Journal
JOURNAL OF SENSOR AND ACTUATOR NETWORKS
Volume 6, Issue 4, Pages -Publisher
MDPI
DOI: 10.3390/jsan6040028
Keywords
e-health; human activity recognition (HAR); Internet of Things (IoT); rule tree classifier; C4.5; Bayesian classifier
Categories
Funding
- Pontificia Universidad Javeriana (PUJ) in Bogota, Colombia under the project framework Centro de Excelencia y Apropiacion en Internet de las Cosas (CEA-IoT)
- Colombian Ministry for the Information and Communications Technology (Ministerio de Tecnologias de la Informacion y las Comunicaciones-MinTIC)
- Colombian Administrative Department of Science [FP44842-502-2015]
Ask authors/readers for more resources
This paper presents a novel system based on the Internet of Things (IoT) to Human Activity Recognition (HAR) by monitoring vital signs remotely. We use machine learning algorithms to determine the activity done within four pre-established categories (lie, sit, walk and jog). Meanwhile, it is able to give feedback during and after the activity is performed, using a remote monitoring component with remote visualization and programmable alarms. This system was successfully implemented with a 95.83% success ratio.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available
Share Paper
