integration of the two Energy Saving Measurements (ESM). The results showed that the integration of ESM1 system can reduce the annual energy demand by 22% and the energy bill by 34%, whereas the integration of ESM2 achieved 67% in energy saving. According to the analysis of the results, the integration of ESM1 is expected to save 6044 MWh of electrical energy annually on the 30222 MWh for all campuses and 2559 MWh for ESM2 which is equivalent to 284 m3/yr of diesel. With the reduced energy consumption, it is possible to cut down fossil fuels for electricity production and offset greenhouse gas emissions by 672 tons of carbon dioxide annually. Besides, the evaluation of results showed that the energy performance indicator was reduced from 530 kWh/bed/yr to 248 kWh/bed/yr, which represents 56% of energy saving. [ABSTRACT FROM AUTHOR]

Thermal insulation blocks have recently been highly considered in hot weather countries - where temperature can reach high levels - according to their low thermal conductivity that can result in a considerable reduction in the demand for building HVAC systems energy and its related negative impacts to the surrounding environments. The paper concerns recognizing the capabilities of applying thermal insulation blocks in building envelopes in Cairo, Egypt to enhance whole-building performance and conserve environments. The study opted for making a comparative performance analysis on six types of building envelopes of a prototype residential building located in Cairo, Egypt by simulating the building model using building performance simulation software (Design Builder Software Ltd – V. 7.0.0.116 – Educational Version). Four use conventional bricks and blocks; the fifth type uses advanced light sand blocks. The sixth type uses thermal insulation blocks to detect the effects of using thermal insulation blocks on a building’s thermal performance and energy consumption. The performance comparative analysis results referred to a huge amount of heat transfer from and to building interior spaces caused by building external walls in the conventional building envelopes that should be treated to improve building thermal performance; by using thermal insulation blocks study observes a reduction of heat transfer from 41.61% to 65.08% that results in a reduction of energy consumption from 4.27% to 13.32%. Because of the study approach, the study proves that using thermal insulation blocks in a building’s envelope can enhance the building’s thermal performance and thus reduce the building’s energy consumption and related CO2 emissions, operating costs, environmental pollution, and other negative impacts on the surrounding environments. Therefore, researchers are encouraged to evaluate the proposed propositions further. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate bi-directional spillovers into residential and industrial sectors induced by energy efficiency improvement (EEI) in both the short- and long-term, and the impact of nesting structure as well as the size of elasticities of substitution of production and utility functions on the magnitude and the transitional dynamic of rebound effect. Developing a dynamic general equilibrium model, we demonstrate that residential EEIs spillover into the industrial sector through the labor supply channel and industrial EEIs spillover into the residential sector through the conventional income channel. Numerical simulations calibrated on the U.S. suggest that not taking into account these spillover effects could lead to misestimating the rebound effect notably of residential sector EEIs. We also demonstrate how the size and the duration of the rebound effect depend on the elasticities of substitution’s values. Numerical simulations suggest that alternative sets of value for the elasticities of substitution may give different sizable patterns of rebound effects in both the short- and long-term. In policy terms, our results support the idea that energy efficiency policies should be implemented simultaneously with rebound effect offsetting policies by considering short- and long-term economy feedbacks. As a consequence, they require considering debates about what type of policy pathways are more effective in mitigating the rebound effect. [ABSTRACT FROM AUTHOR]

The environmental factors of greenhouses affect crop growth greatly and are mutually coupled and spatially distributed. Due to the complexity of greenhouse climate modeling, the current optimal control of greenhouse crop growth rarely considers the spatial distribution issues of environmental parameters. Proper Orthogonal Decomposition (POD) is a technique to reduce the order of a model by projecting it onto an orthogonal basis. In this paper, POD is used to extract environmental features from Computational Fluid Dynamics (CFD) simulations, and a low-dimensional feature subspace is obtained by energy truncation. With multi-dimensional interpolation, fast and low-dimensional reconstruction of the dynamic variation of greenhouse climates is achieved. On this basis, a rolling-horizon optimal control scheme is proposed. For each finite horizon, the external meteorological data are updated, and the response of the greenhouse environment is quickly calculated by the POD model. With the performance criterion J of maximizing crop production and energy efficiency, through the particle swarm optimization algorithm, the optimal settings for the greenhouse shading rate and the fan speed are derived. Such control computations are rolled forward during the whole planting season. Results of a case study show that the proposed method has low computation cost and high spacial resolution and can effectively improve the spatiotemporal accuracy of greenhouse climate management. In addition, different from traditional global optimal control methods, the proposed rolling-horizon scheme can correct various external disturbances in the procedure of crop growth, and thus it is more robust and has potential for engineering applications. [ABSTRACT FROM AUTHOR]

Effective implementation of renewable energy sources (RES) is one of the main challenges in regard to the organization of local energy microgrids with buildings. One of the solutions is the use of dynamic building façades with photovoltaic (PV) panels, in particular the innovative perovskite solar cells (PSCs). This paper describes a case study performed on a pilot installation of perovskite PV panels located in Poland, Central-Eastern Europe. Results of preliminary measurements on this installation are provided in terms of verifying its energy efficiency and the possibility of selecting settings for the façade dynamics control system. Our experiments have considered the sun-tracking mechanism and its energy consumption as well as the impact of weather conditions at different times of the year. The energy efficiency results for the PV system, with average levels below 10%, are rather low. Therefore, even small energy savings in the operation of the PV system itself are significant. Changes in control scenarios for sun-tracking have been proposed and have obtained a reduction from 5% to 1% of energy consumption in autumn and from almost 3.2% to 0.6% in spring, in relation to overall energy produced by the PV system. The need for further experimental research from the perspective of the development and extension of the analyzed installation is pointed out as well. [ABSTRACT FROM AUTHOR]

Summary: Wireless sensor network (WSN) is frequently being used for increasing the data collection and monitoring critical parameters. Major challenge in WSN design is achieving the better energy efficiency and latency considering the dynamic sink location. Lots of research has been done for improving the performance of WSN systems in wide range of applications. Prime goal of this paper is to evaluate the performance of WSN routing under the grid‐based dynamic sink locations. Later the performance of various existing critical protocols is compared to route data over centralized server. Various applications of WSNs are tabulated along with the sensor utilization. The paper contributed in three passes. Initial contribution of this research is to identify the issues and limitations of present WSN communication technologies. The paper contributed to present a case study to discover the implications of dynamic sink routing for building protocol to extend network's lifetime. The effectiveness of several clustering‐based WSN routing algorithms is first compared in this paper. After that, the protocol with the longest network life is put to the test under a grid‐based dynamic sink routing scenario. The significance of clustering‐based protocols for improving lifetime of the network is evaluated as case study. The clustering‐based energy efficient protocol like low energy adaptive clustering hierarchy (LEACH) and its different variants, PEGASIS, SEP, DEC, their variants, and so on, are compared in this paper. Various performance metrics like network delays, throughput, latency, energy consumption and network lifetime are defined for studying routing protocols. Significance of dynamic sink locations performance is evaluated for Enhanced Distributed Energy Efficient Clustering (EDEEC) protocol. Overall paper covers and reviewed many critical design aspects for WSN networks. [ABSTRACT FROM AUTHOR]

Greenhouse gases emission as well as total energy consumption in buildings of public importance, such as schools, municipal buildings, health care centers, can be significantly reduced by increasing buildings' energy efficiency. Buildings' energy consumption adds up to 37% of total energy consumption in the EU countries. In the Republic of Serbia this amount is significantly higher, about 50%. School buildings are considered as one of the most diverse structures from the point of energy-efficient design and construction. The main aim of this paper is to determine the most appropriate settings for possible improvements in energy efficiency and temperature comfort inside a typical primary school classroom in Serbia. The energy efficiency analysis was performed during the heating season for the naturally ventilated primary school classroom located in the eastern Serbia region. The analysis was performed using novel CFD model, suggested in this paper. The suggested model was used to solve two hypothetical scenarios. The first scenario simulates the temperature field in classroom with current energy characteristic envelope of the school building. The calculated numerical data from the first scenario were compared with in-situ measurements values of temperature and wall heat fluxes and showed satisfying accuracy. The second scenario was simulated to indicate possible improvements, which would allow energy consumption decrease and thermal quality enhancement. The analyzed results, calculated using the suggested numerical model under the second scenario conditions, showed that using appropriate set of measures, it is possible to obtain desired temperature comfort levels without need for increase in the building energy consumption. [ABSTRACT FROM AUTHOR]

Mobile ad hoc networks (MANETs) include a collection of distinct and autonomous nodes that move independently and send data using wireless channels. Clustering and secure routing are treated as proficient techniques to achieve energy efficiency and network stability. Different methods have been presented for addressing the issues of mobility and battery limited characteristics of mobile nodes in MANETs. This paper aims to develop new cluster-based secure routing protocols in MANETs. This paper presents a new Type II fuzzy-based clustering with improved ant colony optimization-based routing (T2FCATR) protocol for secured data transmission in MANETs. Initially, a new type II fuzzy-based clustering process takes place to construct the clusters. Then, the routing issue is addressed by ACO with the Tumbling technique, which offers intercluster routing from CHs to BS. In addition, a hybrid data transmission mechanism is also involved to reduce the number of data transmissions and thereby achieve energy efficiency. The performance of the T2FCATR model has been validated against several aspects. The simulation outcome implied that the T2FCATR model achieves minimum clustering overhead, minimum variations in CHs and CMs. As a whole, it can be concluded that the T2FCATR model is superior to all the compared methods under several aspects. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a multi‐hop cognitive radio (CR) enabled device‐to‐device (D2D) network is considered to extend the communication from a functional area (FA) to a non‐functional area (NFA). A D2D user utilizes a cellular user (CU) band in the cognitive mode for information transmission while maintaining the service quality of CUs by satisfying a collision constraint. It transmits with full power in overlay mode, while the power is controlled in underlay mode. We derive the outage probability of the considered D2D network. The main challenge in CR communications lies in the system robustness to uncertainties. In this paper, we also show the impact of the noise power uncertainty in a multi‐hop D2D network. The expressions for throughput and energy efficiency are also developed under collision constraint and noise uncertainty. The outage probability, throughput, and energy efficiency are investigated for several network parameters such as collision probability, sensing time, noise uncertainty, etc. It is observed that the collision constraint and noise uncertainty have significant impacts on network performance. A simulation test‐bed is developed in MATLAB, and the results obtained in the simulation are verified with the analytical results. [ABSTRACT FROM AUTHOR]

It has been shown in the literature that the lifetime of a wireless sensor network is heavily connected to the number of transmissions that network nodes have to undertake. Considering this finding, along with the effects of the energy hole problem where nodes closer to the sink node transmit more than the more distant ones, a node close to the sink node will be the one that transmits the most, while it will also be the node that will deplete its battery first. Taking into consideration that the failure of a single network node to operate, due to its battery being discharged, can lead to a network stopping its operation, the most energy-consuming node in the network will also be the one that will be responsible for the network's termination. In this sense, the most energy-consuming node's energy consumption optimization is the main case in this paper. More specifically, in this work, it is firstly shown that the energy consumption of a wireless sensor network is closely related to each network node's traffic load, that is the transmissions of the packets that are created or forwarded by a node. The minimization of the most energy-consuming node's energy consumption was studied here, while the implementation of a traffic-load-based algorithm is also proposed. Under the proposed algorithm, given a simple shortest path approach that assigns a parent (i.e., the next hop towards the sink node) in each network node and the knowledge it provides regarding the distance (in hops in this paper's case) of network nodes from the sink node, the proposed algorithm exploits the shortest path's results in order to discover, for all network nodes, neighbors that are of the same distance (from the sink node) with the initially assigned parent. Then, if such neighbors exist, all these neighbors are equally burdened with the parenting role. As a result, the traffic load is shared by all of them. To evaluate the proposed algorithm, simulation results are provided, showing that the goals set were achieved; thus, the network lifetime was prolonged. In addition, it is shown that under the algorithm, a fairer distribution of the traffic load takes place. [ABSTRACT FROM AUTHOR]

This paper presents a literature review of recent research on introducing the Industry 4.0 approach to improving energy efficiency, especially in the wood industry. While researchers focus on processes, service, and customer concepts, the effect on energy consumption is less addressed in these studies and applications. This paper focuses on previous works that discuss how to apply Industry 4.0 concepts to energy issues, such as to achieve better efficiency and performance for the industry in general and the wood industry in particular. The complexity of the study requires a multistep development. First, we define each concept separately and the relationships between them. Second, we apply a search algorithm to find related articles with specific terms, and then use the PRISMA method to select the most important ones, eliminating duplicates and excluding articles that do not mention energy efficiency and Industry 4.0 in the manufacturing or wood industry. Third, we explain and categorize the results and consolidate the study with brief examples from other industries. Finally, we conclude the study by mentioning the limitations and perspectives. [ABSTRACT FROM AUTHOR]

In this paper, a review of the adoption status of energy efficiency and renewable energy technologies is presented, specific to US residential buildings. Various technologies are reviewed and categorized as either their relative "higher adoption" or "lower adoption" rates within the US housing stock. More importantly, the review analysis investigates the main factors associated with their high or low adoption rates. Specifically, the paper provides a background of the historical progression of energy efficiency programs as well as sustainability certifications and standards for buildings. The review then analyzes specific building energy efficiency and renewable energy technologies applied to US residential buildings and their adoption rates. The review analysis indicates that building technologies are more frequently adopted for multiple reasons including requirements by codes and standards, incentives through green certifications, low implementation costs, and acceptance and popularity by the public. In contrast, technologies with low adoption rates have higher payback periods, are not required or highly incentivized through codes and certifications, have limited promotion about their benefits, or are not compatible with existing systems. By determining the reasons for the high and low adoption rates, mitigation options can be identified to increase the application of sustainable energy technologies in designing and retrofitting buildings. [ABSTRACT FROM AUTHOR]

The paper discusses existing trends and prospects for decarbonization in the Commonwealth of Independent States (the CIS), an international organization that regroups Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkmenistan, and Uzbekistan. The CIS occupies a significant share of Eurasia, representing a large share of global energy consumption and production with a corresponding carbon footprint. These countries and their decarbonization prospects are rarely discussed in the English-language scientific literature. This paper fills in this gap by offering a comprehensive analysis based on statistical data, policy documents, and scenario-based future projections. The results underline that revisiting Nationally Determined Contributions, increasing energy efficiency, and decoupling GDP growth from greenhouse gas emissions are essential to the implementation of the Paris Agreement. The future energy mix should include larger shares of renewable energy, hydrogen, fossil fuels (highly efficient with carbon capture), and nuclear energy to achieve energy security and decarbonize the economy of the region in the long term. [ABSTRACT FROM AUTHOR]

As the energy efficiency is a worldwide topic for sustainability in sustainable manufacturing, the industry ought to undertake the responsibility in a low energy manner. For energy efficiency, this paper proposed a novel lightweight non-holonomic spherical underactuated robot (NSUR) with lower energy consumption and fewer actuators than traditional robotics. The kinematics of a robot refers to the motion analysis, such as coordinates, velocity, and acceleration. However, current researches always focus on the holonomic full-actuated robot. This paper is devoted to a kind of novel NSUR and its theoretical kinematics analysis model. After NSUR was introduced, the kinematic representation of NSUR was discussed. A pair inverse and forward kinematics analysis of NSUR was put forward in detail. The kinematic analysis of joint of underactuated robot, as the application of NSUR, is applied to explain and verify this methodology. The measurements and comparisons of energy efficiency between NSUR and traditional robotics are also derived in detail. [ABSTRACT FROM AUTHOR]

WSN consists of many sensors, they need high throughput and network lifetime to get involved in communication. Duty Cycle is a key factor in sensor nodes to maintain sleep, active condition in the presence of overhearing, collisions of packets while data transmission between sensor nodes. The key challenge of sensor nodes is to attain high energy efficiency, throughput and low End-End Delay. This paper presents several of existing approaches for MAC protocol. They are (1) Synchronization between nodes (2) Mathematical Analysis (3) TDMA based MAC and (4) Cross-Layer Design. We proposed a new method for MAC protocol with variable duty cycle. Neighboring nodes follow same duty cycle and same active time. Far away nodes doesn't maintain same duty cycle, hence their active time is not same. The duty cycle is maintained in synchronous way and adaptive manner among the nodes within the network. In this paper, a conventional MAC and proposed MAC are simulated using NS-2.35. Variable duty cycle approach in the proposed MAC with sleep and idle states for the nodes yields better throughput and energy efficiency with respect to other conventional technique. These results validate that the proposed variable DC-MAC is feasible for Wireless Sensor Network applications. [ABSTRACT FROM AUTHOR]

Purpose: Many institutions of higher education have committed to carbon neutrality. Given this goal, the main economic issue is minimizing cost. As for society as a whole, dominant decarbonization strategies are renewable electricity generation, electrification of end uses and energy efficiency. The purpose of this paper is to describe the optimum combination of strategies. Design/methodology/approach: There are four questions for eliminating the primary institutional greenhouse gas emissions: how much renewable electricity to produce on-site; where and at what price to purchase the balance of renewable electricity required; how to heat and cool buildings without fossil fuels; and how much to invest in energy efficiency. A method is presented to minimize decarbonization costs by equating marginal costs of the alternates. Findings: The estimated cost of grid-purchased carbon-free energy is the most important benchmark, determining both the optimal level of campus-produced renewable energy and the optimum efficiency investment. In the context of complete decarbonization, greater efficiency investments may be justified than when individual measures are judged only by fossil-fuel savings. Practical implications: This paper discusses a theoretically ideal plan and implementation issues such as purchasing carbon-free electricity, calculating marginal costs of conserved energy, nonmarginal cost changes, uncertainty about achieving efficiency targets, and dynamic pricing. The principles described in this study can be used to craft a cost-minimizing decarbonization strategy. Originality/value: While previous studies discuss decarbonization strategies, there is little economic guidance on which strategies are optimal, on how to combine strategies to minimize cost or how to identify a preferred path to decarbonization. [ABSTRACT FROM AUTHOR]

The internet is expanding its viewpoint into each conceivable part of the cutting-edge economy. Unshackled from our web programs today, the internet is characterizing our way of life, regardless of whether it's sitting in front of the TV or driving an independent auto. The enchantment of the internet appears to be relatively unbounded. In any case, with each new spell there comes an ever-increasing amount of data, and interest for computational power. Cloud computing which is an on-request conveyance of computing power, applications, database storage, and other IT assets by means of the Internet has violently expanded our computerized lives. Though, there have been critical improvements as far as accessibility, fluctuation, time and quality in administrations are concerned; the unbounded development of our computerized way of life requires monstrous measures of power, especially for the data centers that fill in as the mind of the advanced economy. Data organizations foresee a decrease in the quantity of data centers, as more businesses close their little data centers and move towards cloud computing. All things considered, the move by clients towards cloud, will increase the general energy utilization significantly, exceeding any energy productivity increase; which has recorded for over 70% of data center development in 2018. Many research advancements are already made in this domain for minimizing the energy utilization of the computing types of gear included; for efficient power energy consumption, decrease of carbon impression and e-squander. These procedures are supporters of green cloud computing, which are focused on planning and advancing energy-proficient activities to contain inordinate energy utilization in data centers. This paper discusses different mechanisms for lowering the power utilization in data centers. It provides in depth detail about the various mechanisms that can be employed at the hardware component level so that the utilization of energy by component can be reduced. Techniques that can be applied at network, cluster of servers' level along with the various dynamic power management measures that can be employed at the hardware or firmware level and can lead to energy efficient or green data centers are also studied in detail. The paper concludes with the research challenges for building the green data centers. [ABSTRACT FROM AUTHOR]

Based on the review of a wide range of literature, this paper finds that: (1) the average specific surface energy of various single crystals is only 0.8 J/m2. (2) The average specific fracture energy of the rocks with a pre-crack under static cleavage tests is 4.6 J/m2. (3) The average specific fracture energy of the rocks with a pre-cut notch but with no pre-crack under static tensile fracture (mode I) tests is 4.6 J/m2. (4) The average specific fracture energies of regular rock specimens with neither pre-made crack nor pre-cut notch are 26.6, 13.9 and 25.7 J/m2 under uniaxial compression, tension and shear tests, respectively. (5) The average specific fracture energy of irregular single quartz particles under uniaxial compression is 13.8 J/m2. (6) The average specific fracture energy of particle beds under drop weight tests is 74.0 J/m2. (7) The average specific fracture energy of multi-particles in milling tests is 72.5 J/m2. (8) The average specific energy of rocks in percussive drilling is 399 J/m3, that in full-scale cutting is 131 J/m3, and that in rotary drilling is 157 J/m3. (9) The average energy efficiency of milling is only 1.10%. (10) The accurate measurements of specific fracture energy in blasting are too few to draw reliable conclusions. In the last part of the paper, the effects of inter-granular displacement, loading rate, confining pressure, surface area measurement, premade crack, attrition and thermal energy on the specific fracture energy of rock are discussed. [ABSTRACT FROM AUTHOR]

This paper proposes a novel modulation scheme called "In Phase and Quadrature-Filter Shape Index Modulation" (IQ-FSIM). It aims to enhance the spectral/energy efficiencies (SE/EE) while generalizing several existing modulations and index modulation (IM) domains. In this system, the bitstream is divided into three sub-streams. The first is mapped using amplitude–phase modulation, and the other two are mapped separately to an index of a filter shape at the in-phase and quadrature components. IQ-FSIM in SISO mode enhances the SE by 2 log 2 N (double FSIM gain), thanks to the independent indexation of N different filter shapes on each component changing at the symbol rate. A low-complexity matched filter-based detector that reaches the optimal joint ML performance is proposed. The theoretical lower bounds for the probability of filter index error and the symbol/bit error rate (SER/BER) are derived and validated. The computational complexity of the proposed IQ-FSIM transceiver is estimated and compared to its predecessor FSIM, where it is shown that IQ-FSIM provides up to 93.7% complexity reduction compared to FSIM along with different advantages. In addition, the results reveal that both IQ-FSIM and its special case FSIM, even with non-optimal filter shapes, outperform the equivalent schemes with/without IM of the same SE in AWGN, flat, and frequency-selective fading channels. [ABSTRACT FROM AUTHOR]

This paper is related to light pollution and the energy efficiency of outdoor amenity lighting. It concerns the standard design assessment parameters of light pollution, the Upward Light Ratio (ULR) and Upward Flux Ratio (UFR), and the classic energy efficiency parameter—Normalized Power Density (NPD). The motivation for this research was the observation of certain inaccuracies related to the applicability and interpretation of these parameters in practice and the lack of connection between parameters of light pollution and energy efficiency. The multi-variant computer simulations of the exemplary large-area parking lot lighting system were conducted. Over four hundred cases were carefully analyzed. Individual cases differ in the shape of the task area, luminaire arrangements, mounting height, luminous intensity distribution, aiming, and maintenance factor. The results confirmed that the criteria values of ULR and UFR are often overestimated for modern luminaires, which emit luminous flux emitted only downwards. In this case, the ULR and UFR values do not exceed the criteria values for even zones with lower ambient brightness. Thus, lighting solutions with much lower energy efficiency easily meet the requirements of these parameters. This situation is not rational. So, it is crucial to make the criteria of ULR and UFR much more stringent in all environmental zones. Moreover, the research confirms a strong positive linear correlation between UFR and NPD (0.92, p < 0.001), which means that light pollution can be reduced by ensuring an appropriate level of energy efficiency. It is a great help in designing sustainable outdoor amenity lighting. [ABSTRACT FROM AUTHOR]

Water and energy are the main natural resources, and their rational use is the basis for sustainable development. Therefore, the energy efficiency of water supply networks is one of the priorities for the management system of water utilities. Many methods and indicators can be used to assess the energy efficiency of water distribution networks (WDNs), and their choice should be adapted to the characteristics of a WDN. This paper presents an energy audit of WDNs that are supplied from five reservoirs located above the supply area, to which water is supplied from four underground and surface water intakes. In the analysis of the system operation, a hydrodynamic computer model of the water distribution network was used to estimate the operating parameters that are necessary to determine the energy efficiency indicators. A new method for calibrating the emitter coefficient used for water loss modeling is also proposed. The conducted audit showed that more than 70% of the energy supplied to the WDS was "lost", mainly due to friction (37%) and water losses (27%). Thanks to hydraulic modeling, it was possible to indicate that 34% of the energy lost in the system was related to the use of pressure-reducing valves (PRV), and that only 3% was directly related to friction. In turn, the majority of leaks are attributed to service connections (17.4% vs. 8.8% in the water distribution network). [ABSTRACT FROM AUTHOR]

In this paper, a unified level 2 Advanced Process Control system for steel billets reheating furnaces is proposed. The system is capable of managing all process conditions that can occur in different types of furnaces, e.g., walking beam and pusher type. A multi-mode Model Predictive Control approach is proposed together with a virtual sensor and a control mode selector. The virtual sensor provides billet tracking, together with updated process and billet information; the control mode selector module defines online the best control mode to be applied. The control mode selector uses a tailored activation matrix and, in each control mode, a different subset of controlled variables and specifications are considered. All furnace conditions (production, planned/unplanned shutdowns/downtimes, and restarts) are managed and optimized. The reliability of the proposed approach is proven by the different installations in various European steel industries. Significant energy efficiency and process control results were obtained after the commissioning of the designed system on the real plants, replacing operators' manual conduction and/or previous level 2 systems control. [ABSTRACT FROM AUTHOR]

Most of the countries in South-East Europe primarily depend on fossil fuels to cover their energy demands. The paper discusses the future perspective on wind energy in the country, where over 90% of energy is generated in coal-fired thermal power plants. Given the energy crisis, that has gripped the world, the possibility of covering the increased energy demand is being studied, especially during the winter. Based on current trends on energy generation, with just symbolic participation of wind, hydro and solar energy, the potential for maximization of the use of wind energy is considered, which means the use of each identified adequate location throughout the country. The main advantage here is that the maximum energy produced by wind is during winter when demand increases. This is important to know that Kosovo faces significant heating problems and its demand is covered with electricity. Analyzes prove that the country has a generous wind capacity, which reduces to a certain extent the need to import and even enables the export of energy under certain conditions. The potential installation capacity in Kosovo is 510.9 MW, of which 32.4 MW is currently in operating conditions. From the analysis made for the current wind farm in operation, the plant capacity factor is 31.8%. The study of the results indicates a direct correlation between the increase in load during the winter season and the electricity production by wind farms, thereby, the energy demand can be sufficiently covered. [ABSTRACT FROM AUTHOR]

Developing clustering algorithms for energy optimization, for the Internet of Things (IoT) applications based mainly on wireless sensors networks services, is a major research challenge. The large amount of data generated by this type of networks, requires a huge quantity of energy and a large number of Internet connections to support communication between different devices via the Internet. Therefore, clustering protocols for data routing in IoT, also referred to as hierarchical routing protocols, need to take into account energy efficiency, the number of individual connections and scalability. In this paper, we propose a novel distributed clustering protocol based on the objects' performances aggregation for hierarchical communications in IoT applications focused on Wireless Sensors Networks (WSNs) for the self election of Cluster Heads (CHs) and the clusters construction. Each node calculates a threshold T(i) considered as a competition timer to become a CH. A node can be a CH only once among a fixed number of rounds. An optimum number of clusters is computed based on the network parameters. Simulation results show that our proposed solution is better with energy management performance parameters compared to the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol and two other developed energy-efficient protocols namely LEACH-MAC and TB-LEACH. [ABSTRACT FROM AUTHOR]

In wireless sensor networks, the energy efficiency is a big challenge and this can be defeated using various techniques such as clustering and routing. In the clustering approach, clusters are made up of the sensor nodes. In most of the applications, the sensor nodes are battery-powered. The sensor nodes may carry an uneven load of data and consume an unequal amount of energy. This leads to the formation of an energy hole in the network. Therefore, load balancing in the network with respect to the distance of data transmission is important in WSN. Hence, this paper proposes an energy-efficient as well as Load Balanced Clustering algorithm using Fuzzy logic (LBCF). The values of load and distance between the sensor node and BS are associated using rule-based fuzzy logic. The output values of the fuzzy system decides the cluster heads (CHs) and the size of the cluster. The sensor nodes get assigned to the CHs with respect to the capacity of CH. The simulations are conducted under different scenarios and network parameters and the proposed LBCF shows out performance to the state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

Variable speed drives are the most promising technique for reducing electric motors' energy consumption. This paper discusses energy savings by installing variable speed drives to control rotating equipment motors such as pumps, compressors, blowers, and fans in oil processing facilities. In addition to energy savings, variable speed drives will improve overall equipment efficiency, increase reliability, and reduce greenhouse gas (GHG) emissions. An energy audit was performed on a case study to investigate energy consumption for all electric motors. Technical and operational constraints for installing and operating variable speed drives were discussed. Installation requires adjustments in operation schedules and parameters to allow reducing energy consumption. The case study has illustrated how to calculate energy savings for pipelines, air coolers, air blowers for furnaces, pumps with variable flow rates, and reciprocating compressing systems. Variable speed drives were technically and economically accepted in air blowers, fans, and pumps. Energy consumption and GHG emission were reduced by 67%. The payback period for the whole project was less than one year. Meanwhile, it was not valid for reciprocating compressors as the payback period was 6.2 years. [ABSTRACT FROM AUTHOR]

For improving the energy efficiency level in industrial systems, the service specialists should take appropriate measures to improve the efficiency in a timely manner. A necessity arises to provide adequate training for current and future specialists and practitioners. This training can be based on the digital technologies taking into account the information revolution we are witnessing and the future trends in this field. In this paper, a unified training methodology and laboratory equipment on energy efficiency investigation in induction motor drives is developed based on a developed automated computer system. The methodology is provided with created software products based on developed complex algorithms. The methodology procedure and the corresponding learning processes are organized into six main stages. In order to implement the method in the training of specialists, a computer laboratory bench is designed and implemented. The training is provided with three elaborated textbooks. The education conducted using the methodology improves the competence of the trained persons and gives them the opportunity to make justified and correct decisions and take relevant actions. The proposed development is used for educating number of students in some master programs in the University of Ruse. A major part of them already works in the field. [ABSTRACT FROM AUTHOR]

In ship systems, diesel power generators are used in various systems of autonomous power plants to ensure power supply security. This article presents an autonomous hybrid system of a ship power plant with a diesel generator with a permanent magnet synchronous generator and electricity storage in parallel topology (the permanent magnet synchronous generator is connected directly to the receiving network). The electricity storage through the active converter is connected to the receiving network in parallel with the permanent magnet synchronous generator. The decoupled control of the reactive and active power in the active converter enables stabilization of the voltage in the ship's electrical power grid while ensuring the possibility of obtaining different operating regimes of the power plant at various stages of the ship's operation. The innovative method of voltage stabilization presented in this article is based on the compensation of the unfavorable reaction of the permanent magnet synchronous generator armature through the optimal transmission of negative inductive reactive power from the active converter to the generator using the electromagnetic properties of the synchronous generator. The active converter controls the direction of the active power transmission between the DC source, the grid, and the permanent magnet synchronous generator. This paper proposes a hybrid autonomous power plant system using battery storage in place of a single diesel generator set against the commonly used two diesel generator sets, working in parallel, to increase the energy efficiency of the power plant by minimizing the specific fuel consumption of the diesel generator set. The article examines the possibilities of such a mechatronic system design based on analytical research and analysis of electromagnetic and energy characteristics using the Matlab-Simulink program. [ABSTRACT FROM AUTHOR]

This study analyzes the impact of green finance and renewable energy on energy efficiency in E−7 economies. We analyzed the nonlinear and asymmetric effects of green finance and renewable energy on energy efficiency. We collected data from 1985 to 2017 and applied the NARDL and 2SLS methods. The results reveal that the differences in green finance development in the E−7 region are as follows: China (0.61), Brazil (0.55), India (0.53), Indonesia (0.49), Mexico (0.37), and Russia (0.39). In 2019, the Gini coefficient was the largest in Russia (0.57), followed by Turkey. Based on empirical findings, the largest barrier to green energy efficiency is insufficient private and governmental investment in the energy sector to improve access to power, to increase energy security and promote economic growth in an environmentally sustainable manner. The findings point to a promising but vulnerable future for renewable energy and energy efficiency deployment in E−7 countries. This paper emphasizes that green financing and renewable energy policy limitations must be addressed to realize the funding potential of energy efficiency in E−7 countries. • We have analyzed the barrieres for renewable energy and energy efficiency. • Non-linear and asymmetric effects is observed on energy efficiency. • We have applied NARDL model to examine the relationship among variables. [ABSTRACT FROM AUTHOR]

In this paper, determination of optimized regenerative braking-torque function and application in energy efficient driving strategies is presented. The study investigates a lightweight electric vehicle developed for the Shell Eco-Marathon. The measurement-based simulation model was implemented in the MATLAB/Simulink environment and used to establish the optimization. The optimization of braking-torque function was performed to maximize the recuperated energy. The determined braking-torque function was applied in a driving strategy optimization framework. The extended driving strategy optimization model is suitable for energy consumption minimization in a designated track. The driving strategy optimization was created for the TT Circuit Assen, where the 2022 Shell Eco-Marathon competition was hosted. The extended optimization resulted in a 2.97% improvement in energy consumption when compared to the result previously achieved, which shows the feasibility of the proposed methodology and optimization model. [ABSTRACT FROM AUTHOR]

Summary: In a high‐speed vehicular scenario, due to vehicle penetration loss (VPL) and fast signal fluctuations, frequent handovers occur, which results in more battery consumption. So power saving is a critical concern in high‐speed wireless networks. In the past, moving relay (MR)‐based heterogeneous network (HetNet) models were proposed and studied to overcome the effect of VPL, but the issue of power saving has not been studied till now for vehicular HetNet. In this paper, we propose an energy‐efficient algorithm that selects the best number of cooperative MRs among multiple MRs installed on the top of the train for efficient utilization of transmission power in a NOMA‐based wireless network. A half‐duplex amplify‐and‐forward relaying protocol is used for the investigation. We define the optimization problem of energy efficiency for cooperative MR. The problem of energy maximization is stated as an optimization problem, and an energy‐efficient MR selection algorithm is proposed as the solution to the optimization problem. The simulation results show that the proposed algorithm enhances the energy efficiency of vehicular and nonvehicular users and it also decreases the outage probability at fixed spectral efficiency in comparison with the fixed MR‐based selection combining and maximum ratio combining diversity techniques. This result will be beneficial in vehicular communication to achieve maximum energy efficiency. [ABSTRACT FROM AUTHOR]

Summary: Wireless sensor network (WSN) is a well‐developed domain suitable in the optimal collection and processing of information needed for the present world. For processing and transmitting the correct data by the network, it is affected by many disrupting factors like interference, battery life, distance between the nodes, and redundant data. There have been many methods proposed in the past. Among all the disrupting factors, routing has been the most studied problem in the WSN literature, whereas packet length sizing has been the most untouched topic compared to routing. Sizing the packet lengths to transmit it through the network is important to get error‐free data and run an energy‐efficient network. In this paper, we propose a sling‐shot spider optimization (S2SO) algorithm for packet length optimization in WSN and Internet of Things (IoT)‐based networks. The S2SO algorithm is developed based on the spider's unique behavior of catching prey. The proposed algorithm is implemented in three types of networks: 1‐hop, 2‐hop, and multi‐hop networks. A mathematical model for the communication channel, energy efficiency, and energy consumption is developed for all three types of networks. The proposed packet length optimization model is simulated in MATLAB software and compared with conventional bio‐inspired algorithms. The results show that the proposed algorithm is very fast in finding the optimal results and transmits optimal packet size with low error rate of 0.2 p.u. and a high efficiency of 98%. [ABSTRACT FROM AUTHOR]

In Africa, switching to renewable energy sources with low carbon emissions is becoming more popular. In the Economic Community of West African states (ECOWAS), the low-carbon energy transition must overcome significant obstacles, including those posed by policies put in place and their implementation. In order to replace the current fossil fuel-driven economy with low-carbon development that also advances the regional aims and Sustainable Development Goals (SDGs), this paper analyzes the current policy landscape in the region. A total of 75 policies from four categories (energy access, energy efficiency, renewable energy, climate change) were chosen for the policy review. Multicriteria decision analysis and a thorough review of the literature have shed light on how well the policies of the ECOWAS countries could promote low-carbon development and what the main challenges to overcome are. The last step was the comparison of the progress of the two key policies in the region: the National Energy Efficiency Action Plan (NEEAP) and National Renewable Energy Action Plan (NREAP). The results illustrate the amount of work still needing to be done in the region, with only 26 of the 75 policies receiving a score above 50. However, the prospect of a better energy strategy that adequately considers the difficulties of the energy transition is possible, given the progress made by the region's nations since the creation of national action plans for energy efficiency (EE) and renewable energy (RE). Our analysis has also shown that countries like Senegal have obtained quite promising results, as evidenced by the best scores of 76.88 and 73.25, respectively, obtained by its NREAP and NEEAP policies. [ABSTRACT FROM AUTHOR]

Accuracy is the vital indicator in location estimation used in many scenarios, such as warehousing, tracking, monitoring, security surveillance, etc., in a wireless sensor network (WSN). The conventional range-free DV-Hop algorithm uses hop distance to estimate sensor node positions but has limitations in terms of accuracy. To address the issues of low accuracy and high energy consumption of DV-Hop-based localization in static WSNs, this paper proposes an enhanced DV-Hop algorithm for efficient and accurate localization with reduced energy consumption. The proposed method consists of three steps: first, the single-hop distance is corrected using the RSSI value for a specific radius; second, the average hop distance between unknown nodes and anchors is modified based on the difference between actual and estimated distances; and finally, the least-squares approach is used to estimate the location of each unknown node. The proposed algorithm, named Hop-correction and energy-efficient DV-Hop (HCEDV-Hop), is executed and evaluated in MATLAB to compare its performance with benchmark schemes. The results show that HCEDV-Hop improves localization accuracy by an average of 81.36%, 77.99%, 39.72%, and 9.96% compared to basic DV-Hop, WCL, improved DV-maxHop, and improved DV-Hop, respectively. In terms of message communication, the proposed algorithm reduces energy usage by 28% compared to DV-Hop and 17% compared to WCL. [ABSTRACT FROM AUTHOR]

The energy efficiency of material extrusion additive manufacturing has a significant impact on the economics and environmental footprint of the process. Control parameters that ensure 3D-printed functional products of premium quality and mechanical strength are an established market-driven requirement. To accomplish multiple objectives is challenging, especially for multi-purpose industrial polymers, such as the Poly[methyl methacrylate]. The current paper explores the contribution of six generic control factors (infill density, raster deposition angle, nozzle temperature, print speed, layer thickness, and bed temperature) to the energy performance of Poly[methyl methacrylate] over its mechanical performance. A five-level L25 Taguchi orthogonal array was composed, with five replicas, involving 135 experiments. The 3D printing time and the electrical consumption were documented with the stopwatch approach. The tensile strength, modulus, and toughness were experimentally obtained. The raster deposition angle and the printing speed were the first and second most influential control parameters on tensile strength. Layer thickness and printing speed were the corresponding ones for the energy consumption. Quadratic regression model equations for each response metric over the six control parameters were compiled and validated. Thus, the best compromise between energy efficiency and mechanical strength is achievable, and a tool creates significant value for engineering applications. [ABSTRACT FROM AUTHOR]

The number of operations incorporating E-VTOL aircrafts is increasing each year, and the optimization of the energy consumption of such vehicles is a major problem. In this paper, a small-scale ARCHER helicopter's energy consumption is analyzed, wherein different flight conditions, main rotor revolutions, and flight control system settings are considered. The helicopter dynamic model was developed in the FLIGHTLAB environment and was then validated based on flight test data. The model used for the calculation of energy consumption was developed using the electric and dynamic characteristics of the main rotor, electric motor, and transmission system. The main part of this work concerns the analysis of electric energy consumption during the vehicle's flight via the use of an automatic flight control system (AFCS) that ensures repeatable flight conditions. The AFCS was designed such that it includes both path and attitude control to provide hover and cruise control modes. The helicopter's energy consumption was analyzed during different phases of flight, when executing maneuvers, and using different main rotor angular velocities to perform - a given task. The results show that the level of energy consumption significantly depends on the helicopter's main rotor revolutions, flight speed, and the maneuvers performed. The proposed methodology can be used in prospective energy-efficient mission planning and UAV helicopter design. [ABSTRACT FROM AUTHOR]

The need for healthy indoor conditions, the energy crisis, and environmental concerns make building ventilation systems very important today. The elements of ventilation systems to reduce energy intensity are constantly the subject of much scientific research. The most recent articles published in the last three years are analyzed in this paper. Publications focused on the topic of reducing energy consumption in ventilation systems were selected and divided into five key research areas: (1) the aspect of the airtightness of buildings and its importance for the energy consumption, (2) the methods and effects of implementing the concept of demand-controlled ventilation in buildings with different functions, (3) the possibilities of the technical application of decentralized ventilation systems, (4) the use of earth-to-air heat exchangers, (5) the efficiency of exchangers in exhaust air heat-recovery systems. The multitude of innovative technologies and rapid technological advances are reflected in articles that appear constantly and prompt a constant updating of knowledge. This review constitutes a relevant contribution to recognizing current advancements in ventilation systems and may be helpful to many scientists in the field. [ABSTRACT FROM AUTHOR]

The publication deals with the problem of the effect of interference with the movement of the "preceding" train on the movement of the "following" train in the case of efforts to reduce the distance between trains on a moving block interval. The paper presents results of the simulations for train of the ED250 type for a set of 135 traffic situations: for three contexts of reducing the speed of the "preceding" train, for five variants of the method of controlling the "following" train and for nine initial distances between these trains. The results confirmed the possibility of gaining time and energy benefits by implementing an appropriate method of controlling the "following" train, as well as providing insights into the area of shortening the gaps between trains, including the pursuit of synchronizing the speed of trains and possibly coupling them into a so-called virtual couples. [ABSTRACT FROM AUTHOR]

Due to the growing impact of the information and communications technology (ICT) sector on electricity usage and greenhouse gas emissions, telecommunication networks require new solutions which will enable the improvement of the energy efficiency of networks. Access networks, which are responsible for the last mile of connectivity and also for one of the largest shares in network energy consumption, are viable candidates for the implementation of new protocols, models and methods which will contribute to the reduction of the energy consumption of such networks. Among the different types of access networks, hybrid fiber–wireless (FiWi) networks are a type of network that combines the capacity and reliability of optical networks with the flexibility and availability of wireless networks, and as such, FiWi networks have begun to be extensively used in modern access networks. However, due to the advent of high-bandwidth applications and Internet of Things networks, the increased energy consumption of FiWi networks has become one of the most concerning challenges required to be addressed. This paper provides a comprehensive overview of the progress in approaches for improving the energy efficiency (EE) of different types of FiWi networks, which include the radio-and-fiber (R&F) networks, the radio-over-fiber networks (RoF), the FiWi networks based on multi-access edge computing (MEC) and the software-defined network (SDN)-based FiWi networks. It also discusses future directions for improving the EE in the FiWi networks. [ABSTRACT FROM AUTHOR]