Personalized nutrition in healthcare using IoT for tailored dietary solutions K. Priyadharshini, K. Dhivya, M. S. Kamalesh, S. J. Suji Prasad, Deeban Chakravarthy, M. Sudhakar Integrating Artificial Intelligence into the Energy Sector, 2025 Personalized nutrition is precision health that forms personalized diets based on the genetic, environmental, and lifestyle characteristics of an individual. It further improves with the integration of Internet of Things in collecting, analyzing, and feedback mechanisms in real time, enhancing the precision and adaptation of nutritional interventions: glucose levels, body composition, and diet are monitored with wearables, smart appliances, and connected health systems. The data, thus processed, is then channeled through AI algorithms to derive personal recommendations that are tailored to the health goals, medical conditions, and preferences of the individual. Healthcare providers can use the IoT in personalized nutrition to gain more effective, sustainable diets that result in better patient outcomes for chronic diseases, weight management, and well-being. The chapter analyses technological advancements, challenges, and potential of IoT-enabled personalized nutrition in transforming modern healthcare and fostering a more customized approach toward diet-based interventions.
Cardiac Condition Anticipation and Prognostication via Integrated WOA and Bagging-GBDT International Journal of Intelligent Systems and Applications in Engineering, 2024
Parkinson's Disease Diagnosis using Neutral Matrix and Machine Learning Priyanshu Grover, Suryaveer Singh Kadyan, Deeban Chakravarthy 2024 International Conference on Advances in Modern Age Technologies for Health and Engineering Science Amathe 2024, 2024 This research explores the potential of the Neutral Matrix (NM) to diagnose Parkinson's disease (PD). It builds upon current diagnostic methods by incorporating imaging, genetic markers, and advanced clinical data analysis. The findings highlight the effectiveness of NM in achieving accurate and consistent disease identification, potentially improving patient satisfaction and enabling early intervention. This study emphasizes the significance of NM as a contributor to the ongoing development of PD diagnostic strategies. By enhancing the accuracy and reliability of diagnosis, NM offers valuable data-driven insights for timely identification of this debilitating condition. Ultimately, this research paves the way for improved PD diagnosis and potentially improved quality of life for affected individuals, leveraging the valuable resource of NM. Additionally, the study delves into the application of game-based assessments in PD diagnosis. By demonstrating the potential of a data-driven approach for accurate and early PD detection, the research contributes significantly to the scientific field. The methodology, trends, operational techniques, results, discussion, and implications are outlined in detail within the study.
Systematic Review of Emerging Deep Learning approaches for Crop Diseases detection V. Vasuki Rohinidevi, Deeban Chakravarthy V, S. Prem Kumar Deepak Proceedings of International Conference on Circuit Power and Computing Technologies Iccpct 2024, 2024 Deep learning, a branch of artificial intelligence, has drawn interest from the academic and corporate realms, especially in areas like speech and image analysis, video processing, and natural language processing. Its use in agricultural plant protection has expanded to include the diagnosis and evaluation of pests and plant diseases. In this situation, there are several benefits to using deep learning. It removes the biases related to manually chosen pathogen properties, improves objectivity when determining disease characteristics, and hastens the advancement of contemporary technology. In order to diagnose agricultural leaf illnesses, this study explores the most recent developments in deep learning methods, including CNN, DENSNET, InceptionV3, VGG16, Resnet50, and MobileNet, in addition to a variety of sensors. This project aims to aid scientists in the field by tackling challenges in merging deep learning and cutting-edge imaging tools to enhance illness identification. It addresses current trends and barriers, shedding light on unresolved issues and paving the way for further research. By clarifying persistent problems and posing new questions, it fosters progress and innovation in the field of medical imaging and diagnosis.
Cipher - Intelligent Surveillance System Devansh Singh, Aryan Chaturvedi, Deeban Chakravarthy 2024 International Conference on Recent Innovation in Smart and Sustainable Technology Icrisst 2024, 2024 This study introduces an Intelligent Surveillance System specifically developed for the purpose of generating captions for images in real-time. The system makes use of sophisticated computer vision and natural language processing methods. The ResNet-101 pre-trained model is used to extract high-level features through a two-step picture encoding method. The caption generation model utilizes LSTM and incorporates an attention mechanism to dynamically prioritize relevant image regions while generating text. Integrating Beam Search improves the quality and variety of captions. This solution greatly improves the understanding of security specialists and analysts by automating the analysis of visual data and providing detailed written explanations. The system's proficiency in producing precise, contextually suitable, and eloquent captions has been proven through meticulous assessments on a wide range of datasets. The results highlight the effectiveness of the system and connecting the fields of computer vision and natural language processing in the area of intelligent surveillance.
A Machine Learning Method for Detecting Behavior-Based Malware Javvaji Venkatarao, V. Deeban Chakravarthy, Singaraju Ramya, V. Siva Prasad, Srikanth Cherukuvada, Annaram Soujanya Proceedings of the 5th International Conference on Inventive Research in Computing Applications Icirca 2023, 2023 While malware has posed a danger to businesses for years, advances in malware detection have lagged. Malware can cause damage to a system by starting unneeded services, which increases the system's workload and prevents it from operating smoothly. Malware detection can be done in one of two ways: the traditional signature-based approach or the more modern behavior-based approach. When malware is activated on a system, it conducts specific actions, such as launching malicious OS services or downloading malicious files from the web, that characterize its behaviour. The described technique detects malicious software based on its actions. The suggested model in this paper combines Support Vector Machine and Principal Component Analysis.
Load balancing in data centers using SDN controllers International Journal of Advanced Science and Technology, 2020
Detection and prevention of ddos attacks in software defined networking International Journal of Advanced Science and Technology, 2020
Dynamically generating range of clustered controllers using kernel density estimation for load balancing in a multi-controller software defined networking International Journal of Advanced Science and Technology, 2020
Building fault tolerant, scalable and high speed multicontroller environment in software defined networking International Journal of Advanced Science and Technology, 2020
A survey on security in software-defined-networking International Journal of Recent Technology and Engineering, 2019
Performance of several load balancing techniques and algorithms in cloud environment International Journal of Innovative Technology and Exploring Engineering, 2019
A survey paper on dynamic load balancing in software defined networking International Journal of Recent Technology and Engineering, 2019
A survey on analysis of network traffic in data centers using controllers in SDN International Journal of Recent Technology and Engineering, 2019
Dynamic load balacing using Queuing Interface System Arpn Journal of Engineering and Applied Sciences, 2017
SDN enabled packet based load-balancing (PLB) technique in data center networks Arpn Journal of Engineering and Applied Sciences, 2017
A survey on approach for improving anti-phishing security using VSS scheme in visual cryptography International Journal of Pharmacy and Technology, 2016
Retraction Note: OTP-ER: an ordered transmission paradigm for effective routing in IoT based wireless sensor networks CJ Kumar, VD Chakravarthy, K Ramana, PK Reddy Maddikunta, Q Xin, ... Optical and Quantum Electronics 56 (9), 1517 , 2024 2024
Binary classification of brain tumor using machine learning algorithms S Dua, VD Chakravarthy, I Sharma AIP Conference Proceedings 3075 (1), 020181 , 2024 2024 Citations: 1
Custom model for skin cancer detection algorithm for non-caucasian dataset S Khare, VD Chakravarthy, KS Chauhan AIP Conference Proceedings 3075 (1), 020191 , 2024 2024 Citations: 2
A machine learning method for detecting behavior-based malware J Venkatarao, VD Chakravarthy, S Ramya, VS Prasad, S Cherukuvada, ... 2023 5th International Conference on Inventive Research in Computing … , 2023 2023 Citations: 2
Stock price prediction by normalizing LSTM and GRU models J Venkatarao, DVD Chakravarthy, S Meadi Journal of Survey in Fisheries Sciences 10 (1S), 5326-5332 , 2023 2023 Citations: 5
Cyberbullying detection and hate speech identification using machine learning techniques T Agrawal, VD Chakravarthy 2022 Second International Conference on Interdisciplinary Cyber Physical … , 2022 2022 Citations: 14
STRATIFIED COGNITIVE POWER ALLOCATION SPECIFICATION FOR UE AND BS IN 5G. CR Babu, VD Chakravarthy, R Jeya International Journal of Early Childhood Special Education 14 (3) , 2022 2022
THE TUNNEL-POTENTIAL COVID-19 THREAT DETECTOR USING SMART GATE BASED IOT. DH Reddy, VD Chakravarthy, A Shukla International Journal of Early Childhood Special Education 14 (3) , 2022 2022
A novel software‐defined networking approach for load balancing in data center networks VD Chakravarthy, B Amutha International journal of communication systems 35 (2), e4213 , 2022 2022 Citations: 33
Unified Flow Based Approach in Software-Defined Networks VD Chakravarthy, DS Chandra, SSS Pavan ICT Systems and Sustainability: Proceedings of ICT4SD 2021, Volume 1, 581-589 , 2022 2022
Fuzzy‐Based Approach for Clustering Data with Multivalued Features LNC Prakash K, M Vimaladevi, VD Chakravarthy, GS Narayana, ... Wireless Communications and Mobile Computing 2022 (1), 3818107 , 2022 2022 Citations: 2
WITHDRAWN: Personal finance transaction index scoring using machine learning model MR Kumar, VD Chakravarthy, TN Ranganatham, K Ramana Materials Today: Proceedings , 2021 2021 Citations: 4
Research Article An Efficient Routing Approach to Maximize the Lifetime of IoT-Based Wireless Sensor Networks in 5G and Beyond C Jothikumar, K Ramana, VD Chakravarthy, S Singh, IH Ra 2021
PoC Design: A Methodology for Proof‐of‐Concept (PoC) Development on Internet of Things Connected Dynamic Environments K Prasanna, K Ramana, G Dhiman, S Kautish, VD Chakravarthy Security and Communication Networks 2021 (1), 7185827 , 2021 2021 Citations: 30
An Efficient Routing Approach to Maximize the Lifetime of IoT‐Based Wireless Sensor Networks in 5G and Beyond C Jothikumar, K Ramana, VD Chakravarthy, S Singh, IH Ra Mobile Information Systems 2021 (1), 9160516 , 2021 2021 Citations: 67
Software-defined network assisted packet scheduling method for load balancing in mobile user concentrated cloud VD Chakravarthy, B Amutha Computer Communications 150, 144-149 , 2020 2020 Citations: 11
Path based load balancing for data center networks using SDN VD Chakravarthy, B Amutha International Journal of Electrical and Computer Engineering (IJECE) 9 (4 … , 2019 2019 Citations: 24
Techniques for optimizing power utilization in data center network architectures: A survey report VD Chakravarthy, V Nagarajan Indian Journal of Science and Technology 9 (37) , 2016 2016 Citations: 2
HPCA: a node selection and scheduling method for Hadoop MapReduce GK Archana, VD Chakravarthy 2015 International Conference on Computing and Communications Technologies … , 2015 2015 Citations: 7
Artifical Bee Colony (ABC) Algorithm with ECDH Algorithm for Finding Optimal Path and Secure Data Transfer V Deeban Chakravarthy, S Sivarajan, N Gayathiri Int J Sci Eng Res 5 (3), 436-439 , 2014 2014 Citations: 3
MOST CITED SCHOLAR PUBLICATIONS
An Efficient Routing Approach to Maximize the Lifetime of IoT‐Based Wireless Sensor Networks in 5G and Beyond C Jothikumar, K Ramana, VD Chakravarthy, S Singh, IH Ra Mobile Information Systems 2021 (1), 9160516 , 2021 2021 Citations: 67
A novel software‐defined networking approach for load balancing in data center networks VD Chakravarthy, B Amutha International journal of communication systems 35 (2), e4213 , 2022 2022 Citations: 33
PoC Design: A Methodology for Proof‐of‐Concept (PoC) Development on Internet of Things Connected Dynamic Environments K Prasanna, K Ramana, G Dhiman, S Kautish, VD Chakravarthy Security and Communication Networks 2021 (1), 7185827 , 2021 2021 Citations: 30
Path based load balancing for data center networks using SDN VD Chakravarthy, B Amutha International Journal of Electrical and Computer Engineering (IJECE) 9 (4 … , 2019 2019 Citations: 24
Cyberbullying detection and hate speech identification using machine learning techniques T Agrawal, VD Chakravarthy 2022 Second International Conference on Interdisciplinary Cyber Physical … , 2022 2022 Citations: 14
Software-defined network assisted packet scheduling method for load balancing in mobile user concentrated cloud VD Chakravarthy, B Amutha Computer Communications 150, 144-149 , 2020 2020 Citations: 11
A Neighbor coverage based probabilistic rebroadcast for reducing routing overhead in mobile ad hoc networks VD Chakravarthy, VD Renga International Journal of Emerging Technology and Advanced Engineering 3 (1 … , 2013 2013 Citations: 8
HPCA: a node selection and scheduling method for Hadoop MapReduce GK Archana, VD Chakravarthy 2015 International Conference on Computing and Communications Technologies … , 2015 2015 Citations: 7
Stock price prediction by normalizing LSTM and GRU models J Venkatarao, DVD Chakravarthy, S Meadi Journal of Survey in Fisheries Sciences 10 (1S), 5326-5332 , 2023 2023 Citations: 5
WITHDRAWN: Personal finance transaction index scoring using machine learning model MR Kumar, VD Chakravarthy, TN Ranganatham, K Ramana Materials Today: Proceedings , 2021 2021 Citations: 4
Artifical Bee Colony (ABC) Algorithm with ECDH Algorithm for Finding Optimal Path and Secure Data Transfer V Deeban Chakravarthy, S Sivarajan, N Gayathiri Int J Sci Eng Res 5 (3), 436-439 , 2014 2014 Citations: 3
Custom model for skin cancer detection algorithm for non-caucasian dataset S Khare, VD Chakravarthy, KS Chauhan AIP Conference Proceedings 3075 (1), 020191 , 2024 2024 Citations: 2
A machine learning method for detecting behavior-based malware J Venkatarao, VD Chakravarthy, S Ramya, VS Prasad, S Cherukuvada, ... 2023 5th International Conference on Inventive Research in Computing … , 2023 2023 Citations: 2
Fuzzy‐Based Approach for Clustering Data with Multivalued Features LNC Prakash K, M Vimaladevi, VD Chakravarthy, GS Narayana, ... Wireless Communications and Mobile Computing 2022 (1), 3818107 , 2022 2022 Citations: 2
Techniques for optimizing power utilization in data center network architectures: A survey report VD Chakravarthy, V Nagarajan Indian Journal of Science and Technology 9 (37) , 2016 2016 Citations: 2
Binary classification of brain tumor using machine learning algorithms S Dua, VD Chakravarthy, I Sharma AIP Conference Proceedings 3075 (1), 020181 , 2024 2024 Citations: 1
Retraction Note: OTP-ER: an ordered transmission paradigm for effective routing in IoT based wireless sensor networks CJ Kumar, VD Chakravarthy, K Ramana, PK Reddy Maddikunta, Q Xin, ... Optical and Quantum Electronics 56 (9), 1517 , 2024 2024
STRATIFIED COGNITIVE POWER ALLOCATION SPECIFICATION FOR UE AND BS IN 5G. CR Babu, VD Chakravarthy, R Jeya International Journal of Early Childhood Special Education 14 (3) , 2022 2022
THE TUNNEL-POTENTIAL COVID-19 THREAT DETECTOR USING SMART GATE BASED IOT. DH Reddy, VD Chakravarthy, A Shukla International Journal of Early Childhood Special Education 14 (3) , 2022 2022
Unified Flow Based Approach in Software-Defined Networks VD Chakravarthy, DS Chandra, SSS Pavan ICT Systems and Sustainability: Proceedings of ICT4SD 2021, Volume 1, 581-589 , 2022 2022
