Abstract
Ambient Assisted Living (AAL) systems aim to enable the elderly people to stay active and live independently into older age by monitoring their behaviour, provide the needed assistance and detect early signs of health status deterioration. Non-intrusive sensors are preferred by the elderly to be used for the monitoring purposes. However, false positive or negative triggers of those sensors could lead to a misleading interpretation of the status of the elderlies. This paper presents a systematic literature review of the sensor failure detection and fault tolerance in AAL equipped with non-intrusive, event-driven, binary sensors. The existing works are discussed, and the limitations and research gaps are highlighted.
Highlights
According to the World Health Organization, the world’s population percentage of people aged over 60 is expected to double in the decades to increase from 12% in 2015 to 22% in 2050.This phenomenon, known as Ageing Population, can be already witnessed in high-income countries.This demographic shift will induce new challenges to the countries, e.g., preparing the health care and social systems to deal with higher capacities [1]
We provide a state-of-the-art review for the sensor failure detection systems and fault tolerance methods in the presence of sensor failures in Ambient Assisted Living (AAL) systems equipped with non-intrusive, binary, event-driven sensors
The research works are categorized according to the function of the proposed systems as well as the approach that their methods are based on: correlation-based fault detection, model-based fault detection, fault-tolerant location tracking, fault-tolerant activity recognition or fault detection and diagnosis framework for AAL, respectively
Summary
According to the World Health Organization, the world’s population percentage of people aged over 60 is expected to double in the decades to increase from 12% in 2015 to 22% in 2050.This phenomenon, known as Ageing Population, can be already witnessed in high-income countries.This demographic shift will induce new challenges to the countries, e.g., preparing the health care and social systems to deal with higher capacities [1]. According to the World Health Organization, the world’s population percentage of people aged over 60 is expected to double in the decades to increase from 12% in 2015 to 22% in 2050. This phenomenon, known as Ageing Population, can be already witnessed in high-income countries. Taking care of the elderlies would decrease the chance of further complications to their health status This can be achieved by providing care in nursing homes or hospitals. The authors in [13] have presented another three perspectives for classification: Fault-tolerant distributed system viewpoint, that is based on the behaviour of the failed sensor, e.g., crash and omission. For sensor networks in general, two perspectives for fault type classification in sensor networks was proposed by [12]: Data-centric viewpoint, which is based on the characteristics of sensor readings, e.g., stuck-at and spike.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
