Related papers: A Novel IoT-based Framework for Non-Invasive Human…
An experimental testbed has been constructed to assess the capabilities of Light-Wave Sensing, a promising new vitals monitoring approach. A Light-Wave Sensing apparatus utilizes infrared radiation to contactlessly monitor the subtle…
With the advancement of the Internet of Things(IoT) and pervasive computing applications, it provides a better opportunity to understand the behavior of the aging population. However, in a nursing home scenario, common sensors and…
Smart devices in the Internet of Things (IoT) paradigm provide a variety of unobtrusive and pervasive means for continuous monitoring of bio-metrics and health information. Furthermore, automated personalization and authentication through…
Predicting incoming failures and scheduling maintenance based on sensors information in industrial machines is increasingly important to avoid downtime and machine failure. Different machine learning formulations can be used to solve the…
This paper discusses a vision based health monitoring system which would be very easy in use and deployment. Elder and sick people who are not able to talk or walk they are dependent on other human beings for their daily needs and need…
Various methods for designing input features have been proposed for fault recognition in rotating machines using one-dimensional raw sensor data. The available methods are complex, rely on empirical approaches, and may differ depending on…
The perception and recognition of the surroundings is one of the essential tasks for a robot. With preliminary knowledge about a target object, it can perform various manipulation tasks such as rolling motion, palpation, and force control.…
This paper describes a global framework that enables contactless human machine interaction using computer vision and machine learning techniques. The main originality of our framework is that only a very simple image acquisition device, as…
Smart healthcare which is built as healthcare Cyber-Physical System (H-CPS) from Internet-of-Medical-Things (IoMT) is becoming more important than before. Medical devices and their connectivity through Internet with alongwith the…
Internet of Things (IoT) systems continuously collect a large amount of data from heterogeneous "smart objects" through standardised service interfaces. A key challenge is how to use these data and relevant event logs to construct…
The spread of the novel coronavirus (COVID-19) has caused trillions of dollars in damages to the governments and health authorities by affecting the global economies. The purpose of this study is to introduce a connected smart paradigm that…
An infectious kind of disease affects a huge number of human beings. A lot of investigation being conducted throughout the world. There are many interactive hardware platform packages like IoT in healthcare including smart tracking, smart…
Sensor-based human activity recognition (HAR), i.e., the ability to discover human daily activity patterns from wearable or embedded sensors, is a key enabler for many real-world applications in smart homes, personal healthcare, and urban…
Managing access between large numbers of distributed medical devices has become a crucial aspect of modern healthcare systems, enabling the establishment of smart hospitals and telehealth infrastructure. However, as telehealth technology…
According to the World Health Organization, the rate of people aged 60 or more is growing faster than any other age group in almost every country, and this trend is not going to change in a near future. Since senior citizens are at high…
Malicious software is an integral part of cybercrime defense. Due to the growing number of malicious attacks and their target sources, detecting and preventing the attack becomes more challenging due to the assault's changing behavior. The…
Smartphones have ubiquitously integrated into our home and work environments, however, users normally rely on explicit but inefficient identification processes in a controlled environment. Therefore, when a device is stolen, a thief can…
This study investigates the use of large language models (LLMs) for human behavior understanding by jointly leveraging motion and video data. We argue that integrating these complementary modalities is essential for capturing both…
Seizure forecasting may provide patients with timely warnings to adapt their daily activities and help clinicians deliver more objective, personalized treatments. While recent work has convincingly demonstrated that seizure risk assessment…
We describe a novel metric-based learning approach that introduces a multimodal framework and uses deep audio and geophone encoders in siamese configuration to design an adaptable and lightweight supervised model. This framework eliminates…