The National Sample Survey Organization (NSSO) has identified disability as a significant public health challenge in India, with a notable increase in limb loss, visual impairment, and other disabilities arising from factors such as wars, accidents, health issues, and aging. Many visually impaired individuals struggle with motor skills and strength, making traditional power wheelchairs problematic. Furthermore, the high cost of these wheelchairs renders them inaccessible to many. Caregiver workload in nursing and old-age homes is escalating due to a disproportionate ratio of disabled residents to caregivers. This research introduces a prototype for a Smart Wheelchair aimed at reducing accident risks and easing caregiver responsibilities. The wheelchair integrates various hardware and software elements coordinated via an Arduino Uno board. A primary feature is the Ultrasonic sensor, which measures distance and detects falls. In conjunction with this, a mobile application, Blynk, alerts caregivers immediately if the user experiences an accident, ensuring prompt response and increased safety.

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IoT-Enabled Smart Wheelchair System for Real-Time Fall Detection and Alerting

  • Swetarani Mishra,
  • Debabrata Dansana,
  • Brojo Kishore Mishra,
  • Tanmaya Bhoi

摘要

The National Sample Survey Organization (NSSO) has identified disability as a significant public health challenge in India, with a notable increase in limb loss, visual impairment, and other disabilities arising from factors such as wars, accidents, health issues, and aging. Many visually impaired individuals struggle with motor skills and strength, making traditional power wheelchairs problematic. Furthermore, the high cost of these wheelchairs renders them inaccessible to many. Caregiver workload in nursing and old-age homes is escalating due to a disproportionate ratio of disabled residents to caregivers. This research introduces a prototype for a Smart Wheelchair aimed at reducing accident risks and easing caregiver responsibilities. The wheelchair integrates various hardware and software elements coordinated via an Arduino Uno board. A primary feature is the Ultrasonic sensor, which measures distance and detects falls. In conjunction with this, a mobile application, Blynk, alerts caregivers immediately if the user experiences an accident, ensuring prompt response and increased safety.