A5013228021- IoT and Edge/Fog Computing
- Context-Aware Activity Recognition Systems
- Artificial Intelligence in Healthcare
- Machine Learning in Healthcare
- COVID-19 diagnosis using AI
- Blockchain Technology Applications and Security
- Remote Sensing in Agriculture
- Smart Agriculture and AI
- Digital Transformation in Industry
- IoT-based Smart Home Systems
- Cardiovascular Health and Risk Factors
- AI and Big Data Applications
- Non-Invasive Vital Sign Monitoring
- Quantum Computing Algorithms and Architecture
- Spectroscopy and Chemometric Analyses
- Municipal Solid Waste Management
- Flexible and Reconfigurable Manufacturing Systems
- Healthcare and Environmental Waste Management
- Recycling and Waste Management Techniques
- Date Palm Research Studies
- Mobile Crowdsensing and Crowdsourcing
- Smart Grid Security and Resilience
- Sepsis Diagnosis and Treatment
- Genomics and Phylogenetic Studies
- Internet of Things and AI
Maharshi Dayanand Saraswati University
2023
REVA University
2023
Institute of Management Technology
2021
Indira Gandhi Delhi Technical University for Women
2017
Heart failure is a frequent cause of hospitalization and readmission because the severity disease. Researchers explored using Machine Learning (ML) algorithms to forecast whether heart patients must be readmitted hospital. This study examines ML that use data from electronic health records hospital readmissions for with failure. We will assess accuracy, precision, recall, F1-score logistic regression, decision trees, random forests, Support Vector Machines (SVM), artificial neural networks....
A rapid rise in inhabitants across the globe has led to inadmissible management of waste various countries, giving health issues and environmental pollution. The waste-collecting trucks collect just once or twice seven days. Due improper collection practices, dustbin is spread on streets. Thus, defeat this situation, an efficient solution for smart effective using machine learning (ML) Internet Things (IoT) proposed paper. In solution, authors have used Arduino UNO microcontroller,...
The Internet of Things (IoT) will disrupt medicine the most. Healthcare uses edge computing, deep learning, IoT, and machine learning for real-time analytics, monitoring, data analysis. This research evaluate, expand, overcome difficulties, improve IoT-based healthcare systems. article explores IoT computing's benefits drawbacks. Edge computing can delivery, cost, results, according to authors. Researchers offer wearable sensors, smart health gateways, early warning score artificial...
Cardiovascular Disease (CVD) affects deaths and hospitalisations. Clinical data analytics struggles to predict heart disease survival. This report compares machine learning-based cardiovascular prediction studies. The authors use a Kaggle dataset of 70,000 records 16 features show SMOTE model with hyperparameter-optimized classifiers. Random Forest outperforms KNN 13 elements in prediction. Naive Bayes SVM on complete feature sets. proposed achieves 86% accuracy, the optimised technique...
Early sepsis detection improves patient outcomes and care. This research provides a Machine Learning (ML) system for hospitalized detection. Gradient boosting, an ensemble learning method, analyses data to detect early. A comprehensive electronic health record database, MIMIC-III, was used design test the algorithm. The algorithm's accuracy, precision, recall, F1 score, ROC AUC were measured. proposed approach more accurate than traditional models. It accurately predicted patients aid...
The healthcare industry faces immense pressure due to increasing acute diseases, emergencies, and rising costs. Developing an intelligent system can address these challenges by leveraging recent technological advancements such as Artificial Intelligence (AI), the Internet of Things (IoT), cloud computing. Intelligent systems help professionals make better decisions, provide high-quality patient care, monitor activities remotely. However, implementing presents data privacy security concerns....
This research examines the fundamental reasons chatbots exist, their functions, and challenges. The applicability consistency of analysis are improved by utilization quantitative data that is gathered in real-time. also compares past techniques creating with modern ones, highlighting how far have progressed from being able to merely engage scripted scenarios advanced skills they today thanks end-to-end neural networks. Microsoft Research carried out published it journal Science. first...
Fall related injuries are a major cause of severe health damage and immobility in elderly population. Often the treatment fall associated is delayed due to long lie periods after because absence or acknowledgement incident. This leads large costs further long-term care monitoring costs. Hence there need an automated, low-cost small size ubiquitous detection system such that incidents can be acknowledged time person get immediate medical treatment. paper explains design accelerometer-based...
The focus of this research is on using bioacoustics for frequency-based pest deterrence in sustainable agriculture, with the Fourier transform as driving force. critical need new and improved methods control agricultural settings addressed. This study, which makes use cutting-edge technology, investigates how Transform might be used a useful instrument fight against pests. algorithm control; it's based bioacoustic analysis. By "Insect Bioacoustic Signals (IBS) Dataset," study reveals...