IOT system for fall detection.
A 3-member team researched the health hazard that accompanies "Falls" and explored different solutions to combat this problem. The team was organised in an agile manner utilising a Gantt Chart and commonly used communication tools, considering it was implemented during covid lockdown.
For a live demo of the system, look into "DEMO" folder!
We wanted to make a system that is:
- Accurate enough in detecting fall
- Capable of immediately alerting a 3rd person in call for help
- Capable of low power, constant use with great autonomy
- Compact and tiny enough for a comfortable wearable device.
- Low cost
Tech used:
- ESP32 DEVKIT1
- WIFI protocol
- I2C protocol with interrupts of ADXL345 (accelerometre)
- MQTT protocol for node control
- Node-RED for node communication and alerts
- Alert system both via telegram and via siren node
In the end, such an IOT system was designed, implemented and tested with the following characteristics/functionalities:
- Battery monitoring-low consumption techniques (ex. Deep Sleep mode and interrupts)
- Fall detection algorithm inside the MCU
- Wifi connection
- Wifi credentials storage in Flash memory
- MQTT protocol and communication with NODE-red server
- Telegram Chatbot for alerts
- Siren esp32 node for sound alert.
As an end result, an academic paper was also written, containing all the above mentioned research plus testing results (85% TP 90% TN). The paper will not be published here, but I strongly encourage you to check the DEMO file in this github repo to see the device in live demos!
- Dimitrios Lampros
- Andreas Chadoumellis
- Paris Stentoumis
Mentor: Dimitris Karagiannis