A group of Electronics Engineering (ECE) students won the Best Project Award anew in the recently held TechnoFest 2022.
Team “AIDerLy”, composed of Charles Andrew Q. Bugarin, Juan Miguel M. Lopez, Scud Gabriel M. Pineda, and Ma. Franzeska C. Sambrano (who single-handedly bagged the Best Presenter award as well), impressed the panelists with their one-of-a-kind, non-invasive fall detection system for the elderly.
A closer look inside the Non-invasive Fall Detection System created by ECE students
“Our project is a vision-based fall detection system ported on a smartphone application that utilizes deep learning trained and tested from multiple RGB camera setups. In the event of a fall, the system is designed to provide an on-premises auditory alarm, an IoT notification, and a real-time video feed via the smartphone app,” Sambrano explained.
The occurrence of unwanted falls among the elderly remains a cause for worry and a threat to their health. In fact, the Centers for Disease Control and Prevention says that each year, millions of older people—those 65 and older—fall.
Sambrano shared how much they wanted to help the elderly, more so because of their deep love and connection to their parents and grandparents. “In technology, we believe that no one should be left behind and now is the time to make technological advancements in elderly care.”
LOOK: Development phase of the fall detection system
Technically speaking, the system’s hardware is composed of an RGB camera, a Piezo buzzer, and a Raspberry Pi 4B. When a fall activity is detected, the camera captures the video and processes the data through the RPi. The system will then trigger an on-premises alarm via the Piezo Buzzer and simultaneously, the elderly’s family member/s will receive an IoT notification. The system also provides real-time monitoring of the fall activity so users can request assistance right away.
After the TechnoFest presentation, the panelists commended the project, and Dr. Pocholo James M. Loresco, AIDerLy’s thesis adviser, encouraged the team to publish it and participate in different academic research competitions.
“The most exciting part of doing this project is when the system is up and running, and the detection is stable,” Sambrano said. “Winning the Best Project in TechnoFest 2022 is a first for our team, but definitely not the last.”
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