R. M. Swarna Priya

TL;DR: A deep neural network (DNN) is used to develop effective and efficient IDS in the IoMT environment to classify and predict unforeseen cyberattacks and performs better than the existing machine learning approaches with an increase in accuracy and decreases in time complexity.

TL;DR: Energy Efficient Cloud Based Internet of Everything (EECloudIoE) architecture is proposed in this study, which acts as an initial step in integrating these two wide areas thereby providing valuable services to the end users.

TL;DR: This research paper focuses on developing a prediction model for predicting the life of battery well ahead and alert the technologists so that the monitoring will not be interrupted using Principal Component Analysis (PCA) and Deep Neural Network (DNN).

TL;DR: In this article, the authors provide a thorough overview on integrating federated learning (FL) with industrial IoT in terms of privacy, resource and data management, and discuss the potential of using machine learning, deep learning and blockchain techniques for FL in secure industrial IoT.

TL;DR: The proposed algorithm risk assessment sentiment analysis (RASA) uses the keywords generated from the network to classify the tweets and sentiment score for each location is identified and helps the government to take preventive measures to manage the posteffect of the disaster event in a location.