Multilayer Neural Network Based Fall Alert System Using IOT

  • Shareefa Ahmad Abu Shahada
  • Suzan Mohammed Hreiji
  • Saleh Ibrahim Atudu
  • Shermin Shamsudheen
Keywords: Fall, IoT, neural network , sensors, accelerometer, GSM.


Fall in elderly people staying alone is a health concern which draws the attention of researchers in past years. In this research, we develop an elderly monitoring system using advanced technology based on sensors and the Internet of Things. In this system, older people can avoid any interaction with healthcare institutions like nursing home and hospitals. We present this challenge by establishing a smart setup to monitor human behavior through accelerometer, pulse sensor and GSM. To implement this concept, we used an alert system to the personal care assistant, to monitor the data using different learning methods. Based on Multi-layer Neural Network technique data are collected from the sensors, then processed and passed to the server in the form of an alert through the buzzer, SMS, email or voice message. The result obtained show an accuracy level of 96% compared to other classifiers.


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Author Biographies

Shareefa Ahmad Abu Shahada

Student, Department of Computer Science, Jazan University, Saudi Arabia

Suzan Mohammed Hreiji

Student, Department of Computer Science, Jazan University, Saudi Arabia.

Saleh Ibrahim Atudu

Student, Department of Computer Science, Jazan University, Saudi Arabia.

Shermin Shamsudheen

Faculty of Computer Science and Information systems, Jazan University, Saudi Arabia


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