Abstract

Fall detection systems are crucial for ensuring the safety of the elderly, especially those who are wheelchair-bound. A potential remedy involves promptly detecting human falls in near real-time to facilitate rapid assistance. While various methods have been suggested for fall detectors, there remains a necessity to create precise and sturdy architectures, methodologies, and protocols for detecting falls, particularly among elderly individuals, especially those using wheelchairs. The objective is to design an affordable and dependable IoT-based system for detecting falls in wheelchair users, alerting nearby individuals for assistance and promote sustainable safety. The setup includes a MEMS Sensor, GSM module, and Arduino UNO microcontroller for detecting falls, with the goal of securing the well-being and promoting independent living for the elderly.

Details

Title
Promoting sustainable safety: Integrating fall detection for person and wheelchair safety
Author
Polepaka, Sanjeeva; Sangem, Harshini; Aleti, Amrutha Varshini; Ajjuri, Akshitha; Myasar Mundher Adnan; Swathi, B; Nagpal, Amandeep; Kalra, Ravi
Publication year
2024
Publication date
2024
Publisher
EDP Sciences
ISSN
25550403
e-ISSN
22671242
Source type
Conference Paper
Language of publication
English
ProQuest document ID
3180959927
Copyright
© 2024. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the terms of the License.