B
B. Prabadevi
Researcher at VIT University
Publications - 30
Citations - 848
B. Prabadevi is an academic researcher from VIT University. The author has contributed to research in topics: Computer science & Smart grid. The author has an hindex of 6, co-authored 25 publications receiving 180 citations.
Papers
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Journal ArticleDOI
Industry 5.0: A survey on enabling technologies and potential applications
Praveen Kumar Reddy Maddikunta,Quoc-Viet Pham,B. Prabadevi,N. Deepa,Kapal Dev,Thippa Reddy Gadekallu,Rukhsana Ruby,Madhusanka Liyanage +7 more
TL;DR: This paper aims to provide a survey-based tutorial on potential applications and supporting technologies of Industry 5.0 from the perspective of different industry practitioners and researchers.
Posted Content
A Survey on Blockchain for Big Data: Approaches, Opportunities, and Future Directions.
N. Deepa,Quoc-Viet Pham,Dinh C. Nguyen,Sweta Bhattacharya,B. Prabadevi,Thippa Reddy Gadekallu,Praveen Kumar Reddy Maddikunta,Fang Fang,Pubudu N. Pathirana +8 more
TL;DR: A comprehensive survey on blockchain for big data, focusing on up-to-date approaches, opportunities, and future directions is provided, including blockchain for secure big data acquisition, data storage, data analytics, and data privacy preservation.
Journal ArticleDOI
An AI?based intelligent system for healthcare analysis using Ridge?Adaline Stochastic Gradient Descent Classifier
N. Deepa,B. Prabadevi,Praveen Kumar Reddy Maddikunta,Thippa Reddy Gadekallu,Thar Baker,M. Ajmal Khan,Usman Tariq +6 more
TL;DR: The proposed scheme RASGD improves the regularization of the classification model by using weight decay methods, namely least absolute shrinkage and selection operator and ridge regression methods, and attains an accuracy of 92%, which is better than the other selected classifiers.
Journal ArticleDOI
Comparative analysis of machine learning algorithms for prediction of smart grid stability
Ali Kashif Bashir,Suleman Khan,B. Prabadevi,N. Deepa,Waleed S. Alnumay,Thippa Reddy Gadekallu,Praveen Kumar Reddy Maddikunta +6 more
TL;DR: In this article, state-of-the-art machine learning algorithms, namely Support Vector Machines (SVM), KNN, Logistic Regression, Naive Bayes, Neural Networks, and Decision Tree classifier, have been deployed for predicting the stability of the smart grid.
Journal ArticleDOI
Toward Blockchain for Edge-of-Things: A New Paradigm, Opportunities, and Future Directions
B. Prabadevi,N. Deepa,Quoc-Viet Pham,Dinh C. Nguyen,Praveen Kumar Reddy M,Thippa Reddy G,Pubudu N. Pathirana,Octavia A. Dobre +7 more
TL;DR: In this paper, a novel edge-of-things (BEoT) architecture for supporting industrial applications under the management of blockchain at the network edge in a wide range of IoT use cases such as smart home, smart healthcare, smart grid, and smart transportation is presented.