End-to-End Encryption in Resource-Constrained IoT Device
Cryptography; lightweight cryptography; security; the IoT
Internet of Things (IoT) technologies will interconnect with a wide range of network devices, regardless of their local network and resource capacities. Ensuring the security, communication, and privacy protection of end-users is a major concern in IoT development. Secure communication is a significant requirement for various applications, especially when communication devices have limited resources. The emergence of IoT also necessitates the use of low-power devices that interconnect with each other for essential processing. These devices are expected to handle large amounts of monitoring and control data while having limited capabilities and resources. The algorithm used for secure encryption should protect vulnerable devices. Conventional encryption methods such as RSA or AES are computationally expensive and require large amounts of memory, which can adversely affect device performance. Simplistic encryption techniques are easily compromised. To address these challenges, an effective and secure lightweight cryptographic process is proposed for computer devices. This process utilizes a symmetrical encryption key block, incorporating a custom proxy network (SP) and a modified Feistel architecture. Security analysis and performance evaluation results demonstrate that the proposed protocol is secure and energy-efficient. The symmetric key encryption scheme is based on sequences in the Feistel cipher, with multiple rounds and sub-keys generated using principles derived from genetic algorithms. This proposed algorithm minimizes processing cycles while providing sufficient security. 2013 IEEE.
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ACCESS.2023.3292829 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164431177&doi=10.1109%2fACCESS.2023.3292829&partnerID=40&md5=a3dcc33f15079833d4625a59de49c3de
Alluhaidan A.S.D., Princess Nourah bint Abdulrahman University, College of Computer and Information Sciences, Department of Information Systems, Riyadh, 11564, Saudi Arabia; Prabu P., CHRIST (Deemed to be University), Department of Computer Science, Bengaluru, 560029, India
End-to-End Imitation Learning for Autonomous Driving: Design and Implementation on a Custom Robotic Platform
Autonomous Vehicle; Imitation Learning; Jetson Xavier; Linear Actuators; PilotNet
This paper presents an end-to-end imitation learning system for autonomous driving on a custom robotic vehicle. A PilotNet-inspired CNN, trained on 20 laps of Udacity Beta simulator data from three cameras, was deployed on an NVIDIA Jetson Xavier for real-time steering. The robot features a 48V, 1.5kW BLDC motor and a precision steering system using dual linear actuators. Manual override is enabled via an RC controller. The integration of deep learning with custom hardware highlights challenges in transferring simulation-trained models to real-world systems. 2025 IEEE.
Roy, Riya; Saju, Akhil; Renji, Sharon; Pranathi, Sakamuri; Kandangath, Megha Rajesh; Vaahinee, B.; Jeff Ron, S.; Steve, Jaidan; Parag Jose, C.; Wang, Yong
2025 IEEE International Conference on Vehicular Technology and Transportation System, ICVTTS 2025;
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.1109/ICVTTS67119.2025.11296487 https://www.scopus.com/pages/publications/105032138465?origin=resultslist
Roy R., CHRIST (Deemed to be University), Bangalore, India; Saju A., CHRIST (Deemed to be University), Bangalore, India; Renji S., CHRIST (Deemed to be University), Bangalore, India; Pranathi S., CHRIST (Deemed to be University), Bangalore, India; Kandangath M.R., CHRIST (Deemed to be University), Bangalore, India; Vaahinee B., CHRIST (Deemed to be University), Bangalore, India; Jeff Ron S., CHRIST (Deemed to be University), Bangalore, India; Steve J., CHRIST (Deemed to be University), Bangalore, India; Parag Jose C., CHRIST (Deemed to be University), Bangalore, India; Wang Y., Binghamton University, New York, United States
Endophytic bacteria Klebsiella spp. and Bacillus spp. from Alternanthera philoxeroides in Madiwala Lake exhibit additive plant growth-promoting and biocontrol activities
Antimicrobial; Bacterial endophyte; Biofertilizer; Bioinoculant; Halotolerant; IAA; RSM; Sustainability; V. unguiculata
Background: The worldwide increase in human population and environmental damage has put immense pressure on the overall global crop production making it inadequate to feed the entire population. Therefore, the need for sustainable and environment-friendly practices to enhance agricultural productivity is a pressing priority. Endophytic bacteria with plant growth-promoting ability and biocontrol activity can strongly enhance plant growth under changing environmental biotic and abiotic conditions. Herein, we isolated halotolerant endophytic bacteria from an aquatic plant, Alternanthera philoxeroides, from the polluted waters of Madiwala Lake in Bangalore and studied their plant growth promotion (PGP) and biocontrol ability for use as bioinoculant. Results: The isolated bacterial endophytes were screened for salt tolerance ranging from 5 to 15% NaCl concentration. Klebsiella pneumoniae showed halotolerant up to 10% NaCl and Bacillus amyloliquefaciens and Bacillus subtilis showed up to 15%. All three strains demonstrated good PGP abilities such as aminocyclopropane-1-carboxylic acid (ACC) deaminase activity, phosphate solubilization, ammonia production, and nitrogen fixation. In addition, K. pneumoniae also exhibited high indoleacetic acid (IAA) production (195.66 2.51g/ml) and potassium solubilization (2.13 0.07ppm). B. amyloliquefaciens and B. subtilis showed good extracellular enzyme production against cellulase, lipase, protease, and amylase. Both the isolates showed a broad spectrum of antimicrobial activity against the tested organisms. The optimization of IAA production by K. pneumoniae was done by the response surface methodology (RSM) tool. Characterization of IAA produced by the isolate was done by gas chromatography-mass spectrometry (GCMS) analysis. The enhanced plant growth-promoting ability of K. pneumoniae was also demonstrated using various growth parameters in a pot trial experiment using the seeds of Vigna unguiculata. Conclusion: The isolated bacterial endophytes reported in this study can be utilized as PGP promotion and biocontrol agents in agricultural applications, to enhance crop yield under salinity stress. The isolate K. pneumoniae may be used as a biofertilizer in sustainable agriculture and more work can be done to optimize the best formulations for its application as a microbial inoculant for crops. 2023, The Author(s).
Biswas S.; Philip I.; Jayaram S.; Sarojini S.
Journal of Genetic Engineering and Biotechnology, Vol-21, No. 1
Springer Science and Business Media Deutschland GmbH
Biswas S., Department of Life Sciences, CHRIST (Deemed to Be University), Bangalore-29, India; Philip I., Department of Life Sciences, CHRIST (Deemed to Be University), Bangalore-29, India; Jayaram S., Department of Life Sciences, CHRIST (Deemed to Be University), Bangalore-29, India; Sarojini S., Department of Life Sciences, CHRIST (Deemed to Be University), Bangalore-29, India
Endurance and Evolution: Exploring Levels of Resilience Among Indian Breast Cancer Survivors
breast cancer; India; phenomenology; posttraumatic growth; quality of life; resilience; trauma
Resilience for Indian women with breast cancer involves maintaining positivity and adaptability amid the complex challenges affecting their physical, emotional, and social well-being. However, research focused on resilience amongst this population in Indian settings is limited. Therefore, the aim of the study is to explore the experience of levels, patterns, and processes of resilience in Indian women living with breast cancer. A qualitative phenomenological approach was used to study resilience. Thirty-three participants from two hospitals underwent semistructured interviews, including survivors, women in cancer therapy, and family members. Data collected via audio recordings were analyzed using reflective thematic analysis techniques. The finding describes four themes of experience of resilience in women living with breast cancer. (a) Cancer diagnosis is a life-changing experience. Breast cancer diagnosis and therapy cause existential crisis, psychological distress, and social stigma. (b) Restoring healthy perception in an adverse event. Navigating challenges and achieving a balance between internal and external factors. (c) Types of supportthe pathway to resilience. Enhanced their resilience through internal support including attributes, past experiences, sociodemographic factors, and brain fitness. External support includes family, friends, religious or spiritual advisors, medical care, role models, other cancer survivors, and comfortable environments. (d) Learning and growing from the experience. Gained a better perspective on life, ultimately resulting in a new normal and finding meaning in the experience. Data show breast cancer survivors experience dynamic resilience, highlighting the need for culturally tailored interventions and supportive avenues within cancer care by healthcare providers and policymakers. The Author(s) 2024.
Alexander A.; Kuruveettissery S.; Ramesh R.S.; Srinath B.S.; Appachu S.; Thippeswamy R.
Alexander A., Department of Psychology, CHRIST (Deemed to be University), Bengaluru, India, Division of Molecular Medicine, St John's Research Institute, St John's Medical College, Bengaluru, India; Kuruveettissery S., Department of Psychology, CHRIST (Deemed to be University), Bengaluru, India; Ramesh R.S., Department of Surgical Oncology, St. John's Medical College, Bengaluru, India; Srinath B.S., Sri Shankar Cancer Hospital and Research Centre, Bengaluru, India; Appachu S., Sri Shankar Cancer Hospital and Research Centre, Bengaluru, India; Thippeswamy R., Sparsh Hospital, Bengaluru, India
Alexander, Annie; Kuruveettissery, Sreenath; Ramesh, Rakesh S.; Srinath, B.S.; Appachu, Sandhya; Thippeswamy, Ravi
Illness Crisis and Loss;Volume;33;Issue;3;pp.549-579
https://doi.org/10.1177/10541373241260157 https://www.scopus.com/pages/publications/85195310975?origin=resultslist
Energy and Environmental Applications of Polymer Based Mixed Metal Oxide Nanocomposites
The dependence of human lives on fossil fuels is very inevitably high for the development of society. This leads to the exploitation of these non-renewable sources, which brings forth society, which is another major issue that has to be tackled. In this study, we have focused on addressing the energy and environmental needs of society using different catalysts. The polymer based mixed metal oxide catalysts are used for the utility towards multiple applications. The energy issues can be mitigated through newlinesupercapacitance studies and water splitting studies. The water splitting studies can newlineproduce hydrogen, an efficient and eco-friendly fuel, and supercapacitors can store newlineenergy effectively. Water pollution is another problem faced by our society, which newlinereduces the availability of freshwater sources. This can be overcome by following newlineeffective and cost-efficient adsorption techniques. Another major threat that prevails in our society is corrosion. Corrosion inhibition studies are followed to tackle this issue and provide a corrosion-free environment. The various polymers used in this study are polyaniline, polypyrrole, poly (3,4-ethylenedioxythiophene), and chitosan. These polymers are mixed with different metal oxides, and the synergy between the polymers and metal oxides provides efficiency towards the mentioned applications. The successful formation of composites is confirmed using various characterization techniques. Several electrochemical studies like cyclic voltammetry, galvanostatic charge-discharge studies, electrochemical impedance spectroscopy, linear sweep voltammetry, and potentiodynamic techniques are employed to analyze the efficacy of the composites towards supercapacitance, water splitting, and corrosion inhibition studies. The batch adsorption studies are executed for water purification studies. The synthesized multifunctional composites can be used as potential candidates for addressing the energy and environmental needs of our society in a sustainable manner.
Energy efficiency and conservation using machine learning
computational intelligence; conservation; data preprocessing; energy consumption; energy efficiency; energy management; energy sustainability; Machine learning; modeling; oneAPI; optimization; prediction; sustainable development; sustainable practices
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.
Ramakrishnan A.B.; Murugesh T.S.; Pulari S.R.; Vasudevan S.K.; G.K. A.
Green Machine Learning and Big Data for Smart Grids: Practices and Applications, pp. 69-78.
Ramakrishnan A.B., Deparment of Computer Science and Engineering, SASTRA Deemed to be University, SASTRA University Thanjavur Campus, Tamil Nadu, Thanjavur, India; Murugesh T.S., Department of Electronics and Communication Engineering, Government College of Engineering Srirangam, Tamil Nadu, Tiruchirappalli, India; Pulari S.R., Tutor, Bahrain Polytechnic, Bahrain; Vasudevan S.K., Technical Evangelist, APJ, SP&E - Developer Platform and Evangelism, Software and Advanced Technology Group, Intel India Pvt. Ltd., Karnataka, Bengaluru, India; G.K. A., Master of Computer Aplications, Christ University, Karnataka, Bengaluru, India
Energy Efficiency Enhancement in Wind-Powered Pumping with TBRC MPPT Integration
Energy efficiency; Energy storage system; TBRC based MPPT; Wind energy based pumping schemes; Wind power
This paper introduces a novel strategy to enhance energy efficiency in a Battery and Wind Energy-based Pumping Scheme (BWEPS) by implementing a Test Bench Rapid Control (TBRC) based Maximum Power Point Tracking (MPPT) system within a LabVIEW SPEEDGOAT environment. Wind Energy Conversion Systems (WECS) are inherently challenged by the stochastic nature of wind, which causes frequent fluctuations in output power and reduces overall efficiency if not properly managed. To address these issues, this study applies TBRC as a real-time control framework, enabling faster response, improved adaptability, and more accurate tracking of the maximum power point under dynamic conditions. The integration of battery storage further contributes to stabilizing system performance by mitigating intermittency and ensuring reliable energy availability for pumping operations. The proposed approach not only develops and validates the TBRC-based MPPT algorithm but also optimizes BWEPS operation and benchmarks it against traditional energy storage and control techniques. Experimental validation through real-time simulation demonstrates significant improvements in energy efficiency, reliability, and operational stability. The outcomes highlight the potential of TBRC-based MPPT control as a promising solution for advancing hybrid renewable energy systems, offering an effective pathway for sustainable and resilient water pumping applications. 2025 IEEE.
Cheepati, Kumar Reddy; Chandrika, V.S.; Muthukaruppasamy, S.; Kannan, V Kamatchi; Arunraja, A.; Venkatapathi, K.
Proceedings of the 6th International Conference on Smart Electronics and Communication, ICOSEC 2025;pp.793-798
https://doi.org/10.1109/ICOSEC67334.2025.11459571 https://www.scopus.com/pages/publications/105037141430?origin=resultslist
Cheepati K.R., Ksrm College Of Engineering, Electrical And Electronics Engineering, Kadapa, India; Chandrika V.S., Kpr Institute Of Engineering And Technology, Electrical And Electronics Engineering, Coimbatore, India; Muthukaruppasamy S., Velammal Institute Of Technology, Electrical And Electronics Engineering, Chennai, India; Kannan V.K., Knowledge Institute Of Technology, Electrical And Electronics Engineering, Salem, India; Arunraja A., Christ Deemed To Be University, Bangalore, India; Venkatapathi K., Sri Venkatesa Perumal College Of Engineering And Technology, Electrical And Electronics Engineering, Puttur, India
Energy efficient data collection in sparse sensor networks using multiple Mobile Data Patrons
Depletion problem; Mobile data Patron; Resource limited sensors; Sparse distribution; Sparse sensor networks
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
Prabu P.; Ahmed A.N.; Venkatachalam K.; Nalini S.; Manikandan R.
Computers and Electrical Engineering, Vol-87
https://doi.org/10.1016/j.compeleceng.2020.106778 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088988293&doi=10.1016%2fj.compeleceng.2020.106778&partnerID=40&md5=d85072b0322332418602f1c54be66424
Prabu P., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Ahmed A.N., Department of Computer Engineering, Lebanese French University, Iraq; Venkatachalam K., School of CSE, VIT University Bhopal, India; Nalini S., Dept of Applied Mathematics, PSG College of Technology, Coimbatore, India; Manikandan R., School of CSE, VIT University Bhopal, India
Energy Efficient Evolutionary Algorithm based Clustering with Route Selection Protocol for IoT Assisted Wireless Sensor Networks
Clustering; Energy Efficiency; Evolutionary Algorithm; Internet of Things; Multihop Routing; 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.
Priyadharshini T.C.; Geetha D.M.; Anita E.A.M.
International Journal of Computer Networks and Applications, Vol-9, No. 3, pp. 328-339.
https://doi.org/10.22247/ijcna/2022/212558 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135471178&doi=10.22247%2fijcna%2f2022%2f212558&partnerID=40&md5=9ebde8a5f08db7222118a1a6c8cb4d80
Priyadharshini T.C., Department of Information and Communication Engineering, Anna University, Tamil Nadu, Chennai, India; Geetha D.M., Department of Electronics and Communication Engineering, Sri Krishna College of Engineering and Technology, Tamil Nadu, Coimbatore, India; Anita E.A.M., Department of Computer Science and Engineering, Christ University, Bangalore, India
Energy efficient heterogeneous clustering scheme using improved golden eagle optimization algorithmfor WSN-based IoT
CH selection; Energy efficiency; IGEOA; IOT; Wireless sensor network
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.
Silambarasan E.; Naresh E.; Asha V.; Lamani M.R.
International Journal of Information Technology (Singapore)
Springer Science and Business Media B.V.
Silambarasan E., Department of Computer Applications, National Institute of Technology, Tamil Nadu, Tiruchirappalli, India; Naresh E., Department of Information Technology, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India; Asha V., RNS Institute of Technology, Karnataka, Bengaluru, 560 098, India; Lamani M.R., CHRIST (Deemed to Be University), Kanmanike, Kumbalgudu, Mysore Road, Karnataka, Bangalore, 560074, India
Silambarasan, E.; Naresh, E.; Asha, V.; Lamani, Manjunath Ramanna
International Journal of Information Technology (Singapore);Volume;17;Issue;3;pp.1753-1760
https://doi.org/10.1007/s41870-024-02029-z https://www.scopus.com/pages/publications/85196740944?origin=resultslist
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.
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 Smart Scheduling for Multi-path Routing Using Deep Learning
Deep learning; Energy efficient; Multi-path routing; Optimization; Resource management; Smart scheduling
Energy efficiency is a key part of networkingit saves on cost and has an environmental impact. Multi-path routing is a well-known technique used for network traffic management to make it more efficient and reliable. Unfortunately, traditional multi-path routing techniques are oblivious to energy and suffer from poor energy utilization. This paper: An approach to efficient smart scheduling for multi-path routing with deep learning. Employing a deep learning algorithm with relevant network parameters allows us to predict the lightest path for processing in/outbound data. Simulation results demonstrate that our solution guarantees higher energy efficiency than conventional algorithms while enjoying better network performance. This solution proposes the formulation of a green and sustainable networking approach. Thus, it can be better adopted as an innovative security mechanism in many practical scenarios. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Garg, Amit; Logeshwaran, J.; Dhanasekaran, S.; Gupta, Rishi; Singhal, Saurabh
Lecture Notes in Networks and Systems;Volume;1278;pp.419-432
https://doi.org/10.1007/978-981-96-2703-5_28 https://www.scopus.com/pages/publications/105006931876?origin=resultslist
Garg A., Department of Computer Science and Engineering, Manipal University Jaipur, Rajasthan, Jaipur, India; Logeshwaran J., Department of Computer Science, Christ University, Karnataka, Bengaluru, India; Dhanasekaran S., Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, India; Gupta R., Department of Computer Science and Engineering, Manipal University Jaipur, Rajasthan, Jaipur, India; Singhal S., Department of CSE, Apex Institute of Technology, Chandigarh University, Mohali, India
Energy harvesting using two-dimensional magnesiochromite (MgCr2O4)
Device; DFT; Flexoelectricity; MgCr2O4; Two-dimensional material
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
Mahapatra P.L.; Singh A.K.; Tromer R.; Kumbhakar P.; Sinha S.K.; Lahiri B.; Kundu T.K.; Galvao D.S.; Tiwary C.S.
https://doi.org/10.1016/j.mtnano.2023.100374 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165357418&doi=10.1016%2fj.mtnano.2023.100374&partnerID=40&md5=15fa984054593ab753085885c0c54ffa
Mahapatra P.L., School of Nano Science and Technology, Indian Institute of Technology, West Bengal, Kharagpur, 721302, India; Singh A.K., Metallurgical and Materials Engineering, Indian Institute of Technology, Kharagpur, 721302, India; Tromer R., Applied Physics Department and Center for Computing in Engineering and Sciences, University of Campinas, Campinas, S Paulo, Brazil; Kumbhakar P., Metallurgical and Materials Engineering, Indian Institute of Technology, Kharagpur, 721302, India, Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore, 560029, India; Sinha S.K., Department of Materials Engineering, Indian Institute of Science, Bangalore, 560012, India; Lahiri B., Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Kharagpur, 721302, India; Kundu T.K., Metallurgical and Materials Engineering, Indian Institute of Technology, Kharagpur, 721302, India; Galvao D.S., Applied Physics Department and Center for Computing in Engineering and Sciences, University of Campinas, Campinas, S Paulo, Brazil; Tiwary C.S., Metallurgical and Materials Engineering, Indian Institute of Technology, Kharagpur, 721302, India
Energy Harvesting Using ZnO Nanosheet-Decorated 3D-Printed Fabrics
3D printing; energy harvesting; interface; nanogenerator; two-dimensional ZnO
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.
Kumbhakar P.; Ambekar R.S.; Parui A.; Roy A.K.; Roy D.; Singh A.K.; Tiwary C.S.
ACS Applied Materials and Interfaces, Vol-15, No. 37, pp. 44513-44520.
https://doi.org/10.1021/acsami.3c08374 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171900799&doi=10.1021%2facsami.3c08374&partnerID=40&md5=3ff67744c99edb810c532476d9d5eebe
Kumbhakar P., Department of Metallurgical and Materials Engineering, Indian Institute of Technology Kharagpur, West Bengal, Kharagpur, 721302, India, Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore, 560029, India; Ambekar R.S., Department of Metallurgical and Materials Engineering, Indian Institute of Technology Kharagpur, West Bengal, Kharagpur, 721302, India; Parui A., Department of Materials Engineering, Indian Institute of Science, Karnataka, Bangalore, 560012, India; Roy A.K., Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright Patterson AFB, 45433-7718, OH, United States; Roy D., Directorate of Nanomaterials, DMSRDE, GT Road, Uttar Pradesh, Kanpur, 208013, India; Singh A.K., Department of Materials Engineering, Indian Institute of Science, Karnataka, Bangalore, 560012, India; Tiwary C.S., Department of Metallurgical and Materials Engineering, Indian Institute of Technology Kharagpur, West Bengal, Kharagpur, 721302, India
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.
Eapen N.G., CHRIST (Deemed to be University), Pune Lavasa Campus, India; Harsha K.G., CHRIST (Deemed to be University), Pune Lavasa Campus, India; Kesan A., CHRIST (Deemed to be University), Pune Lavasa Campus, India
Energy management of hybrid microgrids A comparative study with hydroplus and methanol based fuel cells
Battery degradation; Emissions; Energy management; Fuel cells; Hydroplus; Operations cost
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
International Journal of Hydrogen Energy, Vol-85, pp. 909-930.
https://doi.org/10.1016/j.ijhydene.2024.08.405 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202354491&doi=10.1016%2fj.ijhydene.2024.08.405&partnerID=40&md5=f7b938e75db7c046baa4d240f8297728
Allwyn R.G., EEE Department, School of Engineering and Technology, Christ(Deemed to Be University), Bangalore Kengeri Campus, Karnataka, India, ECE Department, Sultan Qaboos University, P.O Box 33, P.C 123, Muscat, Oman; Margaret V., EEE Department, School of Engineering and Technology, Christ(Deemed to Be University), Bangalore Kengeri Campus, Karnataka, India; Al-Hinai A., ECE Department, Sultan Qaboos University, P.O Box 33, P.C 123, Muscat, Oman, Sustainable Energy Research Center, Sultan Qaboos University, Muscat, Oman
Energy Management System for EV Charging Infrastructure
Demand-Supply Balancing; Electric Vehicle (EV) Charging; Energy Management Systems (EMS); Real-Time Power Allocation; Renewable Energy Integration; Smart Grid
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.
Bhutkar G.; Kumar Y.; Subramani R.; Jothi E.; Valarmathy A.S.; Sherje N.; Tharmar S.
https://doi.org/10.1051/e3sconf/202459104004 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211798420&doi=10.1051%2fe3sconf%2f202459104004&partnerID=40&md5=aef97eea211aa5b0b909ab931d3ac168
Bhutkar G., Department of Computer Engineering, Vishwakarma Institute of Technology, Pune, India; Kumar Y., Institute of Business Management, GLA University, Mathura, India; Subramani R., Department of Mathematics, Christ University, Bengaluru, India; Jothi E., Department of IT, New Prince Shri Bhavani College of Engineering and Technology, Tamil nadu, Chennai, 600073, India; Valarmathy A.S., Department of EEE, Prince Shri Venkateshwara Padmavathy Engineering College, Chennai, 127, India; Sherje N., Mechanical Engineering, Dr. D. Y. Patil Institute of Technology, Pimpri, Pune, India; Tharmar S., Mohamed Sathak Engineering College, Kilakarai, India