Smart Home Activity Recognition for Ambient Assisted Living (AAL)

Title

Smart Home Activity Recognition for Ambient Assisted Living (AAL)

Creator

Naaz S.; Rajamohan K.

Description

With the increasing age of an individual, the chances of being prone to chronic diseases like diabetes or non-curable diseases like Alzheimer's Syndrome or Parkinson's Syndrome increases. Due to the health issues, elderly must be accompanied by caretakers to monitor their well-being at all times. With growing responsibilities and work pressure, the family members may find it challenging to find a trustworthy caretaker. In such scenarios, an assisted living environment acts as a boon. A normal home embedded with different sensors to monitor an individual's well-being is called as Ambient Assisted Living(AAL). This living environment detects anomalous behaviour and recognizes human activities. In this research paper, a smart home activity recognition model is proposed and implemented using four machine learning algorithms using six different publicly available datasets. It has been observed that Random Forest machine learning algorithm shows the best accuracy on most of the dataset. The Electrochemical Society

Source

ECS Transactions, Vol-107, No. 1, pp. 20253-20264.

Date

2022-01-01

Publisher

Institute of Physics

Coverage

Naaz S., Department of Computer Science, CHRIST University, Karnataka, Bangalore, India; Rajamohan K., Department of Computer Science, CHRIST University, Karnataka, Bangalore, India

Rights

Restricted Access

Relation

ISSN: 19386737; ISBN: 978-160768539-5

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1149/10701.20253ecst

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134056767&doi=10.1149%2f10701.20253ecst&partnerID=40&md5=2be1cad2071bf04aa3980c3a4839407e