학술논문

Artificial Intelligence and IoT in Elderly Fall Prevention: A Review
Document Type
Periodical
Source
IEEE Sensors Journal IEEE Sensors J. Sensors Journal, IEEE. 24(4):4181-4198 Feb, 2024
Subject
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Robotics and Control Systems
Older adults
Monitoring
Artificial intelligence
Medical services
Sensors
Internet of Things
Intelligent sensors
Artificial intelligence (AI)
computer vision
elderly fall prevention
Internet of Things (IoT)
smart homes
wearable devices
Language
ISSN
1530-437X
1558-1748
2379-9153
Abstract
Globally, the number of falls among the elderly is rising, particularly among those 60 and older. An important contributing element to these falls is the fact that elderly people who live alone are not regularly supervised. A significant number of claims are filed for injuries caused by falls in the elderly, and at times, these falls result in fatalities. Therefore, wellfounded and practical e-health technologies are critical for elder care, particularly for individuals who live alone. One of the emerging and rapid-growing technologies, such as artificial intelligence (AI), would be an excellent companion for them to continuously monitor their health condition and prevent falls. This review article compares various research, surveys, studies, and experiments conducted on elderly fall prevention utilizing AI and other technologies, such as the Internet of Things (IoT), sensor, radio detection and ranging (RADAR), infrared (IR) radiation, and hardware technologies. It has been identified that in real time and long-term monitoring without human intervention, AI–IoT technology will be the best solution for fall prevention in older adults.