Wearables and the Internet of Things (IoT), applications, opportunities, and challenges: A Survey
Smart wearables collect and analyze data, and in some scenarios make a smart decision
and provide a response to the user and are finding more and more applications in our daily …
and provide a response to the user and are finding more and more applications in our daily …
Human activity recognition for healthcare using smartphones
G Ogbuabor, R La - Proceedings of the 2018 10th international …, 2018 - dl.acm.org
The healthcare benefits associated with regular physical activity monitoring and recognition
has been considered in several research studies. Solid evidence shows that regular …
has been considered in several research studies. Solid evidence shows that regular …
Wearable computing for Internet of Things: A discriminant approach for human activity recognition
With the rapid development of the wireless sensor network and the continuous improvement
of its key technologies, the concept of Internet of Things has been encouraged and extended …
of its key technologies, the concept of Internet of Things has been encouraged and extended …
Human activity recognition from multiple sensors data using deep CNNs
Smart devices with sensors now enable continuous measurement of activities of daily living.
Accordingly, various human activity recognition (HAR) experiments have been carried out …
Accordingly, various human activity recognition (HAR) experiments have been carried out …
Early detection of Potato Disease using an enhanced convolutional neural network-long short-term memory Deep Learning Model
Potato diseases pose a significant threat to farmers, impacting potato crops' productivity,
quality, and financial stability. Among the most notorious diseases is late blight, caused by …
quality, and financial stability. Among the most notorious diseases is late blight, caused by …
Employing a deep convolutional neural network for human activity recognition based on binary ambient sensor data
G Mohmed, A Lotfi, A Pourabdollah - Proceedings of the 13th ACM …, 2020 - dl.acm.org
Due to rising cost of social care, the number of older adults who prefer to live independently
in their own home has increased. The independent lifestyle cannot be achieved if the elderly …
in their own home has increased. The independent lifestyle cannot be achieved if the elderly …
Toward the personalization of biceps fatigue detection model for gym activity: an approach to utilize wearables' data from the crowd
Nowadays, wearables-based Human Activity Recognition (HAR) systems represent a
modern, robust, and lightweight solution to monitor athlete performance. However, user data …
modern, robust, and lightweight solution to monitor athlete performance. However, user data …
The most important variables associated with death due to COVID‐19 disease, based on three data mining models Decision Tree, AdaBoost, and Support Vector …
BS Gharehhasani, M Rezaei, A Naghipour… - Health Science …, 2024 - Wiley Online Library
Introduction Death due to covid‐19 is one of the biggest health challenges in the world.
There are many models that can predict death due to COVID‐19. This study aimed to fit and …
There are many models that can predict death due to COVID‐19. This study aimed to fit and …
[PDF][PDF] Survey on soft computing approaches for human activity recognition
MV Kharat, KH Walse, RV Dharaskar - Int. J. Sci. Res, 2017 - researchgate.net
Human activity recognition is intrinsic area of exploration just because of its real world's
applications. The sensors included smart phones are used to recognize activity. Mobile …
applications. The sensors included smart phones are used to recognize activity. Mobile …
A supervised autoencoder for human activity recognition with inertial sensors
J An, Y Kwon, YS Cho - 2023 IEEE International Conference on …, 2023 - ieeexplore.ieee.org
Human Activity Recognition (HAR) with inertial sensors is one of the most active research
fields. Various machine learning algorithms have been proposed in HAR for classifying …
fields. Various machine learning algorithms have been proposed in HAR for classifying …