Comprehensive Analysis Of Energy Consumption Research Articles

Spiking Neural Networks for Real-Time Pedestrian Street-Crossing Detection Using Dynamic Vision Sensors in Simulated Adverse Weather Conditions

This study explores the integration of Spiking Neural Networks (SNNs) with Dynamic Vision Sensors (DVSs) to enhance pedestrian street-crossing detection in adverse weather conditions—a critical challenge for autonomous vehicle systems. Utilizing the high temporal resolution and low latency of DVSs, which excel in dynamic, low-light, and high-contrast environments, this research evaluates the effectiveness of SNNs compared to traditional Convolutional Neural Networks (CNNs). The experimental setup involved a custom dataset from the CARLA simulator, designed to mimic real-world variability, including rain, fog, and varying lighting conditions. Additionally, the JAAD dataset was adopted to allow for evaluations using real-world data. The SNN models were optimized using Temporally Effective Batch Normalization (TEBN) and benchmarked against well-established deep learning models, concerning their accuracy, computational efficiency, and energy efficiency in complex weather conditions. This study also conducted a comprehensive analysis of energy consumption, highlighting the significant reduction in energy usage achieved by SNNs when processing DVS data. The results indicate that SNNs, when integrated with DVSs, not only reduce computational overhead but also dramatically lower energy consumption, making them a highly efficient choice for real-time applications in autonomous vehicles (AVs).

NeTrainSim: a network-level simulator for modeling freight train longitudinal motion and energy consumption

AbstractAlthough train modeling research is vast, most available simulation tools are confined to city- or trip-scale analysis, primarily offering micro-level simulations of network segments. This paper addresses this void by developing the NeTrainSim simulator for heavy long-haul freight trains on a network of multiple intersecting tracks. The main objective of this simulator is to enable a comprehensive analysis of energy consumption and the associated carbon footprint for the entire train system. Four case studies were conducted to demonstrate the simulator’s performance. The first case study validates the model by comparing NeTrainSim output to empirical trajectory data. The results demonstrate that the simulated trajectory is precise enough to estimate the train energy consumption and carbon dioxide emissions. The second application demonstrates the train-following model considering six trains following each other. The results showcase the model ability to maintain safe-following distances between successive trains. The next study highlights the simulator’s ability to resolve train conflicts for different scenarios. Finally, the suitability of the NeTrainSim for modeling realistic railroad networks is verified through the modeling of the entire US network and comparing alternative powertrains on the fleet energy consumption.

Green ICT Methodology for Energy Consumption Calculation in ICT Architecture Components

As the usage of information and communication technology (ICT) solution have been exploded in the last decades, the research community exhibits a deficiency in terms of methodologies for accurately quantifying the energy consumption of individual ICT components. This paper presents a novel methodology aimed at addressing the existing research gap by offering a comprehensive analysis of energy consumption ranges for ICT components, measured in Watt. The methodology being proposed involves the classification of ICT components into distinct classes, namely sensors, gateways, servers-platforms, and databases, while these classes are further subdivided into sub-classes. The calculation of energy consumption places emphasis on particular components within each sub-class, encompassing CPUs, RAM, GPUs, hard drives, network switches, cooling systems, and communication units. Compared with existing green ICT standards where mainly focused on strategy-related recommendations, the methodology utilises manufacturers’ specifications for standard operational procedures in order to compute energy consumption. The objective of the methodology is to extend the current research and provide countable energy consumption attributes of various component types, that are used in the ICT architecture, supporting the decision-making process of architects regarding environmentally sustainable and high-performance device selection. This study concludes with the development of a tree diagram for calculating the energy consumption of an ICT system.

A Federated Learning Latency Minimization Method for UAV Swarms Aided by Communication Compression and Energy Allocation

Unmanned aerial vehicle swarms (UAVSs) can carry out numerous tasks such as detection and mapping when outfitted with machine learning (ML) models. However, due to the flying height and mobility of UAVs, it is very difficult to ensure a continuous and stable connection between ground base stations and UAVs, as a result of which distributed machine learning approaches, such as federated learning (FL), perform better than centralized machine learning approaches in some circumstances when utilized by UAVs. However, in practice, functions that UAVs must perform often, such as emergency obstacle avoidance, require a high sensitivity to latency. This work attempts to provide a comprehensive analysis of energy consumption and latency sensitivity of FL in UAVs and present a set of solutions based on an efficient asynchronous federated learning mechanism for edge network computing (EAFLM) combined with ant colony optimization (ACO) for the cases where UAVs execute such latency-sensitive jobs. Specifically, UAVs participating in each round of communication are screened, and only the UAVs that meet the conditions will participate in the regular round of communication so as to compress the communication times. At the same time, the transmit power and CPU frequency of the UAV are adjusted to obtain the shortest time of an individual iteration round. This method is verified using the MNIST dataset and numerical results are provided to support the usefulness of our proposed method. It greatly reduces the communication times between UAVs with a relatively low influence on accuracy and optimizes the allocation of UAVs’ communication resources.

Effect of Texture on Total Energy Consumption of High Frequency Hydraulic Impact Piston Pair

Limited by the influence of the traditional clearance seal structure on the leakage and friction loss of piston pair, the energy utilization ratio of the hydraulic impactor is difficult to improve effectively. To solve this problem, a novel micro-texture clearance seal structure of impact piston cylinder was proposed, and an integrated energy consumption evaluation index considering leakage and friction loss of impact piston pair was proposed. Based on the average Reynolds equation, a comprehensive energy consumption analysis model for a textured high-frequency hydraulic impact piston pair was established, and the influence of piston texture parameters on the comprehensive energy consumption under rated working conditions was studied. The results show that the cylindrical texture clearance seal structure provided an effective way to improve the energy utilization ratio of hydraulic impactor, with energy consumption 13~15% less than the traditional structure. Variation of area rates textured made the amplitude value of integrated energy consumption of the piston pair decrease by 4~15%, and the optimum area rate was 0.2~0.4. Depth ratio of texture could also reduce the integrated energy consumption of the piston pair, but the reduction range was small.

Ultra Lightweight Multiple-Time Digital Signature for the Internet of Things Devices

Digital signatures are basic cryptographic tools to provide authentication and integrity in the emerging ubiquitous systems in which resource-constrained devices are expected to operate securely and efficiently. However, existing digital signatures might not be fully practical for such resource-constrained devices (e.g., medical implants) that have energy limitations. Some other computationally efficient alternatives (e.g., one-time/multiple-time signatures) may introduce high memory and/or communication overhead due to large private key and signature sizes. In this paper, our contributions are two-fold: First, we develop a new lightweight multiple-time digital signature scheme called Signer Efficient Multiple-time Elliptic Curve Signature ( <inline-formula><tex-math notation="LaTeX">$\mathtt {SEMECS}{}$</tex-math></inline-formula> ), which is suitable for resource-constrained embedded devices. <inline-formula><tex-math notation="LaTeX">$\mathtt {SEMECS}{}$</tex-math></inline-formula> achieves optimal signature and private key sizes for an EC-based signature <i>without</i> requiring any EC operation (e.g., EC scalar multiplication or addition) at the signer. We prove <inline-formula><tex-math notation="LaTeX">$\mathtt {SEMECS}{}$</tex-math></inline-formula> is secure (in random oracle model) with a tight security reduction. Second, we fully implemented <inline-formula><tex-math notation="LaTeX">$\mathtt {SEMECS}{}$</tex-math></inline-formula> on 8-bit AVR microprocessor with a comprehensive energy consumption analysis and comparison. Our experiments confirm up to 19× less battery-consumption for <inline-formula><tex-math notation="LaTeX">$\mathtt {SEMECS}{}$</tex-math></inline-formula> as compared to its fastest (full-time) counterpart, SchnorrQ, while offering significant performance advantages over its multiple-time counterparts in various fronts. We open-source our implementation for public testing and adoption.

Comprehensive Energy Consumption Analysis of an Electric Vehicle Advanced Thermal Management System with Waste Heat Recovery in Cold Climate Conditions

Comprehensive Energy Consumption Analysis of an Electric Vehicle Advanced Thermal Management System with Waste Heat Recovery in Cold Climate Conditions

Multi-external-chamber coaxial borehole heat exchanger: Dynamic heat transfer and energy consumption analysis

The borehole heat exchanger (BHE) is a key component of a ground-coupled heat pump (GCHP) system, and its heat transfer performance strongly influences the entire system. This study aims to evaluate the dynamic heat transfer characteristics of a multi-external-chamber coaxial (MECC) BHE, and compared to a conventional double U-tube (2U) BHE. A three-dimensional numerical model was established and validated by a field experiment. The effects of several key design and operating parameters on heat transfer were investigated, and a sensitivity analysis was performed. The effect of groundwater flow on heat transfer was investigated using a modified three dimensional model. Case studies including comprehensive energy consumption analysis were carried out for two optimization objectives, based on the three-dimensional model coupled with a pulse-load finite line source model. The results indicate that the maximum and average heat transfer rate of the MECC BHE can be increased by 65.2% and 10.32% compared with the 2U BHE. An optimized design for deep application was performed in which the optimal flow direction and optimal insulation length ratio were included. For case studies conducted with 2U BHE, applying MECC BHE instead can reduce the BHE number by 13.3%, or the energy consumption of the water pump and the entire system by 28.16% and 9.66%, respectively.

Energy efficient wearable sensor node for IoT-based fall detection systems

Falls can cause serious traumas such as brain injuries and bone fractures, especially among elderly people. Fear of falling might reduce physical activities resulting in declining social interactions and eventually causing depression. To lessen the effects of a fall, timely delivery of medical treatment can play a vital role. In a similar scenario, an IoT-based wearable system can pave the most promising way to mitigate serious consequences of a fall while providing the convenience of usage. However, to deliver sufficient degree of monitoring and reliability, wearable devices working at the core of fall detection systems are required to work for a prolonged period of time. In this work, we focus on energy efficiency of a wearable sensor node in an Internet-of-Things (IoT) based fall detection system. We propose the design of a tiny, lightweight, flexible and energy efficient wearable device. We investigate different parameters (e.g. sampling rate, communication bus interface, transmission protocol, and transmission rate) impacting on energy consumption of the wearable device. In addition, we provide a comprehensive analysis of energy consumption of the wearable in different configurations and operating conditions. Furthermore, we provide hints (hardware and software) for system designers implementing the optimal wearable device for IoT-based fall detection systems in terms of energy efficiency and high quality of service. The results clearly indicate that the proposed sensor node is novel and energy efficient. In a critical condition, the wearable device can be used continuously for 76 h with a 1000 mAh li-ion battery.

Designing single layer counter in quantum-dot cellular automata with energy dissipation analysis

Abstract Quantum-dot cellular automata is a promising nanotechnology and a possible alternative to complementary metal-oxide-semiconductor (CMOS) transistors. Nowadays, several sequential and combinational logic circuits have been designed and implemented using QCA nanotechnology. However the impact of energy dissipation constraint is still unobserved while the forming complex QCA circuits. This paper presents energy-efficient memory cell (JK flip-flop) and single layer counter circuit using QCA. Moreover, comprehensive energy consumption analysis of the proposed design along with structural comparison is performed over the state-of-the-art QCA memory cells. Experimental results show the computational supremacy of the proposed design in terms of cell counts, space intricacy, wire crossing and time delays. QCADesigner and QCAPro software tools are used for verifying the circuit functionality and estimating the energy dissipation of the proposed designs.

Towards single layer quantum-dot cellular automata adders based on explicit interaction of cells

Quantum-dot cellular automata is one of the most prominent nanotechnologies considered to continue scaling-down trend of sub-micron electronics. Therefore, numerous combinational and sequential circuits have been redesigned and implemented using this new technology. Considering QCA full adder cell as the basic building block in designing arithmetic circuits, great deals of attention have been paid to this research field targeting to diminish circuit latency and complexity. In this paper, contrary to conventional gate-level implementation approaches used in QCA technology, a new explicit interaction approach is utilized for designing QCA circuits. Thus, in the first step, a new well-optimized structure for three-input Exclusive-OR gate (TIEO) is proposed that is based on cell interaction. Accordingly, a low complexity and ultra-high speed QCA one-bit full-adder cell is designed employing this structure. In the next step, a comprehensive energy consumption analysis and comparison is performed over previously published QCA full-adder cells and the proposed design. QCADesigner and QCAPro tools are used for verifying circuit functioning and estimating dissipated energy.

What does quality-aware data collection really achieve in energy harvesting wireless sensor networks?

Energy is the major bottleneck for wireless sensor networks WSNs. Although energy harvesting sensor nodes have emerged as a solution, new challenges in energy management arise due to the intermittently available energy. We also observe that many applications can tolerate certain levels of data inaccuracies. Here, we exploit the application's tolerance for data inaccuracy to achieve an equilibrium between energy consumption and availability while satisfying application's accuracy needs, thereby improving network lifetime. Performance studies indicate that our method outperforms other data collection methods. Moreover, our comprehensive energy consumption analysis of quality-aware data collection on different sensor node arrangements reveals the limitations on energy savings when quality-aware data collection is used. We show that a tighter cooperation between MAC layer and Application layer, that is achieved through an Application-driven control mechanism can unlock the full potential of quality-aware data collection.

Energy Hole Minimization with Field Division for Energy Efficient Routing in WSNs

We analyze performance of famous cluster based routing protocols and identify the factors affecting energy consumption in wireless sensor networks (WSNs). From theoretical and experimental analysis, it is observed that communication distance and cluster node density are the major sources in the formation of energy and coverage holes. To overcome these deficiencies, we propose a new hybrid approach of static clustering and dynamic selection of cluster heads. We also conduct a comprehensive energy consumption analysis of our technique with selected existing ones. Simulation results show that the proposed technique is relatively better in terms of energy holes minimization and network lifetime prolongation.

Effect of Packet Inter-arrival Time on the Energy Consumption of Beacon Enabled MAC Protocol for Body Area Networks

One of the major concerns for the development of Wireless Body Area Network (WBAN) is to increase the network lifetime. IEEE 802.15.4 standard for Medium Access Control (MAC) layer can be used for energy efficient and reliable transmission by modifying the different control parameters. Such a modification is very difficult, because an accurate model for the influence of these control parameters of minimum energy and delay is not available. Moreover, there is no mechanism available how to adopt and implement these parameters that can implement on the Body Nodes (BNs). In this paper, we provide the mechanism for emergency data along with normal and periodic data by modifying the superframe structure. Coordinator transmits and extra beacon upon the request of emergency data. A comprehensive analysis of energy consumption of BNs including the affect of packet inter-arrival time is given in this paper. Analysis show that, Contention Access Period (CAP) of superframe is not feasible for emergency data due to its extra delay and energy.

A framework for characterising energy consumption of machining manufacturing systems

Energy consumption in machining manufacturing systems is increasingly of interest due to concern for global climate change and manufacturing sustainability. To utilise energy more effectively, it is paramount to understand and characterise the energy consumption of machining manufacturing systems. To this end, a framework to analyse energy consumption characteristics in machining manufacturing systems from a holistic point of view is proposed in this paper. Taking into account the complexity of energy consumption in machining manufacturing systems, energy flow is described in terms of three layers of machining manufacturing systems including machine tool layer, task layer and auxiliary production layer. Furthermore, the energy consumption of machining manufacturing systems is modelled in the spatial and temporal dimensions, respectively, in order to quantitatively characterise the energy flow. The application of the proposed modelling framework is demonstrated by employing a comprehensive analysis of energy consumption for a real-world machining workshop. The characteristics of energy consumption for machine tool layer, task layer and auxiliary production layer are, respectively, obtained using quantitative models in the spatial and temporal dimensions, which provides a valuable insight into energy consumption to support the exploration of energy-saving potentials for the machining manufacturing systems.

Analysis on the Carbon Emission Reduction Potential in the Cement Industry in Terms of Technology Diffusion and Structural Adjustment: A Case Study of Chongqing

A carbon emission reduction potential model based on technology diffusion and structural adjustment has been proposed in the cement industry. Take 2005 as the base period, the total demand and consumption structure for the planning year is predicted according to the industry growth and the urbanization rate. Based on the comprehensive analysis of energy consumption in all aspects of the production process in the cement industry, and considering the effects and trends of the technological progress and technology diffusion on carbon emissions, this article evaluates the carbon reduction potential and take Chongqing for example to predict its total carbon emission and carbon reduction potential in the year 2020.

Bus Energy Consumption for Multilevel Signals

A comprehensive analysis of energy consumption for voltage-mode multilevel signals on a nanometer-technology bus is presented. A transition-dependent model is used which allows simplified calculation of the energy consumption. The accuracy of the approach is demonstrated using circuit simulations of three different electrical models of the bus, namely, lumped-C, distributed-RC, and distributed- RLC networks. We also verify that bus energy consumption is independent of driver resistance, as predicted by the model. Finally, we present a comparative analysis of power consumption for multilevel and binary buses.

Life cycle energy assessment of Australian secondary schools

The Australian Department of Commerce builds many secondary schools in New South Wales every year, and the impact of energy consumption for such a type of construction has rarely been done before in Australia. Although there is a particular responsibility to ensure that public-owned projects contribute to the future well-being of the natural environment, environmental performance and energy efficiency of public projects are not well studied. In order that more informed design and planning decisions can be made about the future construction of school projects, this research paper uses life cycle energy analysis to study the total energy consumption of 20 public secondary school projects in New South Wales. The results will serve as a model for a more comprehensive analysis of energy consumption in establishing environmental performance criteria for the design and construction of future school projects in New South Wales. Le ministère australien du Commerce construit chaque année de nombreuses écoles secondaires dans la province de Nouvelle Galles du Sud; l'étude de l'impact de la consommation d'énergie de ce type de bâtiment a rarement été faite auparavant en Australie. Bien qu'il existe une responsabilité particulière à s'assurer que les projets contribuent au développement harmonieux de l'environnement naturel, les performances environnementales et l'efficacité énergétique des projets publics ne font pas l'objet d'études sérieuses. Pour que l'on puisse prendre des décisions mieux étayées en matière de conception et de planning de futurs projets de construction d'écoles, cette communication s'appuie sur l'analyse énergétique du cycle de vie pour étudier la consommation énergétique totale de 20 projets d'écoles secondaires publiques en Nouvelle Galles du Sud. Les résultats obtenus serviront de modèles à une analyse plus complète de la consommation d'énergie en établissant des critères de performances environnementales applicables à la conception et à la construction de futures écoles en Nouvelle Galles du Sud. Mots clés: Performances des bâtiments, énergie intégrée, analyse énergétique du cycle de vie, énergie opérationnelle, bâtiments publics, écoles