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Energy-efficient low-power LED-mediated effective photodegradation of cationic and anionic dyes by phthalocyanine-based COF sensitized ZnO photoactive material
The present work involves the synthesis of 2D covalent organic framework involving zinc phthalocyanine and perylene systems (2DZnPc) as low-power LED visible-light sensitizer for ZnO nanomaterial. The synthesized materials and their composites (2DZnPc@ZnO) were characterized by Fourier transform infrared spectroscopy (FTIR), powder X-ray diffraction (XRD), Scanning electron microscopy (SEM), and Solid-state diffuse reflectance spectrophotometer to understand the structure, size, morphology, and optical properties. To examine the photodegradation competence of ZnO alone and its four different composites (2DZnPc@ZnO5, 2DZnPc@ZnO10, 2DZnPc@ZnO15, and 2DZnPc@ZnO20) in the presence of the energy-efficient low-power white LED (16 W) as source of visible light, and as modular pollutants, cationic methylene violet (MV) and anionic Eosin Y (EY) dyes were employed. The effect of different parameters on photocatalytic activity such as photocatalyst dosage, interaction time, pH of dye solution, and photocatalyst re-usage is examined. The results indicate that photosensitizing ZnO with 2DZnPc improved photocatalytic performance for the photodegradation of MV and EY dyes substantially. In an optimized environment, the removal efficiency of MV and EY was found to be 98 and 92 % respectively in 90 min. 2024 Elsevier Ltd -
Energy-Efficient Long-Range Sectored Antenna for Directional Sensor Network Applications
The popularity of Directional Sensor Network (DSN) is increasing due to their improved transmission range, spectral reusability, interference mitigation, and energy efficiency. In this paper, the radio module of the DSN is implemented using an eight-sector antenna array. Two types of sectored antennas, namely the Rectangular Patch Sectored Antenna (RPSA) and the Triangular Patch Sectored Antenna (TPSA), are proposed to operate at frequency of 2.4 GHz ISM band. The RPSA has a half-power beamwidth (HPBW) of 45 and a peak gain of 5.2 dBi, while the TPSA has an HPBW of 48 and a peak gain of 4.16 dBi. The design and performance evaluation of RPSA and TPSA in terms of gain, reflection characteristics (|S11|), and HPBW are conducted using Ansys High Frequency Structure Simulator (HFSS) and Vector Network Analyzer (VNA). To demonstrate the concept, the fabricated sectored antennas are connected to MicaZ Wireless Sensor Network (WSN) nodes using an indigenously designed Single Pole 8 Throw (SP8T) Radio Frequency (RF) switchboard. The performance of the DSNs based on RPSA and TPSA is evaluated using the Cooja simulator and a testbed consisting of MicaZ nodes. The results show that RPSA outperforms TPSA and omnidirectional-based WSNs in terms of power consumption, received signal strength, and packet delivery ratio. 2024 IETE. -
Energy-Efficient Cluster in Wireless Sensor Network Using Life Time Delay Clustering Algorithms
Through Wireless Sensor Networks (WSN) formation, industrial and academic communities have seen remarkable development in recent decades. One of the most common techniques to derive the best out of wireless sensor networks is to upgrade the operating group. The most important problem is the arrangement of optimal number of sensor nodes as clusters to discuss clustering method. In this method, new client nodes and dynamic methods are used to determine the optimal number of clusters and cluster heads which are to be better organized and proposed to classify each round. Parameters of effective energy use and the ability to decide the best method of attachments are included. The Problem coverage find change ability network route due to which traffic and delays keep the performance to be very high. A newer version of Gravity Analysis Algorithm (GAA) is used to solve this problem. This proposed new approach GAA is introduced to improve network lifetime, increase system energy efficiency and end delay performance. Simulation results show that modified GAA performance is better than other networks and it has more advanced Life Time Delay Clustering Algorithms-LTDCA protocols. The proposed method provides a set of data collection and increased throughput in wireless sensor networks. 2022 CRL Publishing. All rights reserved. -
Energy-efficient and secure routing strategy for opportunistic data transmission in WSNs
Driven by the critical importance of routing in Wireless Sensor Networks (WSNs) and the security vulnerabilities present in existing protocols, this research aims to address the key challenges in securing WSNs. Many current routing protocols focus on computational efficiency but fall short of providing strong security measures, leaving them vulnerable to malicious attacks. Reactive protocols, often preferred for their reduced bandwidth usage, heighten security concerns due to their limited resources for maintaining network routes, while proactive alternatives require more resources. Additionally, the ad hoc nature and energy limitations of WSNs make traditional security models, designed for wired and wireless networks, impractical. To overcome these limitations, this paper introduces the Secured Energy-Efficient Opportunistic Routing Scheme for sustainable WSNs. The proposed protocol is designed to enhance security by continuously updating neighbor information and verifying the validity of routing parameters, while also being power-aware, a critical factor given the energy constraints of WSNs. The protocol has been evaluated through simulation experiments, measuring key performance indicators such as throughput, average end-to-end delay (E2 delay), energy consumption, and network lifetime. The results demonstrate that the proposed protocol effectively strengthens WSN security while addressing the unique operational constraints of these networks. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Energy-based features for Kannada handwritten digit recognition
In this paper, Kannada handwritten digit recognition system is proposed based on energy features. Ground truth datasets are not available to test the performance of proposed features. Hence, own dataset of Kannada handwritten digits are collected from schools, colleges, business persons and professionals. The digital images are pre-processed using morphological opening operation for removing the noise and bilinear operation is used for normalisation. The normalised image is divided into 16 blocks, and then wavelet filters were applied for each of the 16 blocks and computed the standard deviation for each of them. In this process, a total of 64 standard deviation of the wavelet coefficients are generated of which 48 coefficients are selected as potential features. The average recognition accuracy of 94.80% is achieved using nearest neighbour classifier. The proposed algorithm is free from skew and thinning and it is novelty of the paper. Copyright 2020 Inderscience Enterprises Ltd. -
Energy-Aware Multilevel Clustering Scheme for Underwater Wireless Sensor Networks
The expansion of wireless sensor networks in the underwater environment resulted in underwater wireless sensor networks. It has dramatically impacted the research arena because of its widespread and real-time applications. But successful implementation of underwater wireless sensor networks faces many issues. The primary concern in the underwater sensor network is sensor nodes' energy depletion problem. In this paper, to improve the lifetime of the underwater wireless sensor network, an Energy-Aware Multi-level Clustering Scheme is proposed. The underwater network region is considered 3D concentric cylinders with multiple levels. Further, each level is divided into various blocks, representing one cluster. The proposed algorithm follows vertical communication mode from the sea bed to the surface area in a bottom-up fashion. Multiple levels with varying heights overcome the communication issues due to high water pressure towards the sea bed. Simulations are carried out to show the efficiency of the proposed algorithm, which performs better in terms of a prolonged network lifetime and average residual energy. The simulation result shows significant improvement in the network lifetime compared with current algorithms. 2013 IEEE. -
Energy Storage System Modelling for Hybrid Electric Vehicle
The equivalent circuit model (ECM)-based traditional state-of-charge (SoC) estimate approaches combine all state variables into a single enhanced state vector. However, the stability and accuracy of the estimates are compromised by the correlations between RC voltages and SOC. In this article, the four battery chemistries have been discussed for their state variable characterization i.e. state of charge (SOC). The battery types considered are lead acid, nickel metal hydride, lithium ion. The manufacturera's battery discharge curves are used to determine the model parameters, and a method is also described for doing this. An improved battery model is suggested in this study that can be applied to HEV design and analysis. By incorporating the electrical characteristics of the battery, the model generates precise results. The Authors, published by EDP Sciences, 2024. -
Energy sector in India: Challenges and solutions
Energy plays a vital role in the socio-economic development and human welfare of a country. It is indeed a difficult task to meet the ever increasing demand with minimum environmental risks. Population explosion and economic growth are the two major facts that drives the energy demands. The economic growth rate of India has hit the decade low of 5% in 2012-13, which shows the challenges yet to come. India being a fast developing nation with second largest population in the world, faces a significant challenge to meet the desired economic growth rate and to provide adequate access to affordable and clean energy for a large population. With the growing concern about India's population, energy demands and climatic issues, it is difficult to formulate a sustainable energy plan for the country. At the same time energy plan should have minimal effects on the health of nature by reducing CO2 emissions. To cut down CO2 emissions, to reduce fossil fuel import bills and to reduce the dependence on a third country energy supplies, India has to increase the share of renewable energy sources in the country's final energy consumption to at least 18% by 2020. This paper provides a comprehensive overview of India's energy sector, discusses the current scenario, identifies the energy utilization, challenges and puts forward some effective solutions in meeting the increasing energy demands. 2013 IEEE. -
Energy saving, waste management, and pollution free steps for university campuses
Global warming is a worldwide concern and the documents related to the need for sustainable measures seen in academic and non-academic literature. In a highly populated country like India, these are more severe worries. Multiple established educational institutions across India have taken significant steps in educating their students on sustainable development goals (SDG). Currently there is a need to assess the extent of effect such training has on student populations of such institutes. Present study attempted to assess the efficacy of SDG-implementation training programmes in a reputed private university, through student assessment of student behaviors outside the institute and in their personal life. Using semi-structured in-depth interview methods, interviewed eight students of Undergraduate and Postgraduate programmes. These students were active participants of community service programmes arranged by the university within a sustainable development model. Data were analyzed using reflexive thematic analysis methods. Emerged themes from data analysis indicate a positive change in their worldview and significant modifications in their personal behavior towards sustainability because of being part of such programmes. Educating others through practice and increased socio-environmental awareness were also major themes. Current study contributes in assessing efficacy of sustainability programmes in educational institutions. This study also suggests few recommendations for increasing competence of the same. 2021 Author(s). -
Energy Management System for EV Charging Infrastructure
The increasing adoption of electric vehicles (EVs) has led to a significant rise in the demand for efficient and sustainable charging infrastructure. Managing the energy supply to meet this growing demand while ensuring grid stability presents a critical challenge. This paper presents an energy management system designed for electric vehicle charging infrastructure that balances demand and supply in real time. The proposed system dynamically allocates available power to connected EVs based on their charging demands and the total power available, ensuring optimal utilization of energy resources. By simulating various scenarios, the system demonstrates its capability to prevent overloading, efficiently distribute power, and prioritize critical energy needs. The results of the simulation show that the system can effectively manage power distribution, reduce peak load impact, and enhance the reliability of EV charging networks. This approach offers a scalable and adaptable solution for integrating EVs into the existing power grid, contributing to the development of smart and sustainable transportation systems. The Authors, published by EDP Sciences. -
Energy management of hybrid microgrids A comparative study with hydroplus and methanol based fuel cells
Energy management is essential for the efficient operation of microgrids with reduced energy costs and minimized emissions. Energy management of PV/battery/fuel cell/diesel generator-based microgrid to minimize the operations cost considering battery degradation and emissions for a fully functional microgrid existing in the campus of Sultan Qaboos University, Oman, is presented in this work. A microgrid with a state-of-the-art hydroplus fuel cell without the necessity for hydrogen storage is presented in this study with experimentally obtained parameters. Also, a comparison of operations cost with microgrids using two different technologies of PEM fuel cells, one with hydroplus fuel cell and the second with the methanol fuel cell which requires provision for hydrogen storage is performed with three different cases; the scheduled, grid-tied, and islanded with different scenarios under grid-tied mode. The analysis proved that using a hydroplus fuel cell instead of a methanol fuel cell with hydrogen storage reduces the cost of the daily operation by 6.9% in the scheduled mode and 18.2% in the islanded mode. In the grid-tied mode three different grid limits, 20 kW, 15 kW, and 10 kW are considered. The analysis showed no reduction, 1.3% and 5.9% reduction in the operations cost respectively. The results obtained are highly promising to be applied in microgrids where conventional fuel cells are currently employed. The new technology of fuel cells introduced in this study, possesses the advantages of near zero emissions and reduced operations costs besides avoiding the perilousness of hydrogen storage. 2024 Hydrogen Energy Publications LLC -
Energy Intelligence: The Smart Grid Perspective
Smart grids enable a two-way data-driven flow of electricity, allowing systematic communication along the distribution line. Smart grids utilize various power sources, automate the process of energy distribution and fault identification, facilitate better power usage, etc. Artificial Intelligence plays an important role in the management of power grids, making it even smarter. With the help of Artificial Intelligence and Internet of Things, smart grids can optimize the energy consumption, provide continuous feedback on usage, and monitor live usage statistics, thereby making the energy intelligent. Smart grids require specific hardware to continuously monitor and adapt to the requirements of the system. By enabling energy intelligence, we empower building-level and city-level optimizations that make use of green energy, thereby contributing more toward sustainable development. Thus, the multifaceted energy management system uses sustainable and renewable energy sources, combined with smart devices to provide a two-way communication system to optimize the end-to-end distribution of energy, beneficial to both suppliers and consumers. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
Energy Harvesting Using ZnO Nanosheet-Decorated 3D-Printed Fabrics
In this work, we decorated piezoresponsive atomically thin ZnO nanosheets on a polymer surface using additive manufacturing (three-dimensional (3D) printing) technology to demonstrate electrical-mechanical coupling phenomena. The output voltage response of the 3D-printed architecture was regulated by varying the external mechanical pressures. Additionally, we have shown energy generation by placing the 3D-printed fabric on the padded shoulder strap of a bag with a load ranging from ?5 to ?75 N, taking advantage of the excellent mechanical strength and flexibility of the coated 3D-printed architecture. The ZnO coating layer forms a stable interface between ZnO nanosheets and the fabric, as confirmed by combining density functional theory (DFT) and electrical measurements. This effectively improves the output performance of the 3D-printed fabric by enhancing the charge transfer at the interface. Therefore, the present work can be used to build a new infrastructure for next-generation energy harvesters capable of carrying out several structural and functional responsibilities. 2023 American Chemical Society. -
Energy harvesting using two-dimensional magnesiochromite (MgCr2O4)
Two-dimensional (2D) materials with high surface activity can be utilized for harvesting energy from small mechanical sources using flexoelectricity. In the present work, we have synthesized an atomically thin 2D spinel MgCr2O4 by a liquid-phase exfoliation process, and characterization shows the preferential exfoliation along the (111) plane with low formation energy. The fabricated flexoelectric device produces an electrical response up to ?3 V (peak-to-peak voltage) upon pressing and releasing the cell with ?0.98 N force. Furthermore, the energy harvesting properties of 2D MgCr2O4 are explored by combining bending with other sources of external energy, with applied varying magnetic flux (Vmax = ?2.6 V) and temperature with 0.9 N force (Vmax = ?18 V). Our calculations determine that 2D MgCr2O4 has a flexoelectric coefficient of approximately ?XZXZ = 0.005 nC/m. Overall, the results indicate that 2D MgCr2O4 is a very promising material for the next generation of self-powered wearable electronics and energy harvesting. 2023 Elsevier Ltd -
Energy efficient routing protocols for wireless sensor networks
Wireless Sensor Networks (WSNs) have gained universal attention now a day s owing to the advancements made in the fields of information and communication technologies and the electronics field. This innovative sensing technology incorporate an immense number of sensor nodes or motes set up in newlinean area to perceive any continuously fluctuating physical phenomena. These newlinetiny sensor nodes sense and process the sensed data and transfer this information to a base station or sink via radio frequency (RF) channel. newlineThe small size of these sensors is an advantage as it can be easily embedded within any device or in any environment. This feature has attracted the use of WSNs in immense applications especially in monitoring and tracking; the most prominent being the surveillance applications. But this tiny size of sensor nodes restricts the resource capabilities. Usually the WSNs are installed in application areas where the human intervention is quite risky or difficult. The sensed information might be needed to take critical decisions in emergency applications. So maintaining the connectivity of the network is of utmost newlineimportance. The efficient use of the available resources to the maximum extend newlineis a necessity to prolong the network lifetime. If any node runs out of power, the newlineentire network connectivity collapses and intend of the deployment might become futile. Because of this reason most of the research in the area of WSNs has concentrated on energy efficiency where the design of energy efficient routing protocols plays a major role. newlineThis research work titled Energy Efficient Routing Protocols for Wireless Sensor Networks proposes to develop energy efficient routing protocol strategies so as to enhance the lifetime of the WSNs. A thorough study of the existing literature serves as the back bone for attaining acquaintance concerning the pertinent scenario, the problems faced and the application of the WSNs. newlineThe use of clustering and sink mobility to enhance the energy utilisation is explored in this research. -
Energy efficient routing protocols for wireless sensor networks
Wireless Sensor Networks (WSNs) have gained universal attention now a day???s owing to the advancements made in the fields of information and communication technologies and the electronics field. This innovative sensing technology incorporate an immense number of sensor nodes or motes set up in an area to perceive any continuously fluctuating physical phenomena. These tiny sensor nodes sense and process the sensed data and transfer this information to a base station or sink via radio frequency (RF) channel. The small size of these sensors is an advantage as it can be easily embedded within any device or in any environment. This feature has attracted the use of WSNs in immense applications especially in monitoring and tracking; the most prominent being the surveillance applications. But this tiny size of sensor nodes restricts the resource capabilities. Usually the WSNs are installed in application areas where the human intervention is quite risky or difficult. The sensed information might be needed to take critical decisions in emergency applications. So maintaining the connectivity of the network is of utmost importance. The efficient use of the available resources to the maximum extend is a necessity to prolong the network lifetime. If any node runs out of power, the entire network connectivity collapses and intend of the deployment might become futile. Because of this reason most of the research in the area of WSNs has concentrated on energy efficiency where the design of energy efficient routing protocols plays a major role. This research work titled ???Energy Efficient Routing Protocols for Wireless Sensor Networks??? proposes to develop energy efficient routing protocol strategies so as to enhance the lifetime of the WSNs. A thorough study of the existing literature serves as the back bone for attaining acquaintance concerning the pertinent scenario, the problems faced and the application of the WSNs. The use of clustering and sink mobility to enhance the energy utilisation is explored in this research. A modification of the most traditional energy efficient routing protocol for WSNs, LEACH (Low Energy Adaptive Clustering Hierarchy) is implemented initially by modifying the clustering mechanism. An enhancement of it by incorporating sink mobility, to further augment the energy efficiency is executed next. A modification of HEED (Hybrid Energy Efficient Distributed Clustering Hierarchy) protocol using the unequal clustering technique is also proposed. The modified protocols are simulated using MATLAB under different circumstances by varying the number of sensor nodes and the area of deployment. These modified protocols are intended for delay tolerant applications that require periodic sensing. The performance of the modified protocols is evaluated using metrics like residual energy of the network, packet delivery ratio, energy consumed by the network, delay, and the number of live nodes. The simulation outcomes showcased the effectiveness of the modified protocols compared to the relevant existing protocols in literature. -
Energy efficient heterogeneous clustering scheme using improved golden eagle optimization algorithmfor WSN-based IoT
In the Internet of Things, Wireless Sensor Networks (WSNs) are networks of interconnected sensors that wirelessly collect and transmit information about the environment. Using IoT sensors, IoT applications can remotely monitor and control physical environments. Clustering in WSNs involves organizing sensor nodes into groups called clusters with one or more CHs for efficient data integration, communication and management, improving network performance and resource utilization. In WSNs, achieving energy efficiency is critical to extend network lifetime and ensure stable operation. An important aspect contributing to energy optimization is the selection of CHs. However, the lack of an efficient cluster head selection mechanism remains a significant challenge. Therefore, this study introduces an optimized multivariate cluster head selection method that leverages the Improved Golden Eagle Optimization Algorithm (IGEOA). With this approach, the selection of CHs is optimized, combining multiple objective functions designed for energy efficiency. By using this algorithm, clusters are formed based on the selected CHs. In addition, a cluster maintenance phase is integrated to supervise the post-establishment clustering of the network, which ensures optimal cluster performance and resource utilization in WSN. Evaluation through simulation illustrates that the proposed method significantly improves both performance and energy efficiency in a WSN environment. Bharati Vidyapeeth's Institute of Computer Applications and Management 2024. -
Energy Efficient Evolutionary Algorithm based Clustering with Route Selection Protocol for IoT Assisted Wireless Sensor Networks
Internet of Things (IoT) assisted wireless sensor network (WSN) finds its applicability in several real-time tracking and surveillance applications. However, it suffers from various issues such as restricted battery capacity, repeated interruptions owing to multi-hop data transmission, and limited communication range. Gathering and multihop directing are considered effective solutions to complete enhanced energy competence and a generation of IoT-assisted WSN. An NP-hard problematic that can be handled with an evolutionary algorithm is the collection of the cluster head (CH) and the best potential paths to the goal. Both of these problems involve finding the optimum route to the target (EA). In this context, this study presents the design of the Energy Efficient Evolutionary Algorithm-based Clustering with Route Selection (EEEA-CRS) Protocol for Internet of Things-Assisted Wireless Sensor Networks (IoT-Assisted WSN). The EEEA-CRS technique that has been proposed has the primary intention of enhancing the energy efficiency as well as the lifetime of the IoT-assisted WSN. The EEEA-CRS approach that has been presented is broken down into its basic parts, which are the Fuzzy Chicken Swarm Optimization based Clustering (FCSO-C) phase and the Biogeography Optimization-based Multihop Routing phase (BBO-MHR). The FCSO-C technique that has been suggested chooses CHs with the use of a fitness function that takes into account residual energy, inter-cluster distance, and intra-cluster detachment. In adding, the BBO-MHR strategy identifies the optimum pathways to BS by taking into account the costs of communicating with other clusters, both within and between them. A number of different simulations were carried out in order to demonstrate that the EEEA-CRS methodology yields superior results. The EEEA-CRS method was shown to be superior to other methods in use today, according to the findings of an exhaustive comparison and study. EverScience Publications. -
Energy efficient data collection in sparse sensor networks using multiple Mobile Data Patrons
Wireless sensor networks consist of sensor nodes that can sense the environment and forward the sensed data to the destination. It takes multiple hops for the data to get transmitted from the source to the destination node. Mobile Data Patron is a high energy mobile data collector that collects data from the sensors within sparse networks. In sparse networks, the sensors detect the physical phenomenon, and the MDP is used to collect data generated by the sensors. In existing models, a single MDP is used to collect data from sensors within sparse networks. It requires high amounts of energy for long-range data transmission to the base station. The proposed work uses multiple MDPs to solve the energy depletion problem. The research also focuses on improving the data transfer rate so that the MDPs lose minimal amounts of energy. 2020 -
Energy efficiency and conservation using machine learning
This chapter explores the fascinating nexus between machine learning (ML), energy efficiency, and conservation, concentrating on a captivating case study that makes use of the oneAPI framework. Optimizing energy consumption has become crucial due to the increased interest in sustainable practices. By investigating the use of oneAPI in energy efficiency projects, we examine the possibility of ML techniques to overcome this difficulty. We demonstrate how ML algorithms can accurately model and anticipate energy usage patterns through a thorough analysis of real-world data. Additionally, we discuss the importance of feature engineering, algorithm selection, and data pretreatment in creating accurate energy consumption models. The case study emphasizes the wider implications of utilizing ML to support energy-saving initiatives in addition to demonstrating the effectiveness of oneAPI. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.