Enabling Agricultural Sector through Blockchain Technology Farmers Perspective
Agriculture; Blockchain; COVID-19; Farmer; Food Supply; Pandemic; Security; Technology
The agricultural sectors in India and abroad have been affected extensively due to the Covid-19 pandemic. It is necessary to provide solutions for the availability of resources, controlling the cost, quality in production, transparent food supply, fulfilling demand, and removing intermediaries. The structural reforms in the agricultural sector by adopting emerging technologies, especially blockchain technology (BCT) and the robotics automation process, are inevitable during the pandemic and future development. To study the impact of blockchain on the Agriculture sector, the farmer's level of awareness of the blockchain technology, its methodological influence, the inclination of farmers to adopt the technology in their farming, and agri-related activity are vital. This paper aims to explore the opportunities of BCT in expanding the agriculture sector, ascertain the awareness and intensity of farmers' knowledge of the effect of BCT, and develop the mean difference in the opinion of the farmers towards the utilization of BCT in the relevant field of agriculture. A structured interview schedule was administered with 360 sample farmers from the Delta regions of three states located in the southern part of India, such as Andhra Pradesh, Karnataka, and Tamilnadu, using a purposive sampling technique intending. Irrespective of the age, gender, land capacity, possession, education level, learned procedures, and abundant experience helped the farmers demand a new technology interface to improve their income level and register their sustainability. 2022 by authors, all rights reserved.
Seranmadevi R.; Senthil Kumar A.; Hariharan R.
Universal Journal of Agricultural Research, Vol-10, No. 3, pp. 213-227.
https://doi.org/10.13189/ujar.2022.100304 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132362969&doi=10.13189%2fujar.2022.100304&partnerID=40&md5=09184ad61984f5c26cb51456863f55da
Seranmadevi R., Department of Professional Studies, Central Campus, Christ University, Karnataka, Bangalore, 560029, India; Senthil Kumar A., Department of Commerce, St. Joseph's College (Autonomous), Karnataka, Bangalore, 560027, India; Hariharan R., Department of Commerce, St. Joseph's College (Autonomous), Karnataka, Bangalore, 560027, India
Enabling context-awareness: A service oriented architecture implementation for a hospital use case
Context-aware systems; Pervasive computing; Smart ward; SOA; Web Service
The medical field is continuously flooded with newer technologies and tools for automating all kinds of medical care processes. There are a variety of software solutions and platforms for enabling smart healthcare and for assisting care providers such as doctors, nurses, surgeons and specialists with all kinds of timely insights to diagnose and decide the correct course of actions. There are patient monitoring and expert systems to simplify and streamline healthcare service design, development, and delivery. However there are concerns and challenges with the multiplicity and heterogeneity of technologies and solutions. The dense heterogeneous medical devices available in the intensive therapy units pose a challenge of medical device integration. Needless to say, lot of research work has gone in devising techniques in integrating these systems for exchange of data. However mere device integration does not exploit the modern technologies until meaningful and critical information is presented to doctors and patient care personals adapting to the changes in the patient condition. The goal of this research is to apply context aware computing using service oriented architecture in acquiring, analysing and assisting doctors and nurses with necessary information for easy and critical time saving decision making. This paper presents an implementation of the identified web services which can be consumed during a treatment at the Intensive Therapy Unit (ITU). 2015 IEEE.
Proceedings of the 2015 International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2015, pp. 224-228.
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICATCCT.2015.7456886 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84966622072&doi=10.1109%2fICATCCT.2015.7456886&partnerID=40&md5=8f9e696d5b5d53331dfdfaffeed1ae9c
Immanuel V.A., Department of Computer Science, Christ University, Bangalore, India; Raj P., Infrastructure Architect, IBM Global Cloud Center of Excellence, IBM, Bangalore, 560045, India
Encapsulated 3converter for power loss minimization in a grid-connected system
carrier pulse width modulation; DCAC three phase bidirectional converter; encapsulated DCDC converter; energy storage system
A newly designed DCAC three phase bidirectional converter (DATBC) with an encapsulated DCDC converter (EDC) for the energy storage system (ESD) is analysed and investigated in this research paper. By using encapsulated or embedded or hidden DCDC converter a stable and constant DC bus is developed between the encapsulated DCDC converter and DCAC three phase bidirectional converter. The proposed converter is entirely different from the traditional dual-stage DCAC converter, because it takes less than 20% of power used for the DCAC conversion process. So, this reduced power consumption increases efficiency to a considerable value. A new control technique for zero sequence has been adopted components are inserted in the modulating signal based on carrier pulse width modulation (CPWM). Working principle, implementation and characteristics of the DCAC three phase bidirectional converter are analysed. Effectiveness and feasibility of the developed converter are examined with a proto-type model. 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Suresh K.; Parimalasundar E.; Jayakumar S.; Ravikumar R.
All Open Access; Gold Open Access; Green Open Access
Suresh K., Department of EEE, Christ Deemed to be University, Bangalore, India; Parimalasundar E., Department of EEE, Sree Vidyanikethan Engineering College, Tirupati, India; Jayakumar S., Department of ECE, Er. Perumal Manimekalai College of Engineering, Hosur, India; Ravikumar R., Department of EEE, Joginpally B.R. Engineering College, Hyderabad, India
Encoder-Decoder Approach toward Vehicle Detection
codec; convolutional neural network; moving object detection; Surveillance video; tracking; vehicle detection; YOLOv3
Vehicle Detection algorithms run on deep neural networks. But one problem arises, when the vehicle scale keeps on changing then we may get false detection or even sometimes no detection at all, especially when the object size is tiny. Then algorithms like CNN, fast-RCNN, and faster-RCNN have a high probability of missed detection. To tackle this situation YOLOv3 algorithm is being used. In the codec module, a multi-level feature pyramid is added to resolve multi-scale vehicle detection problems. The experiment was carried out with the KITTI dataset and it showed high accuracy in several environments including tiny vehicle objects. YOLOv3 was able to meet the application demand, especially in traffic surveillance Systems. Grenze Scientific Society, 2023.
14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023, Vol-2023-June, pp. 1-6.
Deb P., Department of Data Science, Christ University Lavasa, Pune, India; Kumar S., Department of Data Science, Christ University Lavasa, Pune, India; Preethi N., Department of Data Science, Christ University Lavasa, Pune, India
Encountering risk with resilience for experiences: a case study on tourism in a conflicted tourist destination
Novel tourist experiences; Psychological resilience; Srinagar; Terrorism risk; Tourism
Purpose: This paper aims to unravel how tourists balance their novel experiences with risk perceptions, psychological resilience and behavioral intentions. Additionally, it explores how tourists' personalities moderate the relationship between experiences and travel intentions. Design/methodology/approach: A total of 234 self-administered questionnaires were distributed to a diverse group of tourists who recently explored the Srinagar region to capture their perspectives. The data obtained was analyzed using Smart PLS-SEM. Findings: This study revealed that the impact of perceived terror risk on behavioral intentions is not statistically significant. Instead, tourists' experiences significantly influence psychological resilience and behavioral intentions. Tourists with higher resilience are inclined to perceive these experiences as aiding in managing negative feelings. Research limitations/implications: The study's focus is confined to one conflict zone within the country due to research constraints, excluding other areas. Practical implications: This research provides practical insights for destination management authorities and highlights areas for improvement for tourism service providers and the government in the Srinagar region, as well as other conflict regions. Emphasizing mutual respect between locals and tourists can foster community-based tourism, enhancing the region's appeal and promoting positive intentions for all involved parties. Social implications: This study examines how local communities in conflict-affected areas adjust to and manage the presence of tourists, with an emphasis on building resilience and support systems. Additionally, it explores how travel decisions and behaviors are influenced by tourists' perceptions of safety and how these perceptions can influence broader societal attitudes toward areas affected by conflict. Evaluating the local population's economic reliance on tourism may result in changed social dynamics, as well as possible exploitation or over-reliance on industry. Promoting mutual understanding and cultural interchange between locals and visitors may have a positive impact on efforts to promote social cohesion and peacebuilding. Originality/value: This study broadens the scope of the existing literature on destination attributes in conflict zones, offering a unique perspective on the intrinsic features of this issue. The solutions proposed in this study contribute a novel dimension to the current literature. 2024, International Tourism Studies Association.
International Journal of Tourism Cities, Vol-10, No. 4, pp. 1414-1434.
Sufi T., Department of Tourism, School of Business and Economics, Universidad de las Amicas Puebla, San Andr Cholula, Mexico; Ranga B., Parul University, Vadodara, India; Ranga I., Department of Tourism Management, School of Business and Management, Christ University, Bangalore, India
Encouraging sustainable living through HR initiatives
This chapter examines how human resources (HR) professionals can facilitate organizational change in the direction of environmental responsibility in the context of sustainable human resource management. HR establishes itself as a strategic catalyst for concrete transformations in employee conduct and organizational culture by implementing performance management integration, waste reduction, and sustainable commuting initiatives. The study emphasizes tangible instances, demonstrating how human resource initiatives surpass theoretical concepts to promote a dedication to environmental stewardship actively. In ecological sustainability, HR professionals serve as catalysts for organizations, imparting knowledge and devising strategies to direct progress. This thorough examination offers practical recommendations for incorporating environmentally conscious principles into the operations of organizations, thereby promoting long-term sustainability. 2024, IGI Global. All rights reserved.
Building Sustainable Human Resources Management Practices for Businesses, pp. 52-73.
Singha R., Christ University, India; Singha S., Kristu Jayanti College (Autonomous), India; Jasmine E., Indian Institute of Psychology and Research, India
Encryption of motion vector based compressed video data
Accordion matrix; CR; Motion compensation; Motion estimation; Motion vector; MSE; PSNR; Run-length coding
Enormous size of video data for natural scene and objects is a burden, threat for practical applications and thus there is a strong requirement of compression and encryption of video data. The proposed encryption technique considers motion vector components of the compressed video data and conceals them for their protection. Since the motion vectors exhibit redundancies, further reduction of these redundancies are removed through run-length coding prior to the application of encryption operation. For this, the motion vectors are represented in terms of ordered pair (val, run) corresponding to the motion components along the row and column dimensions, where val represents value of the motion vector while run represents the length of repetition of val. However, an adjustment for having maximal run is made by merging the smaller run value. Eventually we encrypted the val components using knapsack algorithm before sending them to the receiver. The method has been formulated, implemented and executed on real video data. The proposed method has also been evaluated on the basis of some performance measures namely PSNR, MSE, SSIM and the results are found to be satisfactory. Springer International Publishing Switzerland 2016.
Mishra M.K.; Mukhopadhyay S.; Biswas G.P.
Smart Innovation, Systems and Technologies, Vol-51, pp. 349-357.
Springer Science and Business Media Deutschland GmbH
Mishra M.K., Department of Computer Science, Christ University, Bangalore, 560029, India, Department of CSE, Indian School of Mines, Dhanbad, 826004, Jharkhand, India; Mukhopadhyay S., Department of Computer Science, Christ University, Bangalore, 560029, India, Department of CSE, Indian School of Mines, Dhanbad, 826004, Jharkhand, India; Biswas G.P., Department of Computer Science, Christ University, Bangalore, 560029, India, Department of CSE, Indian School of Mines, Dhanbad, 826004, Jharkhand, India
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.
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
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.