Dr. V.Srikanth

@abbs.edu.in

PROFESSOR AND PROGRAM COORDINATOR-MCA DEPARTMENT
ACHARYA BANGALORE B SCHOOL

Dr. V.Srikanth


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https://researchid.co/dr.srikanthv

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science Applications, Artificial Intelligence, Software
16

Scopus Publications

294

Scholar Citations

11

Scholar h-index

11

Scholar i10-index

Scopus Publications

  • 5G-OPTIMISED QoS CONTROL MECHANISM FOR REAL-TIME DATA STREAMING IN MOBILE AD-HOC NETWORKS (MANETS)
    Journal of Environmental Protection and Ecology, 2025
  • Precision Offloading in Edge Computing: Leveraging Predictive Model
    Suganya T S, Saivijayalakshmi J, Karthik M, Keerthana T, Srikanth V, Vidhya U
    Journal of Machine and Computing, 2024
    The intended effect of the investigation is to provide sophisticated prediction and decision-making models in order to optimize service delivery and improve the Quality of Experience (QoE) for users. This research tackles the problems that are associated with job offloading in edge computing settings. In order to reduce service latency and improve overall performance, the Bi-Directional Long Short-Term Memory (B-LSTM) model is used. This model provides the ability to forecast task creation and server load. In order to accommodate the particular qualities of different devices, the Selective Objective Offloading Decision (SOOD) approach is presented. This method makes use of the TOPSIS methodology to turn server assessment into a decision-making issue that involves several criteria. A considerable increase of 98.4% in user quality of experience is achieved by the SOOD paradigm. In addition, the Rapid Offloading Decision (ROD) model is presented in order to manage unexpected work patterns. This is accomplished by using the log information of surrounding devices, which results in instantaneous and dependable offloading choices. Through the usage of prediction algorithms and selective decision-making, this research gives a complete strategy to improving the efficiency of edge computing. The goal of this technique is to maximize the utilization of servers and the user experience.
  • Development of an Electric Automation Control Model Using Artificial Intelligence
    V. Srikanth, P. Aswini, V. Asha, Khobragade Pithamber, Rajeev Sobti, Z. Salman
    2024 2nd International Conference Computational and Characterization Techniques in Engineering and Sciences Ic3tes 2024, 2024
    The design of an AI-based electrical computerization control system is implemented to efficiently address the challenges encountered by contemporary electrical engineering. A model of an AI-based control system for electrical automation is presented. To achieve optimal control settings, the control strategy makes use of an artificial intelligence system. Even in the presence of a twenty per cent load intervention and 2.1 Hz wavelength interference, the research demonstrates that the organisation has significant anti-interference capabilities, as shown by an acceptable fail rate of 0.02 for each at the system management level. Consequently, using an AI algorithm in automated electrification control may lead to a significant improvement in control reaction time, cost savings, and efficient construction.
  • Machine Learning-Based Analogue Circuit Design for Stage Categorization and Evolutionary Optimization
    V. Srikanth, P. Aswini, Rakesh Chandrashekar, N Sirisha, Manish Kumar, K. Adnan
    2024 2nd International Conference Computational and Characterization Techniques in Engineering and Sciences Ic3tes 2024, 2024
    The goal of this study is to provide a two-stage bottom-up approach that uses machine learning to simplify the development of analogue devices. Analogue CMOS (complementary metal-oxide-semiconductor) circuit designers use their expertise to address complex problems, involving multiple factors and goals. The research delves into the possibilities of libraries housing open-source machine-learning models to aid designers and provides a framework outlining the specifics of ML-generated analogue circuits. Creating neural network designs has traditionally relied on commercialized CMOS or software simulations; however, these approaches don't guarantee optimal performance. The proposed approach is validated using a three-stage device design. In the first stage, the type is accurately predicted with a precision of 89.75% utilising a machine learning approach called the decision tree. Both of these rule induction strategies are used to generate prediction logic. The second stage involves forecasting the usual parameters for each stage type using four learning techniques: decision trees, gradient-boosted trees, random forests, and support vector machines. When compared to other approaches, the support vector machine outperforms them all while exhibiting the lowest error rates.
  • Agriculture using Smart Sensors
    Data Driven Mathematical Modeling in Agriculture Tools and Technologies, 2024
  • Deep Learning-based Dynamic User Alignment in Social Networks
    Khaled Matrouk, Srikanth V, Sumit Kumar, Mohit Kumar Bhadla, Mirza Sabirov, Mohamed J. Saadh
    Journal of Data and Information Quality, 2023
    Academics and businesses are paying intense attention to social network alignment, which centers various social networks around their shared members. All studies to date treat the social network as static and ignore its innate dynamism. In reality, an individual's discriminative pattern is embedded in the dynamics of social networks, and this information may be used to improve social network alignment. This study finds that these dynamics can reveal more apparent patterns better suited to lining up the social web of things (SWoT). The correlation between the user structure and attributes for each social network must be maintained to combine the binary dynamics and make the original synthetic embedding representation. Finally, the initial embedding of each network is projected to a target subspace as part of the semi-supervised spatial transformation learning process. The Dynamic Social Network Alignment approach outperforms the current mainstream algorithm by 10% in this article's extensive series of trials using real-world datasets. The findings of this study show that this alignment of enormous networks addresses the volume, variety, velocity, and veracity (or 4Vs) of vast networks. To improve the efficacy and resilience of an adversarial network alignment, adversarial learning techniques can be applied. The results show that the model with structure, attribute, and time information performs the best, while the model without attribute information comes in second, the model without time information performs mediocrely, and the model without structure information performs the worst.
  • A Novel Hybrid Optimization Approach for Securing Health Information using Block Chain
    International Journal of Intelligent Systems and Applications in Engineering, 2023
  • Combining Neural Networks to Recognize Offline Digits & Words by Training the Model Using Keras
    Hina Hashmi, Srikanth V
    2023 3rd International Conference on Advancement in Electronics and Communication Engineering Aece 2023, 2023
    The identification of words and numerical characters in an offline setting falls within the realm of word processing and optical character recognition systems. The process of identifying appropriate techniques for extracting features and selecting a classifier can be a challenging undertaking. The present study outlines a methodology for the development of handwritten recognition systems utilizing a neural network classifier. The technique is being assessed through the examination of a dataset sourced from Kaggle, which pertains to the recognition of automobile number plates. The selection of frequently occurring words is performed manually from a repository of vehicles. These words then undergo several stages, including data acquisition, pre-processing, and feature extraction, to enable their recognition.
  • Forecasting diseases that affect plant leaves and moisture levels in the soil using a data mining approach
    Ritu Shree, Rupal Gupta, V. Srikanth
    Multidisciplinary Science Journal, 2023
    The foundation of the global and Indian economies is agriculture. Since agriculture started millions of years ago, many environments, civilizations, and technical developments have fostered and defined the evolution of agricultural technology. In this study, we examine how we may analyze images of plants and soil to better keep tabs on their health, as well as how we can determine how much water each kind of plant needs. Images of the plants and soil are first taken using a digital camera with the necessary resolution. The form and geometric characteristics are extracted from the plant images using the inner distance shape context-based descriptor and geometrical descriptors. The soil images are also used to extract features and color properties. The botanical plant species dictionary is used to identify the plant type using the contour elements of the plant photos. Gradient structured random forest (GS-RF) classification is used to forecast leaf diseases. Principal Component Analysis (PCA) and Hierarchical Gradient Deep Neural Network (HG-DNN) classification techniques are used to determine the causes of a given plant disease based on the characteristics of soil images and plant disease images. The findings are communicated to the growers through text messages sent to their mobile phones on a daily and seasonal basis, along with any potential recommendations for preventative actions.
  • A Cardiovascular Disease Detection System using Machine Learning
    V Srikanth, T R Mahesh
    Proceedings of 5th International Conference on Contemporary Computing and Informatics Ic3i 2022, 2022
    In recent times, the health sector has placed a greater emphasis on data comprehension through the utilization of data mining and collection technology. Multiple design standards indicate that medical practitioners make between 12 and 13% of incorrect prognostications. Therefore, an automated method for disease prediction is required in order to improve the accuracy of health diagnoses and to raise assessments reliability. Many academics have placed an emphasis on accuracy rate throughout the construction of automated techniques. The automated system that was created to forecast heart disease will reduce the burden of computational work and the factors that raise the amount of computational work. The accuracy of the prediction is improved through the employment of the classification models, which retrieves and selects data. The information about heart disease that is readily available to the public yields contradictory outcomes when it is investigated. Learning patterns involves both linear and non-linear examination of the underlying features. The prediction rates can be improved by Support vector regression that is linearly iterated (LlSVR) and classification using stacked monkey optimization (SMO). The computations were performed in MATLAB 2016b, and a number of evaluation techniques were used to assess the outcomes. The suggested model is 98.5 percent accurate, 98.8 percent precise, 99.5 percent recall, and 99.28 percent F-measure. The findings point to the possibility that the anticipated LISVR-SMO will function better than the approaches that are now being used and provide better trading.
  • Fruit fly Optimization with Deep Learning Based Reactive Power Optimization Model for Distributed Systems
    V. Srikanth, Vasanthakumar Natarajan, B. Jegajothi, S.S.L. Durai Arumugam, D. Nageswari
    Proceedings of the International Conference on Electronics and Renewable Systems Icears 2022, 2022
  • Chaotic Whale Optimization based Node Localization Protocol for Wireless Sensor Networks Enabled Indoor Communication
    V. Srikanth, Ranjan Walia, P. John Augustine, Venkatesh R, Jerrin Simla, B. Jegajothi
    Proceedings of the International Conference on Electronics and Renewable Systems Icears 2022, 2022
  • IOT Based Deep Learning framework to Diagnose Breast Cancer over Pathological Clinical Data
    Shweta Singh, V. Srikanth, Sumit Kumar, L. Saravanan, Sheshang Degadwala, Suneet Gupta
    Proceedings of 2nd International Conference on Innovative Practices in Technology and Management Iciptm 2022, 2022
  • Robust Node Localization with Intrusion Detection for Wireless Sensor Networks
    R. Punithavathi, R. Thanga Selvi, R. Latha, G. Kadiravan, V. Srikanth, Neeraj Kumar Shukla
    Intelligent Automation and Soft Computing, 2022
  • Metaheuristic Optimization Enabled Unequal Clustering with Routing Technique
    V. Srikanth, M. Vanitha, M. Maragatharajan, Preetha Marappan, Sathiya Priya S, B. Jegajothi
    Proceedings of the International Conference on Electronics and Renewable Systems Icears 2022, 2022
  • Usage of ML and IoT in Healthcare Diagnose During Pandemic
    Shashi, V. Srikanth, Prarthita Biswas, V. Chinnammal, Supriya Ashok Bhosale, Sheshang Degadwala
    Proceedings of 3rd International Conference on Intelligent Engineering and Management Iciem 2022, 2022

RECENT SCHOLAR PUBLICATIONS

  • An Advanced Internet of Things enabled security system design for Residential Intrusion Detection
    DV Srikanth
    ieee Xplore , 2026
    2026
  • artificial intelligence-Driven Adaptive Testing:A Psychometric approach to personalized learning in computer science education
    DV Srikanth
    Vascular and Endovascular Review Journal 38 (no 9s) , 2025
    2025
  • Sustainable Waste Management through Block chain and Internet of Things Integration in Industrial zones
    DV Srikanth
    International journal of environmental sciences 11 (8) , 2025
    2025
    Citations: 2
  • Block chain based supply chain optimization for eco-enterpreneurs:enhancing transparency and carbon footprint accountability
    DV Srikanth
    International journal of environmental sciences 11 (17s) , 2025
    2025
    Citations: 15
  • AI powered entrepreneurial Ecosystems:A computational model for sustainable start up growth in Green Tech Sectors
    DV Srikanth
    International journal of environmental sciences 11 (17s) , 2025
    2025
  • 5g optimized qos control mechanism for real time data streaming in mobile ad-hoc networks(MANETS)
    V Srikanth
    Journal of environmental Protection and Ecology 26 (3), 1114-1124 , 2025
    2025
    Citations: 22
  • Artificial intelligence based monitoring and forecasting of urban air pollution in smart cities
    DV Srikanth
    International journal of environmental sciences 11 (3) , 2025
    2025
    Citations: 2
  • Development of an electric automation control model using artificial intelligence
    V Srikanth
    IEEE explore , 2024
    2024
    Citations: 16
  • machine learning based analogue circuit design for stage categorization and evolutionary optimization
    V Srikanth
    IEEE explore , 2024
    2024
    Citations: 17
  • Precision offloading in Edge Computing:Leveraging predictive model
    S V
    journal of machine and computing 4 (4), 1079-1091 , 2024
    2024
  • Future navigator: machine learning approaches to career planning
    D Srikanth V
    international journal of innovative research in computer science and … , 2024
    2024
  • The new era of voting using block chain technology
    D Srikanth V
    international journal of innovative research in science, engineering and … , 2024
    2024
  • The future of virtual reality
    D Srikanth V
    international journal of research Publication and reviews 5 (5), PP:. 5789-5792 , 2024
    2024
  • unifying forces: harnessing block chain and artificial intelligence integration fir enhanced innovation
    D Srikanth V
    IJIRCCE 12 (5), P-issn: 2320-9798 , 2024
    2024
  • Leveraging the cloud: a security renaissance for modern businesses
    D Srikanth V
    IJIRCCE 12 (5), e-issn: 2320-9801 , 2024
    2024
  • Psyche in cyberspace: exploring the intersection of mental health and digital realms
    D Srikanth V
    international journal of modernization in engineering technology and science … , 2024
    2024
  • Cloud Quanta : Pioneering the future of quantum computing in the cloud
    D Srikanth V
    international journal of innovative research in science, engineering and … , 2024
    2024
  • AI in Transportation:Implementing AI in Transportation for automate vehicle tracking systems
    D Srikanth V
    international journal of innovative research in science , engineering and … , 2024
    2024
  • Block chain in health data management
    D Srikanth V
    international journal of Innovative research paper in computer and … , 2024
    2024
  • From perception to Prediction:Leveraging explainable AI in self-Driving cars for enhanced passenger trust
    D Srikanth V
    International journal of Innovative research in computer and communication … , 2024
    2024

MOST CITED SCHOLAR PUBLICATIONS

  • ecommerce online security and trust marks
    V srikanth
    international journal of computer engineering and technology 3 (2), 238-255 , 2012
    2012
    Citations: 56
  • Robust node localization with intrusion detection for wireless sensor networks
    V Srikanth
    Intelligent Automation & Soft Computing 33 (1), 143-156 , 2022
    2022
    Citations: 40
  • Chaotic Whale Optimization based Node Localization Protocol for Wireless Sensor Networks Enabled Indoor Communication
    V Srikanth, R Walia, PJ Augustine, J Simla, B Jegajothi
    2022 International Conference on Electronics and Renewable Systems (ICEARS … , 2022
    2022
    Citations: 28
  • IOT Based Deep Learning framework to Diagnose Breast Cancer over Pathological Clinical Data
    S Singh, V Srikanth, S Kumar, L Saravanan, S Degadwala, S Gupta
    2022 2nd International Conference on Innovative Practices in Technology and … , 2022
    2022
    Citations: 25
  • Fruit fly optimization with deep learning based reactive power optimization model for distributed systems
    V Srikanth, V Natarajan, B Jegajothi, SSLD Arumugam, D Nageswari
    2022 International Conference on Electronics and Renewable Systems (ICEARS … , 2022
    2022
    Citations: 24
  • A business review of e-retailing in India
    V Srikanth
    International journal of business research and management 1 (3), 105-121 , 2011
    2011
    Citations: 24
  • 5g optimized qos control mechanism for real time data streaming in mobile ad-hoc networks(MANETS)
    V Srikanth
    Journal of environmental Protection and Ecology 26 (3), 1114-1124 , 2025
    2025
    Citations: 22
  • machine learning based analogue circuit design for stage categorization and evolutionary optimization
    V Srikanth
    IEEE explore , 2024
    2024
    Citations: 17
  • An Insight to Build an E-Commerce Website with OSCommerce
    V Srikanth
    International Journal of Computer Science Issues (IJCSI) 8 (3), 332 , 2011
    2011
    Citations: 17
  • Development of an electric automation control model using artificial intelligence
    V Srikanth
    IEEE explore , 2024
    2024
    Citations: 16
  • Block chain based supply chain optimization for eco-enterpreneurs:enhancing transparency and carbon footprint accountability
    DV Srikanth
    International journal of environmental sciences 11 (17s) , 2025
    2025
    Citations: 15
  • INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY (IJCET)
    TK Das, DK Mahapatra, G Pradhan
    Journal Impact Factor 3 (3), 459-483 , 2012
    2012
    Citations: 5
  • Sustainable Waste Management through Block chain and Internet of Things Integration in Industrial zones
    DV Srikanth
    International journal of environmental sciences 11 (8) , 2025
    2025
    Citations: 2
  • Artificial intelligence based monitoring and forecasting of urban air pollution in smart cities
    DV Srikanth
    International journal of environmental sciences 11 (3) , 2025
    2025
    Citations: 2
  • Usage of ML and IOT in health care diagnose during pandemic
    V Srikanth
    IEEE Explore , 2022
    2022
    Citations: 1
  • An Advanced Internet of Things enabled security system design for Residential Intrusion Detection
    DV Srikanth
    ieee Xplore , 2026
    2026
  • artificial intelligence-Driven Adaptive Testing:A Psychometric approach to personalized learning in computer science education
    DV Srikanth
    Vascular and Endovascular Review Journal 38 (no 9s) , 2025
    2025
  • AI powered entrepreneurial Ecosystems:A computational model for sustainable start up growth in Green Tech Sectors
    DV Srikanth
    International journal of environmental sciences 11 (17s) , 2025
    2025
  • Precision offloading in Edge Computing:Leveraging predictive model
    S V
    journal of machine and computing 4 (4), 1079-1091 , 2024
    2024
  • Future navigator: machine learning approaches to career planning
    D Srikanth V
    international journal of innovative research in computer science and … , 2024
    2024