Artificial Intelligence and IoT in Elderly Fall Prevention: A Review

Deepika Mohan, Duaa Zuhair Al-Hamid, Peter Han Joo Chong, Kalupahana Liyanage Kushan Sudheera, Jairo Gutierrez, Henry C.B. Chan, Hui Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

20 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)4181-4198
Number of pages18
JournalIEEE Sensors Journal
Volume24
Issue number4
DOIs
Publication statusPublished - 15 Feb 2024

Keywords

  • Artificial intelligence (AI)
  • computer vision
  • elderly fall prevention
  • Internet of Things (IoT)
  • smart homes
  • wearable devices

ASJC Scopus subject areas

  • Instrumentation
  • Electrical and Electronic Engineering

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