In the realm of analyzing human emotions through Artificial Intelligence (AI), a myriad of
challenges persist. From the intricate nuances of emotional subtleties to the broader …

With employing the Internet of Things (IoT) sensors and modern-day machine learning
algorithms, this study presents a modern inquiry at the intersection of healthcare and era …

In this research, a detailed investigation of emotion was carried out using a variety of
advanced metrics, such as fidelity, inclusivity, F1-score, presence, presence ratio, as well as …

The effective interpretation and response to infant crying signals are imperative for ensuring
infant well-being. Manual interpretation of these signals can be challenging, leading to …

Present research is focused on consideration of emotional data. In order to deal with such
objective, EEG technique has been applied. Electroencephalography (EEG) is a technique …

Breast cancer is a major worldwide health concern, and patient outcomes are significantly
impacted by early detection and accurate prognosis. In this study, we present an integrated …

In the context of online grocery shopping, this research explores the potential applications of
machine learning models for improving and predicting customer behavior. Using a large …

This study analyzes the effectiveness of machine learning models in the classification of
cervical cancer using a dataset of 900 cancer and 200 non-cancer images gathered from …

The IoT-based health monitoring system has transformed healthcare by enabling seamless
real-time tracking of vital health parameters. Using affordable and low-power sensors, it …

BBMonitor is a smart baby monitoring system that combines the IoT with AI in order to offer a
feature-complete system to the modern parent, tailored to the ever-growing needs of both …