Airbag Protection and Alerting System for Elderly People

Author:

Ibrahim Mariam1ORCID,Shawish Shuruq2,Aldroubi Sabri1,Dawoud Ali2,Abdin Walid2

Affiliation:

1. Department of Mechatronics Engineering, German Jordanian University, Amman 11180, Jordan

2. Department of Mechanical and Maintenance Engineering, German Jordanian University, Amman 11180, Jordan

Abstract

In the elderly population, falling is an important cause of severe injuries like hip injuries. Injury- or unconsciousness-related immobility implies that the affected are unable to seek assistance. Building fall detection systems is essential since it is usual for senior individuals residing alone to go many hours without being located after a fall, considerably increasing the impact of injuries caused by falls. The primary goal of this paper is to implement an airbag protection and alerting system for elderly people. The system can be installed on a waist belt as an airbag. It is connected wirelessly to the elderly person’s mobile, where an Android mobile application is created to receive alert notifications from the system. The system will detect the fall using a gravity sensor that is connected to an Arduino board. If a fall is detected by the gravity sensor, then the system will activate an air valve and inflate the airbag from the air tank. The system will also send a warning notification to the elderly person’s mobile application via Bluetooth. Then, the elderly person’s GPS location will be determined from their mobile phone and an SMS will be transmitted to a mobile phone belonging to his/her emergency contact of choice. The system is tuned to provide a proper fall detection sensitivity with good accuracy (90%). It has a relatively low cost, very quick response time (only 150 ms delay from the electrical grid), and low power consumption (11.1 Wh).

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference27 articles.

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3. Tomkun, J., and Nguyen, B. (2010). Design of a Fall Detection and Prevention System for the Elderly. [Bachelor’s Thesis, McMaster University Hamilton].

4. Li, Q., Stankovic, J.A., Hanson, M.A., Barth, A.T., Lach, J., and Zhou, G. (2009, January 3–5). Accurate, fast fall detection using gyroscopes and accelerometer-derived posture information. Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks, Berkeley, CA, USA.

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