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Engineering a low-cost diatomite with Zn-Mg-Al Layered triple hydroxide (LTH) adsorbents for the effectual removal of Congo red: Studies on batch adsorption, mechanism, high selectivity, and desorption
In this work, naturally occurring, low-cost diatomite (De) or diatomaceous earth (DE) adsorbent was treated with various molar concentrations (0.05, 0.1, and 0.2 M) of Zn-Mg-Al layered triple hydroxide (LTH) using a co-precipitation approach. The DE-modified samples were named 0.05 LDE, 0.1 LDE, and 0.2 LDE and employed to remove Congo Red (CR) dye from an aqueous solution. The adsorbents were examined using XRD, BET-N2 adsorption-desorption method, ATR-IR, FESEM-EDX, and XPS, and also analyzed for zeta potentials of adsorbents at pH values between 5 and 11 to observe their surface charges. The removal efficiencies of CR were 96.5%, 99.7%, and 94.5% for 20 mg of 0.05 LDE, 0.1 LDE, and 0.2 LDE, respectively, at pH 7. A bare DE, however, showed a removal efficiency of only 7.4%. After CR adsorption, the maximum adsorption capacities (qmax) of the adsorbents were examined using the Langmuir isotherm, and the results showed that 0.1 LDE-CR (44.0 mgg?1) had a higher qmax than 0.05 LDE-CR (35.6 mgg?1), 0.2 LDE-CR (27.9 mgg?1), and DE-CR (0.9 mgg?1). The optimal adsorbent of 0.1 LDE was utilized for the selectivity and salt effects based on the investigation's efficiency in removing contaminants. 0.1 LDE has been studied for reusability of up to five cycles and can remove CR up to three cycles with 77.7% and 79.9% efficiency using NaCl and NaOH, respectively. The adsorbents may therefore be particularly effective at removing CR from water and beneficial in industrial settings where dye is often used. 2023 Elsevier B.V. -
Engineered MOF-199 Modified Electrodes for Enhanced Electrochemical Immunosensing of Lactoferrin via Signal Amplification
The detection of lactoferrin (LF), an essential immunological and nutritional biomarker, demands highly sensitive analytical platforms for low-level detection. In this study, a label-free electrochemical immunosensing platform was constructed by immobilizing anti-lactoferrin antibodies (Anti-LF-Ab) on a multiwalled carbon nanotube and a metalorganic framework (MWCNT/MOF-199) nanocomposite-modified glassy carbon electrode (GCE). The synergy between MWCNTs and MOF-199 provided abundant active sites for antibody immobilization and enhanced electron transfer, yielding an eightfold current increase compared to bare GCE. Electrochemical analyses confirmed efficient charge transfer and stable antibody binding. Under optimized conditions, the immunosensor exhibited exceptional analytical performance with a low detection limit of 5.24 ng ml?1 and a quantification limit of 17.46 ng ml?1 across a wide detection range of 050 ng ml?1. The platform demonstrated strong analytical reliability, including excellent repeatability (RSD < 5%), reproducibility and operational stability over multiple measurement cycles for LF detection in food diagnostics. In addition, Monte Carlo simulations confirmed the stability of the layer-by-layer assembly, supporting the robustness of the engineered sensing interface. 2025 The Author(s). Published on behalf of The Electrochemical Society by IOP Publishing Limited. -
Engineered core-shell nanocomposite fibres incorporating bio-ceramics and bioactive molecules for wound repair
Skin plays a major role in protecting the body from external injuries and contaminants. Despite the self-healing mechanisms of the body, wound healing has several limitations, such as being time-consuming, leading to scar formation, and susceptibility to infections. In this study, a novel coreshell nanofibre membrane was designed to protect wounds and prevent secondary trauma, thereby enhancing the wound healing process. A coreshell nanofibre membrane was prepared using polycaprolactone (PCL) as the core polymer loaded with astaxanthin (ASTX) and bioglass (BG), while the shell was made from polylactic acid (PLA) containing nanohydroxyapatite (nHA) to support faster wound healing. The surface structure, morphology, and hydrophilicity of the fibres were extensively characterised. The analysis revealed uniform, well-organised, interconnected coreshell nanocomposite fibres ideal for cell adhesion and growth. In vitro studies have demonstrated enhanced cell viability and wound closure in mouse L929 fibroblast cells. Immune response studies on test membranes loaded with ASTX, BG, and nHA revealed strong anti-inflammatory and antibacterial activities against Gram-positive and Gram-negative bacteria. In vivo studies indicated favourable cellular responses and superior wound healing potential of membranes incorporated with ASTX, BG and a higher concentration of nHA. These findings highlight the potential of coreshell nanofibre membranes as an innovative wound dressing for full-thickness skin injuries, showing significant promise for biomedical applications, especially in wound healing treatments. 2025 -
Engineered biocorona on microplastics as a toxicity mitigation strategy in marine environment: Experiments with a marine crustacean Artemia salina
The marine environment has become a major sink for microplastics (MPs) wastes. When MPs interact with biological macromolecules, the biocorona forms on their surface, which can alter their biological reactivity and toxicity. In this study, we investigated the impact of biocorona formation on the toxicity of aminated (NH2) and carboxylated (COOH) polystyrene MPs towards the marine crustacean Artemia salina. Biocoronated MPs were prepared using cell-free extracts (CFEs) from microalgae Chlorella sp. (phytoplankton) and the brine shrimp Artemia salina (zooplankton). The results revealed that biocorona formation effectively reduced the toxicity of MPs. Pristine NH2-MPs exhibited higher reactive oxygen species production (ROS) (182%) compared to COOH-MPs (162%) in Artemia salina. Notably, NH2-MPs coronated with brine shrimp CFE exhibited a substantial reduction in ROS production (127%) than those coronated with algal CFE, with COOH-MPs showing a similar trend (120%). Biocorona formation also significantly decreased malondialdehyde (MDA) levels and antioxidant activity compared to pristine MPs. Molecular docking and dynamics simulations demonstrated a strong binding between polystyrene and acetylcholinesterase (AChE). In vitro studies indicated that pristine NH2-MPs exhibited more reduction in AChE activity (84%) compared to COOH-MPs (95%). However, no significant reduction in AChE activity was observed upon exposure to MPs coronated with either algal or brine shrimp cell-free extracts. Independent action modeling indicated an antagonistic interaction for MPs coronated with both the CFEs. Pearson correlation and cluster heatmap analysis suggested that the toxicity reduction in Artemia salina might be driven by decreased oxidative stress followed by the corona formation. Overall, this study provides valuable insights into the potential of biomolecules from phytoplankton and zooplankton to reduce MPs toxicity in Artemia salina, while highlighting their role in modulating the toxicity of other marine pollutants. 2024 The Author(s) -
Engineered biocorona on microplastics as a toxicity mitigation strategy in marine environment: Experiments with a marine crustacean Artemia salina
The marine environment has become a major sink for microplastics (MPs) wastes. When MPs interact with biological macromolecules, the biocorona forms on their surface, which can alter their biological reactivity and toxicity. In this study, we investigated the impact of biocorona formation on the toxicity of aminated (NH2) and carboxylated (COOH) polystyrene MPs towards the marine crustacean Artemia salina. Biocoronated MPs were prepared using cell-free extracts (CFEs) from microalgae Chlorella sp. (phytoplankton) and the brine shrimp Artemia salina (zooplankton). The results revealed that biocorona formation effectively reduced the toxicity of MPs. Pristine NH2-MPs exhibited higher reactive oxygen species production (ROS) (182%) compared to COOH-MPs (162%) in Artemia salina. Notably, NH2-MPs coronated with brine shrimp CFE exhibited a substantial reduction in ROS production (127%) than those coronated with algal CFE, with COOH-MPs showing a similar trend (120%). Biocorona formation also significantly decreased malondialdehyde (MDA) levels and antioxidant activity compared to pristine MPs. Molecular docking and dynamics simulations demonstrated a strong binding between polystyrene and acetylcholinesterase (AChE). In vitro studies indicated that pristine NH2-MPs exhibited more reduction in AChE activity (84%) compared to COOH-MPs (95%). However, no significant reduction in AChE activity was observed upon exposure to MPs coronated with either algal or brine shrimp cell-free extracts. Independent action modeling indicated an antagonistic interaction for MPs coronated with both the CFEs. Pearson correlation and cluster heatmap analysis suggested that the toxicity reduction in Artemia salina might be driven by decreased oxidative stress followed by the corona formation. Overall, this study provides valuable insights into the potential of biomolecules from phytoplankton and zooplankton to reduce MPs toxicity in Artemia salina, while highlighting their role in modulating the toxicity of other marine pollutants. 2024 The Author(s) -
Engine behavior analysis on a conventional diesel engine combustion mode powered by low viscous cedarwood oil/waste cooking oil biodiesel/diesel fuel mixture An experimental study
Binary biofuel is the best alternative source that completely replaces petroleum-based fuel. In this study, we have experimented with the waste cooking oil and cedarwood oil as biofuel in a DI CI engine for various proportions and related its combustion, emission, and performance characteristics to those of base diesel. This study aims to eliminate the utilization of fossil fuel in a diesel engine by introducing green binary fuel (low viscous fuel resulting from the blending of cedarwood oil with WCO biodiesel) successfully. The objective of the study is to convert cedarwood WCO into green binary fuel and investigate its performance, emission, and combustion properties. The transesterification process is utilized for the enhancement of WCO as biodiesel. It occasioned a reduction in brake thermal efficiency as the addition of waste cooking oil in the blend increased. At the same time, the maximum value of BTE of 27.8% was attained for B10C90 (10% transesterified waste cooking oil and 90% cedarwood oil in volume), whereas it was 28.1% for diesel at maximum load conditions. The BSEC was 15.4 MJ/kW-hr for B10C90 and 12.8 MJ/kWhr for diesel. The emission characteristics, CO, HC, NOx, CO2, and smoke for B10C90 were 17.93 g/kWhr, 0.55 g/kWhr., 20.09 g/kWhr, 2210.9 g/kWhr, and 25.55%. Combustion features such as NHRR, burn duration, MPRR, combustion efficiency, Ignition delay, and coefficient of variance for B10C90 were 53.74 bar, 29.38 CAD, 4.71 bar/CAD, 99.7%, 7.01 CAD, and 4.73% respectively. It showed that B10C90 had comparable performance (BTE) and combustion values to mineral diesel with better emission characteristics. 2024 The Institution of Chemical Engineers -
Engaging Adolescents With ASD in Animal-Assisted Therapy: Benefits of Human-Animal Bond
Adolescents with autism spectrum disorder lack social competence. Considering the chronic nature of the disorder, it becomes essential to focus on this critical developmental phase. For people with ASD, animal- assisted interventions appear to help enhance social functioning. This chapter aimed to explore whether therapy animals could help adolescents with ASD become more socially adept through research utilizing an AB single- case experimental design with two adolescents. The participants were measured on social competence, attention, and memory. Over a month, the intervention was given twice a week for 45-60 minutes, resulting in 8 therapy sessions. With the assistance of a trained dog, a licensed clinical psychologist delivered the AAT sessions. Results show that AAT helps improve social competence alongside fostering better attention and memory. The chapter highlights the role of human- animal interactions in the developmental period of adolescence with ASD. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Engagement Detection through Facial Emotional Recognition Using a Shallow Residual Convolutional Neural Networks
Online teaching and learning has recently turned out to be the order of the day, where majority of the learners undergo courses and trainings over the new environment. Learning through these platforms have created a requirement to understand if the learner is interested or not. Detecting engagement of the learners have sought increased attention to create learner centric models that can enhance the teaching and learning experience. The learner will over a period of time in the platform, tend to expose various emotions like engaged, bored, frustrated, confused, angry and other cues that can be classified as engaged or disengaged. This paper proposes in creating a Convolutional Neural Network (CNN) and enabling it with residual connections that can enhance the learning rate of the network and improve the classification on three Indian datasets that predominantly work on classroom engagement models. The proposed network performs well due to introduction of Residual learning that carries additional learning from the previous batch of layers into the next batch, Optimized Hyper Parametric (OHP) setting, increased dimensions of images for higher data abstraction and reduction of vanishing gradient problems resulting in managing overfitting issues. The Residual network introduced, consists of a shallow depth of 50 layers which has significantly produced an accuracy of 91.3% on ISED & iSAFE data while it achieves a 93.4% accuracy on the Daisee dataset. The average accuracy achieved by the classification network is 0.825 according to Cohens Kappa measure. 2020, Intelligent Engineering & System. All rights reserved. -
Engaged institution model: A faculty perspective
This paper attempts to build the engaged institution model from faculty perspective. Data was collected from 200 faculty members across disciplines, who were engaged in community engagement and social responsibility activities in one or the other ways. On analysis of the data, it was found that Instruction and Research, Facilitator, Scholarship factors contribute towards community engagement activities in higher educational institutions and that these factors contribute towards Faculty engagement, Student engagement and Community Engagement. All these factors create Engagement institution model. This work has an implications on theory, practice and policy. Service learning, as a pedagogical tool if implemented in HEIs can effectively bring all the influencing factors together and can help in creating an engaged institution. 2024, IGI Global. All rights reserved. -
Energy-efficient smart cities with green internet of things
With governments of different countries having a vision of smart cities, the technology adoption and implementation are at its peak and the current increase in the usage of advanced technology for a smart city has led to an increase in the carbon imprint across the globe, which needs immediate attention for the environment sustainability. Although the Internet of things (IoT)-enabled devices have changed our world by bringing an ease to our lifestyle, it has to be kept under consideration that they also have adverse effects on the environment. Over the past few years, enabling energy conservation via Internet of Things in the growth of smart cities has received a great deal of attention from researchers and industry experts and has paved the way for an emerging field called the green IoT. There are different dimensions of IoT, in which an effective energy consumption is needed to encourage a sustainable environment. This conceptual paper focuses on the key concept of green IoT and sustainability, knowledge of Smart cities' readiness to Green IoT (G-IoT)-enabled sustainable practices, and identifying the Green IoT sustainability practices for smart cities. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
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-Based Reliable Routing Using Hybrid Nutcracker and Improved Sand Cat Optimization Algorithm for Extending Network Lifetime in WSNs
In wireless sensor networks (WSNs), sensor nodes are deployed in a target region for sensing environmental physical parameters to attain the objective of reactive decision-making. These sensor nodes necessitate energy for processing and forwarding the sensed data to the base station (BS) for better data delivery in WSNs. Balanced energy utilization in WSNs prevents the problem of hotspot, and dynamic cluster head (CH) selection with reliable route establishment is a vital decision-making approach that helps in optimal path selection with maximized energy conservation. In this paper, a nutcracker and sand cat optimization algorithm (NCSCOA)based multiobjective CH selection and sink node mobility scheme is propounded for enabling rapid and reliable data transmission with reduced energy consumption in heterogeneous WSNs. This NCSCOA handled the problem of hotspot as well as isolated nodes and facilitated loop-free routing with the support of the improved nutcracker optimization algorithm (INCOA) that makes the decision of routing using local and global search optimization processes. It constructed an energy-level matrix (ELM) by deriving the impactful factors of intercluster formation, distance between CH and BS, residual energy (RE), and node density for achieving optimal CH selection and route determination. In specific, improved sand cat optimization algorithm (ISCOA) is used during the intercluster formation phase by discovering the optimized path between source and destination during route establishment. Simulation-based findings of the proposed NCSCOA confirmed its efficacy by improving the mean number of alive nodes by 23.18%, reducing energy consumption and delay by 21.86% and 20.98% compared to benchmarked protocols. 2025 John Wiley & Sons Ltd. -
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-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.