Related papers: An AI-Based System Utilizing IoT-Enabled Ambient S…
Some elderly care homes attempt to remedy the shortage of skilled caregivers and provide long-term care for the elderly residents, by enhancing the management of the care support system with the aid of smart devices such as mobile phones…
As elderly population increases, portion of dementia patients becomes larger. Thus social cost of caring dementia patients has been a major concern to many nations. This article introduces a dementia assistive system operated by various…
The need for reducing our energy consumption footprint and the increasing number of electric devices in today's homes is calling for new solutions that allow users to efficiently manage their energy consumption. Real-time feedback at device…
Cognitive impairment has become epidemic in older adult population. The recent advent of tiny wearable and ambient devices, a.k.a Internet of Things (IoT) provides ample platforms for continuous functional and cognitive health assessment of…
Activity recognition is the ability to identify and recognize the action or goals of the agent. The agent can be any object or entity that performs action that has end goals. The agents can be a single agent performing the action or group…
We need open platforms driven by specialists, in which queries can be created and collected for long periods and the diagnosis made, based on a rigorous clinical follow-up. In this work, we developed a multi-language robot interface helping…
Researchers in pervasive computing have worked for decades on sensor-based human activity recognition (HAR). Among the digital health applications, the recognition of activities of daily living (ADL) in smart home environments enables the…
Reliable forecasting of renewable energy generation is a foundational requirement for grid stability energy trading battery scheduling and carbon aware operational planning Solar and wind resources are inherently intermittent their output…
Chronic diseases have become the leading cause of death worldwide, a challenge intensified by strained medical resources and an aging population. Individually, patients often struggle to interpret early signs of deterioration or maintain…
Evaluating the surroundings to gain understanding, frame perspectives, and anticipate behavioral reactions is an inherent human trait. However, these continuous encounters are diverse and complex, posing challenges to their study and…
Human Activity Recognition (HAR) using Inertial Measurement Unit (IMU) sensors is a cornerstone of mobile health, smart environments, and human-computer interaction. However, current deep learning-based HAR models often struggle with heavy…
Predicting human behavior in shared environments is crucial for safe and efficient human-robot interaction. Traditional data-driven methods to that end are pre-trained on domain-specific datasets, activity types, and prediction horizons. In…
Recently, a wide range of smart devices are deployed in a variety of environments to improve the quality of human life. One of the important IoT-based applications is smart homes for healthcare, especially for elders. IoT-based smart homes…
Digital reminder systems are widely used in dementia care to support everyday tasks, but they are typically designed for one-way prompting rather than helping caregivers interpret engagement over time. We present Remindful, a…
This paper introduces an integrated system designed to enhance the explainability of fault diagnostics in complex systems, such as nuclear power plants, where operator understanding is critical for informed decision-making. By combining a…
This paper presents an interdisciplinary PhD project using a humanoid robot to encourage interactive activities for people with dementia living in two aged care facilities. The aim of the project was to develop software and use technologies…
This paper introduces a novel approach to creating adaptive language agents by integrating active inference with large language models (LLMs). While LLMs demonstrate remarkable capabilities, their reliance on static prompts limits…
Smartwatches are increasingly being used to recognize human daily life activities. These devices may employ different kind of machine learning (ML) solutions. One of such ML models is Gradient Boosting Machine (GBM) which has shown an…
Eye-tracking data reveals valuable insights into users' cognitive states but is difficult to analyze due to its structured, non-linguistic nature. While large language models (LLMs) excel at reasoning over text, they struggle with temporal…
Large Language Models (LLMs) have revolutionized various fields with their exceptional capabilities in understanding, processing, and generating human-like text. This paper investigates the potential of LLMs in advancing Network Intrusion…