| Autor: |
Polepaka Sanjeeva, Sangem Harshini, Aleti Amrutha Varshini, Ajjuri Akshitha, Mundher Adnan Myasar, B Swathi, Nagpal Amandeep, Kalra Ravi |
| Jazyk: |
English<br />French |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
E3S Web of Conferences, Vol 507, p 01025 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2267-1242 |
| DOI: |
10.1051/e3sconf/202450701025 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
