Artificial Intelligence and IoT in Elderly Fall Prevention: A Review

• Published in: IEEE sensors journal Vol. 24; no. 4; pp. 4181 - 4198
• Main Authors: Mohan, Deepika, Al-Hamid, Duaa Zuhair, Chong, Peter Han Joo, Sudheera, Kalupahana Liyanage Kushan, Gutierrez, Jairo, Chan, Henry C. B., Li, Hui
• Format: Journal Article
• Language: English
• Published: New York IEEE 15-02-2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial intelligence; Artificial intelligence (AI); computer vision; elderly fall prevention; Falls; Infrared radar; Infrared radiation; Intelligent sensors; Internet of Things; Internet of Things (IoT); Medical services; Monitoring; Older adults; Older people; Radar detection; Sensors; smart homes; wearable devices
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2023.3344605

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.