Kalyanchakravarthi P

@gmrit.edu.in

Assistant Professor ECE
GMR Institute of Technology

https://researchid.co/kalyanecebujji

Scopus Publications

Scholar Citations

Scholar h-index

Scholar i10-index

Scopus Publications

AI Based Reliable and Secure Data Transfer in Wireless Networks
P. Kalyanchakravarthi and Susmitha Das
Springer Nature Switzerland

Anomaly Detection of Smart Grid Equipment Using Machine Learning Applications
Arun Sekar Rajasekaran, P. Kalyanchakravarthi, and Partha Sarathi Subudhi
River Publishers
Many application systems in today’s smart grid network comprise a variety of middleware components, such as vibrating or spinning electrical equipment, data bases, storage, caches, and identification services, among others. Each component is a discrete bundle of physical or virtual computers that will generate a large amount of data in the form of logs and metrics, and failure of these high-vibrating machines will result in the system’s entire shutdown. As a result, the condition monitoring system for this smart grid equipment is more dependable and efficient in predicting the machine’s health ahead of time. To analyze the data and derive any inferences for future analysis and anomaly detection, we’ll need a separate system, which will take longer to handle data given by each component and will demand additional processing resources. As a result, in this chapter, machine learning methods are used to identify abnormalities or condition monitoring for smart grid equipment and machines. Here, we used two separate methods: multivariate statistical analysis by calculating Mob distance and auto encoders, which is an artificial neural network approach. Furthermore, the findings demonstrate that these apps are effective in identifying anomaly ahead of time, i.e. before a few days.

A Novel System Model for Managing Cyber Threat Intelligence
Suresh Dannana, T. Prabakaran, Arun Sekar Rajasekaran, N. Kumareshan, S. Finney Daniel Shadrach, and Kalyanchakravarthi P
IEEE
Cyber threat intelligence (CTI) systems, which collect CTI statistics since publically accessible resources, have been the subject of much study as a means of mitigating the ever-evolving cyber dangers. Due to the ever-increasing sophistication and persistence of cyber attackers, as well as the lightning-fast pace at which cyber assaults develop, quick decision making is now crucial to the sustained security of most companies. As a result, several businesses have started using threat intelligence management systems to better coordinate their defences against cyber threats and those of other companies. Getting a handle on how these platforms should be built, deployed, and utilised requires first knowing how successful they have been in the past. However, a lack of consensus on what aspects affect the performance of threat intelligence management systems exists between academia and industry. We used a review entrenched methodology to gather data from 152 security experts in order to empirically evaluate the concerns. Then, we determined a few variables that are critical to the effectiveness of management platform inside an organisation.

IOT based Smart solution for Traffic congestion at Metro Cities
T. V. Janardhana Rao, R. Arun Sekar, B. Drakshyani, P Kalyan Chakravarthi, N. Kumareshan, and S. P. Karthi
IEEE
The major challenge in metro cities is to handle the vehicle traffic as well as pedestrian traffic at major locations. Over a day nearly 20% time is spend in our work or personal time to over come the delay at traffic to reach the destination. Traffic management systems have been the subject of much study, but because of the blending of technologies like the Internet of Things (IoT) and artificial intelligence, research on intelligent traffic monitoring is currently ongoing (AI). By integrating these technologies, we can improve decision-making processes and promote urban development. The management of urban and highway traffic is the primary emphasis of the available traffic prediction techniques, and there are few studies that have concentrated on collector roads and closed campuses. Furthermore, when the consumers are not using any smart gadgets, it is difficult to reach out to the public and create active relationships to help them make decisions. In order to gather, analyse, and store real-time traffic data for such a situation, this study suggests an IoT-based system paradigm. The goal is to increase mobility by using roadside messaging devices to provide real-time traffic reports on traffic congestion and unexpected traffic events. These time-saving alerts will benefit residents, particularly during rush hour. Also disseminated by the system are the administrative authorities' traffic updates. The results of the trials demonstrate high accuracy in vehicle recognition and a low relative error in road occupancy prediction. A prototype is used to assess the viability of the model. The research project, which is financed by Omani, is looking at Real-Time Feedback for Adaptive Traffic Signals.

IoT-based smart energy meter for smart grids
P Kalyan Chakravarthi, D. Yuvaraj, and V Venkataramanan
IEEE
In the development of an intelligent grid in the energy system,energy efficiency is critical. As a result, proper power usage monitoring and control is essential for a smart grid. The existing power meter system has a number of flaws,one of which being the lack of a full duplex connection. To overcome this, an intelligent meter which works on IOT is proposed in this work. Instead of calculating power consumption with meter reading alone, can manage and calculate the consumption by uploading through cloud. Further the buyer can examine it. As a result, consumer power analysis becomes considerably easier and more controllable. This programme also aids in the detection of energy fraud. As a result, it will initiate a new step towards digital india by taking smart meters in to the real time power consumption calculations.

Optical character recognition technique algorithms

FPGA based architecture for realtime edge detection
P. Kalyan Chakravathi, K Vijaya Kumar, P. Devi Pradeep, and D Suresh
IEEE
Edge Detection is one of the basic characteristics of the image. It is an important basis for the field of image analysis such as image segmentation, target area identification, extraction and other regional forms. The edge detection operators such as canny, sobel, prewitt operators detects the wide range of edges in image. These operators apply the convolution operation at each pixel to have gradient image. FPGA (Field programmable gate array) is fine grained reconfigurable architecture that can virtually perform any processing operation at a hardware level and satisfying real-time requirements for image processing. In FPGA hardware resources there are rich internal multipliers. The design process can directly call these resources to operate, so it is easy to implement complex convolution. FPGA based architecture for real time edge detection presents a new flexible parameterizable architecture which reduces latency and memory requirements. This architecture contains neighborhood extractors and threshold operators that can be parameterized at runtime. The algorithm simplifications reduces mathematical complexity, memory requirements, and latency without losing reliability. This architecture has clear advantage in terms of power consumption and maintain a reliable performance with noisy images.

Data-path selection mechanism based on physical layer impairments for wdm network
Santos Kumar Das, Chakravarthi P. Kalyan, and Sarat Kumar Patra
Inderscience Publishers
In optical networks, Physical Layer Impairments (PLIs) incurred by non-ideal optical transmission media accumulate along the optical path. The overall effect of PLIs determines the feasibility of the light-paths. It is important to understand the process that provide PLI information to the central manager and use this information efficiently to compute feasible routes and wavelengths. Based on the PLI impairments like fibre attenuation, Chromatic Dispersion (CD) and Polarisation Mode Dispersion (PMD), which reflects the Quality of service factors (Q-Factor); a centralised PLI-based routing algorithm is proposed for the selection of data-paths.

RECENT SCHOLAR PUBLICATIONS

Harnessing Solar Energy for a Sustainable Future By Using MyRIO and LabVIEW
BA Kumar, PK Chakravarthi, BR Ratnala, AR Darbha, S Gunda, M Botsa
2024 International Conference on Computational Intelligence for Green and 2024

AI Based Reliable and Secure Data Transfer in Wireless Networks
P Kalyanchakravarthi, S Das
International Conference on Broadband Communications, Networks and Systems 2024

Study on biometric authentication systems, challenges and future trends: a review
GYR P.Kalyanchakravarthi,K.Ravikumar
Shodhasamhita : Journal of Fundamental & Comparative Research 9 (1), 152-158 2023

A novel system model for managing cyber threat intelligence
S Dannana, T Prabakaran, AS Rajasekaran, N Kumareshan, ...
2022 IEEE 2nd Mysore sub section international conference (MysuruCon), 1-5 2022

IOT based Smart solution for Traffic congestion at Metro Cities
TVJ Rao, RA Sekar, B Drakshyani, PK Chakravarthi, N Kumareshan, ...
2022 International Conference on Innovative Computing, Intelligent 2022

Anomaly detection of smart grid equipment using machine learning applications
AS Rajasekaran, P Kalyanchakravarthi, PS Subudhi
Distributed Generation & Alternative Energy Journal, 1721-1738 2022

IoT–based smart energy meter for smart grids
PK Chakravarthi, D Yuvaraj, V Venkataramanan
2022 6th international conference on devices, circuits and systems (ICDCS 2022

Virtual technology for smart education
Kalyanchakravarthi, P., Varaprasad, D. Y., Rao, T. V. J., & Suresh
International Journal of Health Sciences 6 (s2), 5457-5465 2022

Enhancement of Old Images and Documents by Hybrid Binarization Techniques
PKR P Kalyanchakravarthi
International Research Journal of Engineering and Technology (IRJET) 6 (6 2019

OPTICAL CHARACTER RECOGNITION TECHNIQUE ALGORITHMS.
NV Rao, A Sastry, ASN Chakravarthy, P Kalyanchakravarthi
Journal of Theoretical & Applied Information Technology 83 (2) 2016

FPGA based architecture for realtime edge detection
PK Chakravathi, KV Kumar, PD Pradeep, D Suresh
2015 Global Conference on Communication Technologies (GCCT), 12-17 2015

Design and Development of Controller Software for MAS Receiver Using Embedded System
K Haritha, PMK Prasad, M Jawaharlal, PK Chakravathi
Journal of Innovation in Computer Science and Engineering 5 (1), 48-52 2015

CENTRALLIZED WIRELESS POWER DISTRIBUTION
DS Kalyan Chakravarthi P , K Vijayakumar
Journal of Advances in Science and Technology 1 (1), 14-23 2015

Improved SNR for High data rate transmission
KVI D Suresh,P Kalyan Chakravarthi
International Journal of Trend in Research and Development 2 (1), 1-5 2014

Optimized Wireless Video Transmission Protocol
PKC K Prabhakara Rao,Dr. P V Sridevi
International Journal of Electronics & Communication Technology (IJECT) 3 (3 2012

Data-path selection mechanism based on physical layer impairments for WDM network
SKP Santos kumar Das, P Kalyan Chakravarthi
International Journal of Signal and Imaging Systems Engineering 5 (4), 239-245 2012

Physical Layer Impairments Aware Data-Path Selection (PLIADS) in WDM Network
SK Das, SK Patra
2011

Physical Layer Impairments based Data-path Routing in WDM Network
SK Das, SK Patra
2011

2 Problem Statement
AS Rajasekaran, P Kalyanchakravarthi, PS Subudhi

DESIGN OF DOUBLE PRECISION FLOATING POINT MULTIPLICATION ALGORITHM WITH VECTOR SUPPORT
TG Rao, PD Pradeep, P Kalyanchakravarthi

MOST CITED SCHOLAR PUBLICATIONS

OPTICAL CHARACTER RECOGNITION TECHNIQUE ALGORITHMS.
NV Rao, A Sastry, ASN Chakravarthy, P Kalyanchakravarthi
Journal of Theoretical & Applied Information Technology 83 (2) 2016
Citations: 94

IoT–based smart energy meter for smart grids
PK Chakravarthi, D Yuvaraj, V Venkataramanan
2022 6th international conference on devices, circuits and systems (ICDCS 2022
Citations: 28

A novel system model for managing cyber threat intelligence
S Dannana, T Prabakaran, AS Rajasekaran, N Kumareshan, ...
2022 IEEE 2nd Mysore sub section international conference (MysuruCon), 1-5 2022
Citations: 8

Anomaly detection of smart grid equipment using machine learning applications
AS Rajasekaran, P Kalyanchakravarthi, PS Subudhi
Distributed Generation & Alternative Energy Journal, 1721-1738 2022
Citations: 5

FPGA based architecture for realtime edge detection
PK Chakravathi, KV Kumar, PD Pradeep, D Suresh
2015 Global Conference on Communication Technologies (GCCT), 12-17 2015
Citations: 4